https://learnlab.org/research/wiki/api.php?action=feedcontributions&user=Dmbelenk&feedformat=atomLearnLab - User contributions [en]2024-03-29T07:29:00ZUser contributionsMediaWiki 1.31.12https://learnlab.org/wiki/index.php?title=Nokes_-_Game_environments_for_Chemistry&diff=12319Nokes - Game environments for Chemistry2011-12-10T17:59:33Z<p>Dmbelenk: </p>
<hr />
<div>==Summary Table==<br />
{| border="1" cellspacing="0" cellpadding="5" style="text-align: left;"<br />
| '''PIs''' || Tim Nokes, David Yaron<br />
|-<br />
| '''Other Contributers''' || Daniel Belenky, Michael Karabinos <br />
|-<br />
| '''Study Start Date''' || February, 2010<br />
|-<br />
| '''Study End Date''' || Ongoing<br />
|-<br />
| '''LearnLab Site''' || ChemCollective web site, and Carnegie Mellon Modern Chemistry (09-106)<br />
|-<br />
| '''LearnLab Course''' || Chemistry<br />
|-<br />
| '''Number of Students''' || 500 per month on web site, 150 in CMU class<br />
|-<br />
| '''Total Participant Hours''' || 500 per month on web site, 450 in CMU class<br />
|-<br />
| '''DataShop''' || https://pslcdatashop.web.cmu.edu/DatasetInfo?datasetId=504 <br />
*Log files of student interactions with virtual lab and other instructional materials.<br />
|}<br />
<br />
==Abstract==<br />
This set of studies is built around two gaming environment in the chemistry learnlab. The first is online murder mystery activity that currently is carried out by about 500 students per month. The second is a chemistry game being built around the ChemCollective virtual lab.<br />
==Background & Significance==<br />
==Glossary==<br />
==Research questions==<br />
===Study One===<br />
Mixed Reception (http://www.chemcollective.org/mr/) is a online game activity in which students investigate a murder. Students use chemistry topics that are typically covered in the first few months of a high school chemistry course to solve the mystery. In addition, the mystery is set in a chemistry research group and is designed to expose students to the goals and processes of modern chemistry research.<br />
====Hypothesis====<br />
Engagement with a game set in an authentic chemistry context will alter students attitudes regarding the domain of chemistry and their perceptions of themselves as relates to science careers.<br />
====Independent Variables====<br />
This activity is freely available on the web. A questionaire is being added to the beginning of the activity to determine the instructional context (Is this activity part of a course? If so, what course?). Students are randomly partitioned into groups that differ only in the set of questions asked before and after engagement with the activity.<br />
====Dependent Variables====<br />
Students will be given a short questionaire at the start and the end of the activity. The questions are chosen from a pool that includes questions on self-efficacy, learning goals and career goals.<br />
====Results====<br />
The study is now designed and the Mixed Reception web site is being updated for data collection.<br />
====Explanation====<br />
<br />
===Study Two===<br />
The ChemCollective virtual lab has a curriculum base of about 100 activities. Many of these activities fall in the category or analytical chemistry, where students are asked to determine the contents of a solution (identifying the identity of the chemical species and/or their amounts). Such activities can be recast in a one-one-one game format. The game begins by having each student prepare a solution (the opponent's unknown) that they believe their opponent will have a hard time identifying. (The contents are constrained in a way that sets the difficulty level of the game, for instance, an easy level would be one strong acid, and a hard level would be a mixture of a weak acid and a weak base.) The students then take turn performing an experiment on their unknown solution, and can opt to use their turn to guess at the contents. <br />
====Hypothesis====<br />
====Independent Variables====<br />
An advantage of this game format is that each game can be cast in a non-game format that is highly parallel with regards to domain content: students can be given an unknown and asked to identify its contents, they can be given an unknown and asked to identify its contents with the fewest possible number of experiments, or they can play against an opponent as described above.<br />
====Dependent Variables====<br />
Data will be collected on interactions with the virtual lab, along with measures of student learning.<br />
====Results====<br />
====Explanation====<br />
This study is under design for deployment in late March 2010.<br />
<br />
==Further Information==<br />
===Connections to Other Studies===<br />
===Annotated Bibliography===<br />
===References===<br />
===Future Plans===</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Nokes_-_Game_environments_for_Chemistry&diff=12318Nokes - Game environments for Chemistry2011-12-10T17:07:31Z<p>Dmbelenk: </p>
<hr />
<div>==Summary Table==<br />
{| border="1" cellspacing="0" cellpadding="5" style="text-align: left;"<br />
| '''PIs''' || Tim Nokes, David Yaron<br />
|-<br />
| '''Other Contributers''' || Daniel Belenky, Michael Karabinos <br />
|-<br />
| '''Study Start Date''' || February, 2010<br />
|-<br />
| '''Study End Date''' || Ongoing<br />
|-<br />
| '''LearnLab Site''' || ChemCollective web site, and Carnegie Mellon Modern Chemistry (09-106)<br />
|-<br />
| '''LearnLab Course''' || Chemistry<br />
|-<br />
| '''Number of Students''' || 500 per month on web site, 150 in CMU class<br />
|-<br />
| '''Total Participant Hours''' || 500 per month on web site, 450 in CMU class<br />
|-<br />
| '''DataShop''' || Log files of student interactions with virtual lab and other instructional materials.<br />
|}<br />
<br />
==Abstract==<br />
This set of studies is built around two gaming environment in the chemistry learnlab. The first is online murder mystery activity that currently is carried out by about 500 students per month. The second is a chemistry game being built around the ChemCollective virtual lab.<br />
==Background & Significance==<br />
==Glossary==<br />
==Research questions==<br />
===Study One===<br />
Mixed Reception (http://www.chemcollective.org/mr/) is a online game activity in which students investigate a murder. Students use chemistry topics that are typically covered in the first few months of a high school chemistry course to solve the mystery. In addition, the mystery is set in a chemistry research group and is designed to expose students to the goals and processes of modern chemistry research.<br />
====Hypothesis====<br />
Engagement with a game set in an authentic chemistry context will alter students attitudes regarding the domain of chemistry and their perceptions of themselves as relates to science careers.<br />
====Independent Variables====<br />
This activity is freely available on the web. A questionaire is being added to the beginning of the activity to determine the instructional context (Is this activity part of a course? If so, what course?). Students are randomly partitioned into groups that differ only in the set of questions asked before and after engagement with the activity.<br />
====Dependent Variables====<br />
Students will be given a short questionaire at the start and the end of the activity. The questions are chosen from a pool that includes questions on self-efficacy, learning goals and career goals.<br />
====Results====<br />
The study is now designed and the Mixed Reception web site is being updated for data collection.<br />
====Explanation====<br />
<br />
===Study Two===<br />
The ChemCollective virtual lab has a curriculum base of about 100 activities. Many of these activities fall in the category or analytical chemistry, where students are asked to determine the contents of a solution (identifying the identity of the chemical species and/or their amounts). Such activities can be recast in a one-one-one game format. The game begins by having each student prepare a solution (the opponent's unknown) that they believe their opponent will have a hard time identifying. (The contents are constrained in a way that sets the difficulty level of the game, for instance, an easy level would be one strong acid, and a hard level would be a mixture of a weak acid and a weak base.) The students then take turn performing an experiment on their unknown solution, and can opt to use their turn to guess at the contents. <br />
====Hypothesis====<br />
====Independent Variables====<br />
An advantage of this game format is that each game can be cast in a non-game format that is highly parallel with regards to domain content: students can be given an unknown and asked to identify its contents, they can be given an unknown and asked to identify its contents with the fewest possible number of experiments, or they can play against an opponent as described above.<br />
====Dependent Variables====<br />
Data will be collected on interactions with the virtual lab, along with measures of student learning.<br />
====Results====<br />
====Explanation====<br />
This study is under design for deployment in late March 2010.<br />
<br />
==Further Information==<br />
===Connections to Other Studies===<br />
===Annotated Bibliography===<br />
===References===<br />
===Future Plans===</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=PSLC_GradStudents&diff=12289PSLC GradStudents2011-09-26T18:29:22Z<p>Dmbelenk: </p>
<hr />
<div>The purpose of this page is to serve as a repository of information relevant for grad students. We hope to maintain this page as a repository of current and relevant information for graduate students currently affiliated with the PSLC, as well as grad students who hope to be in the PSLC. <br />
<br />
== Announcements==<br />
<br />
1) '''NSF Site Visit''': October 5-6, 2011<br />
<br />
PSLC will be having its site visit with representatives from the National Science Foundation on Wednesday and Thursday October 5th and 6th. <br />
<br />
This visit is a pretty big deal, as it allows the PSLC to justify its existence to NSF and prove to them that they should keep funding us. For the next few years at least. <br />
<br />
I don't think we have a finalized schedule yet, but please try to set aside as much time on those few days to come and listen to the presentations. We like to have a good showing from the grad students. <br />
<br />
<br />
In particular, there are two events that everyone involved in the PSLC should attempt to go to:<br />
<br />
a. ''The Graduate Student/Post-Doc SWOT analysis- '''October 5th from 11:25am-12:25pm''' (Lunch provided); Newell-Simon Hall, room 3305 <br />
<br />
*Each year the grads and post-docs are asked to do an analysis of the Strengths, Weaknesses, Opportunities, and Threats of the PSLC. The first 10-15 minutes of this, Dan Belenky will be presenting our official list. The rest of the time will be open discussion with the NSF visitors about our position as grad students. This is a great opportunity to voice your concerns (or hear your concerns voiced) and to get feedback on how to go about affecting change. <br />
<br />
b. "Poster Session- October 5th from 1:10-2:10pm; final location TBA"<br />
<br />
2) '''Next Month's Meeting'''- Date/Time TBD<br />
<br />
Next month's meeting will probably be the annual Welcome New Grad Students meeting, where we describe what the PSLC is and how to get involved.<br />
Before that, we woud like to get the Wiki page all up to date. <br />
<br />
If you can think of information that you would like listed on the Wiki page, or have suggestions on how to improve it, please e-mail Colleen Davy at cdavy1@andrew.cmu.edu and let her know. <br />
<br />
3) PSLC grads are now responsible for keeping the [http://www.learnlab.org/research/wiki/index.php/PSLC_People#Graduate_Students List of PSLC Grads] up to date. <br />
<br />
* If you know of someone who should be added (or deleted) from this list please e-mail the webmaster at bef25@pitt.edu. Alternatively, feel free to go in and update the list yourself!<br />
<br />
== Meeting Notes==<br />
'''Cognitive Factors'''<br />
<br />
''September 24, 2010''<br />
<br />
Welcome to the new members!<br />
<br />
Send Ruth email if you (or any new collaborators, post-docs, grad students) need to be added to the cognitive factors d-list<br />
<br />
Send Jo email if you need to be added to the general PSLC d-list<br />
<br />
Advisory board dates - January 20 & 21, 2011 (Thur and Fri)<br />
<br />
Speaker Series - Rob Goldstone has agreed to come (probably before the AB)<br />
<br />
Handout: Cognitive Factors Thrust Plan, if see you see errors send them to Chuck (link to document coming soon)<br />
<br />
In general for Annual Report and Strategic Plan it is important to have non-text contributions; send screenshots/pictures of interventions and/or graphs of results as they come up<br />
<br />
Also as a general reminder, it is never too early to send bullets of exciting findings, usually collected at least once a year<br />
<br />
Talk: How does learning to write help learning to read Chinese (fMRI study) - Fan Cao Abstract Two types of instructions were given to a group of English speakers who learn Chinese as a L2. One is character writing and the other is pinyin writing. The hypothesis is that writing will facilitate the integration of orthographic, phonological and semantic representations by involving both perception and production and by emphasizing the special features of Chinese characters. fMRI scans found that sensory-motor cortex and visual-spatial representation cortex are more involved if the subject had writing experience. We also found that writing training produced more elaborated representations of orthography, phonology and semantics in the brain as compared to pinyin training.<br />
<br />
Slides here: Media:PSLC_Sep_24_1.pdf<br />
<br />
Next up: Colleen Davy will speak at the October meeting, likely the last week of Oct at CMU<br />
<br />
'''Grad student meeting notes: 11/15/2010'''<br />
<br />
1) Discussion of iSLC Conference: March 25th-27th, 2011<br />
<br />
Theme: researching communication and communicating language<br />
<br />
If you are interested in giving a talk or a poster, e-mail Colleen Davy at cdavy1@andrew.cmu.edu. You might also be interested in some of the workshops at iSLC. Current proposals for workshops include sessions on CLAN and the R statistical package.<br />
<br />
Colleen needs organizers to help decide on the placement/division of themes for poster sessions and symposia.<br />
<br />
Graduate students need to discuss their role in the Ultimate Block Party at the iSLC.<br />
<br />
2) Advisory board meeting: January 20th -21st<br />
<br />
Theme: PSLC sustainability<br />
<br />
Graduate students and post-docs will present a SWOT analysis.<br />
<br />
Grad students and post docs can present posters at the session. Grad students and post-docs from all thrusts are encouraged to present posters.<br />
<br />
3) Meeting with post-docs: December 6th, 2010<br />
<br />
We will prepare a joint post-doc/grad SWOT analysis to present at the advisory board meeting.<br />
<br />
== FAQs==<br />
<br />
'''1. What does it take to be a PSLC grad student?'''<br />
<br />
Well, there are basically three ways you can be considered a PSLC grad student.<br />
<br />
a. You work on a project that receives funding from the PSLC.<br />
<br />
b. Your advisor or collaborator receives funding from the PSLC and asks you to be involved.<br />
<br />
c. You want to be a PSLC grad student.<br />
<br />
<br />
'''2. What types of opportunities does the PSLC have for a grad student like me?''' <br />
<br />
There are a variety of different levels of involvement and types of activities that the PSLC offers. <br />
<br />
For the casual grad student, the PSLC organizes a speaker series with talks that may be of interest to students interested in the learning sciences. These are open to whomever wishes to go. There are also monthly lunch meetings where people associated with the PSLC can give a talk on their work. <br />
<br />
The grad student community also hopes to organize events catered toward grad students, with topics like applying for grants, finding jobs, collaboration with people at other universities, etc. These are also open to the public. <br />
<br />
For those who wish to get more involved, the grad student community also has monthly meetings to discuss center-wide issues, read and discuss articles we believe are relevant, plan future events, etc. Again, these are open to the public. <br />
<br />
Finally, each thrust has regular or semi-regular meetings to discuss the thrust's theoretical framework, set the research agenda, and discuss the progress of projects within that thrust. While these are open to anyone, they're probably of limited interest unless you currently have or have had a project affiliated with the thrust. <br />
<br />
<br />
<br />
'''3. What is expected of me as a PSLC grad student?'''<br />
<br />
If you receive funding from the PSLC, you are expected, to the extent it is possible, to attend the thrust meetings for your relevant thrust, and attend the monthly PSLC lunches. The grad student community also encourages you to come to the grad student monthly meetings, of course.<br />
<br />
If you don't receive funding from the PSLC, but still wish to be a part of the grad student community, your level of involvement is up to you. <br />
<br />
<br />
'''How do I find out about upcoming talks/meetings/events?'''<br />
<br />
One option is to check the Announcements section of this page. A possibly better option would be to get on our mailing list. To do that, e-mail Jo Bodnar at jobodnar AT cs.cmu.edu and ask to be put on the PSLC general mailing list and grad student mailing list. <br />
<br />
There is also a regularly updated calendar at our [http://www.learnlab.org main webpage] that gives a fairly complete account of most PSLC events.<br />
<br />
<br />
<br />
4. '''I already consider myself a PSLC grad, and want to be included on this page! What do I have to do?'''<br />
<br />
Well the great thing about the wiki page is that anybody can update it whenever they want! So, if you have an account here, and you know how to edit tables, you can just log in and add yourself! <br />
<br />
The table formatting is a bit weird and hard to follow, so if you want to add yourself, the easiest thing to do is just copy this text:<br />
<br />
<pre><br />
|-<br />
| Name || University || Advisor || e-mail address || Bio || Personal Webpage || Link to PSLC project page [Project page URL Project page title]<br />
</pre><br />
<br />
and paste it into the appropriate place on the table. With your own information, of course. <br />
<br />
If you don't have an account already, you can easily request one by clicking the "login/create account" button on the top right hand corner of the screen and following the instructions. Once you have an account, you can just click "Edit" above the table, and you can add yourself. <br />
<br />
<br />
<br />
5. '''But that's such a pain! Isn't there an easier way?!'''<br />
<br />
There sure is! If you don't want to make all that effort just to have your name and e-mail address on a page, just send your info (you could even put it in the format given above!) to our Wikimaster (yep, we made that word up!), Ben Friedline, at bef25 AT pitt.edu, and he'll put it on here.<br />
<br />
<br />
== Who Do I Ask About _______? ==<br />
<br />
This is often cited as being the most frustrating part of being a new grad student wanting to get involved, and by far "the" most frequently asked question, so we created a separate section for it. <br />
<br />
''Getting on the mailing lists''<br />
<br />
To get on the mailing lists, the best thing to do is e-mail Jo Bodnar at bodnar AT CMU.edu. She is going to need to know which mailing lists you want to be on. You have several options. <br />
<br />
1. The PSLC-PIER Distribution List<br />
Signing up for this one is going to get you the most e-mails, but if you want to be involved in the learning sciences community, this is a good one to be on. <br />
<br />
This will give you emails about talks and meetings of general interest to people in the learning sciences community- the PIER Speaker Series, the PIER student EdBags, PSLC All Hands meetings and Speaker Series, Dissertation Proposals and Defenses, etc. You will also get e-mails about more specific meetings, like the course committee meetings and thrust meetings, which may not be of interest to you unless you are involved in those thrusts. <br />
<br />
Oh. And you'll get a billion job posting e-mails from David Klahr as well. <br />
<br />
2. The Graduate Student Distribution List<br />
If you're a grad student, definitely ask to put on this list. This is the list where we plan and announce our events. <br />
<br />
3. The Thrust Distribution Lists<br />
If you should be on any of these lists, you'll know it. I'm also not entirely sure Jo can get you on these lists, but at the very least she will know who to talk to to get you on it. <br />
<br />
But really, if no one has instructed you to get on this list, you probably don't need to.<br />
<br />
''Getting Involved With Research''<br />
<br />
Unfortunately, there is just no easy answer for this. You'll need to do some research- our suggestion would be going to the Thrust pages (on the left side of the page) and reading up on them and trying to find a project you might be interested in, and talking to the PI. Or, if there's a thrust you're interested in, start showing up to the meetings. <br />
<br />
''Getting My Name On the Wiki Page'<br />
<br />
You can check out the FAQs section for instructions on how to add yourself, or you can just e-mail Colleen Davy at cdavy1@andrew.cmu.edu and give her your Name, Institution/Department, Advisor, E-mail, a short Bio, and your personal webpage and/or Wiki page, and she'll add it for you.<br />
<br />
== Who are the PSLC grads? ==<br />
<br />
{| border=1 cellspacing="0" cellpadding="5" style="text-align: left;"<br />
|-<br />
! Grad Student Name<br />
! University/Department<br />
! Advisor<br />
! E-mail<br />
! Bio<br />
! Personal Webpage<br />
! PSLC Projects<br />
|-<br />
| Turadg Aleahmad || Carnegie Mellon, HCII || Ken Koedinger & John Zimmerman || turadg@cmu.edu || My research is in design methods for theory-driven educational technology. || [http://www.cs.cmu.edu/~taleahma] || <br />
|-<br />
| Daniel Belenky || University of Pittsburgh || Timothy Nokes || dmb83@pitt.edu || I am interesting in issues of motivation and cognition. Specifically, I have been studying how achievement goals influence transfer. || N/A || [http://www.learnlab.org/research/wiki/index.php/Nokes_-_Dialectical_Interaction_and_Robust_Learning Dialectical Interaction and Robust Learning]<br />
|-<br />
| Colleen Davy || Carnegie Mellon/Psychology || Brian MacWhinney || cdavy1@andrew.cmu.edu || I am interested in how adult second language learners develop fluent speaking skills in their second language. || N/A || [http://www.learnlab.org/research/wiki/index.php/Davy_%26_MacWhinney_-_Spanish_Sentence_Production Spanish Sentence Production]<br />
|-<br />
| Susan Dunlap || University of Pittsburgh || Charles Perfetti || sud4@pitt.edu || My research areas include second language learning, reading, and spelling || n/a || [http://www.learnlab.org]<br />
|-<br />
| Benjamin Friedline || University of Pittsburgh || Alan Juffs || bef25@pitt.edu || I am interested in how adult second language learners acquire morphology in a second language. || N/A || [http://www.learnlab.org/research/wiki/index.php/Juffs_-_Feature_Focus_in_Word_Learning Feature Focus in Word Learning]<br />
|-<br />
| Nora Presson || Carnegie Mellon, Psychology || Brian MacWhinney || presson@cmu.edu || I am studying how practice conditions can improve learning of second language grammar, especially testing the effects of explicit instruction. || || [http://www.learnlab.org/research/wiki/index.php/Presson_%26_MacWhinney_-_Second_Language_Grammar Second Language Grammar Instruction]<br />
|-<br />
| Mary Lou Vercellotti || University of Pittsburgh || Dr. Nel de Jong || marylou.vercellotti@gmail.com || My research looks at complexity, accuracy, and fluency in the oral production of English as a second language. || N/A || [http://www.learnlab.org/research/wiki/index.php/Fostering_fluency_in_second_language_learning Refinement and Fluency]<br />
|-<br />
| Ruth Wylie || Carnegie Mellon, HCII || Ken Koedinger & Teruko Mitamura || rwylie@cs.cmu.edu || I'm interested in second language learning and self-explanation. || [http://ruthwylie.wordpress.com/ http://www.cs.cmu.edu/~rwylie] || [http://www.learnlab.org/research/wiki/index.php/Wylie_-_Intelligent_Writing_Tutor Self-Explanation and ESL]<br />
|}<br />
<br />
== Science of Learning Relevant Courses ==<br />
The PIER program offers three courses -- see the [http://www.cmu.edu/pier PIER Web page]<br />
<br />
See also the courses taught be any of the PSLC faculty.<br />
<br />
(Please add the names of relevant courses and web pointers if possible!)<br />
<br />
<br />
<pre><br />
05832 / 05432 Cognitive Modeling & Intelligent Tutoring Systems<br />
3:00pm-4:20pm, Tuesdays and Thursdays, Fall 2010<br />
Room 3002, Newell-Simon Hall, Carnegie Mellon University<br />
9 units<br />
Dr. Vincent Aleven, aleven@cs.cmu.edu<br />
</pre><br />
<br />
Students in this course will learn about the Cognitive Tutor technology that has been demonstrated to dramatically enhance student learning in domains like math, science, and computer programming. This type of tutoring software is currently in use in 2,700 schools around the country and is used extensively as platform for learning sciences research. The technology is grounded in artificial intelligence, cognitive psychology, and cognitive task analysis. Students will learn data-driven and theoretical methods for analyzing human problem solving and will learn to use such data to inform the design of intelligent tutoring systems. Course projects will focus on the development of an intelligent tutor using CTAT, the Cognitive Tutor Authoring Tools (see http://ctat.pact.cs.cmu.edu). Some assignments will focus on creating cognitive models in the Jess production rule modeling language.<br />
<br />
Students should either have programming skills, or experience in the cognitive psychology of human problem solving, or HCI / design skills, or permission from the instructor.</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=PSLC_GradStudents&diff=11073PSLC GradStudents2010-09-28T15:15:32Z<p>Dmbelenk: /* Who are the PSLC grads? */</p>
<hr />
<div>The purpose of this page is to serve as a repository of information relevant for grad students. We hope to maintain this page as a repository of current and relevant information for graduate students currently affiliated with the PSLC, as well as grad students who hope to be in the PSLC. <br />
<br />
== Announcements==<br />
<br />
1) PSLC grads are now responsible for keeping the [http://www.learnlab.org/research/wiki/index.php/PSLC_People#Graduate_Students List of PSLC Grads] up to date. <br />
<br />
* If you know of someone who should be added (or deleted) from this list please e-mail the webmaster at bef25@pitt.edu. Alternatively, feel free to go in and update the list yourself!<br />
<br />
2) Please e-mail Mary Lou Vercellotti ASAP if you are interested in attending the iSLC conference in Washington, D.C. on October 13-15. Up to three graduate students may attend.<br />
<br />
3) Ultimate Block Party in Central Park, NY.<br />
<br />
* Description: This is an outreach event for PSLC research. Faculty and graduate students are invited to attend to serve as "experts" as families visit the workshops in the park. (You will receive a brightly colored lab coat if you decide to help out.)<br />
<br />
* How to sign up: E-mail Michael Bett at mbett@cs.cmu.edu if you are interested.<br />
<br />
4) PSLC Graduate Student Meetings are scheduled for the following days and will begin at noon.<br />
<br />
* Monday, September 20 in 408 LRDC - topic: grad student wiki pages<br />
* Monday, October 18 at CMU (location tba) - topic what is the PSLC and why should you care<br />
* Monday, November 15 in 408 LRDC - topic ?<br />
* Monday, December 6 at CMU topic ?<br />
<br />
== Meeting Notes==<br />
<br />
== FAQs==<br />
<br />
'''1. What does it take to be a PSLC grad student?'''<br />
<br />
Well, there are basically three ways you can be considered a PSLC grad student.<br />
<br />
a. You work on a project that receives funding from the PSLC.<br />
<br />
b. Your advisor or collaborator receives funding from the PSLC and asks you to be involved.<br />
<br />
c. You want to be a PSLC grad student.<br />
<br />
<br />
'''2. What types of opportunities does the PSLC have for a grad student like me?''' <br />
<br />
There are a variety of different levels of involvement and types of activities that the PSLC offers. <br />
<br />
For the casual grad student, the PSLC organizes a speaker series with talks that may be of interest to students interested in the learning sciences. These are open to whomever wishes to go. There are also monthly lunch meetings where people associated with the PSLC can give a talk on their work. <br />
<br />
The grad student community also hopes to organize events catered toward grad students, with topics like applying for grants, finding jobs, collaboration with people at other universities, etc. These are also open to the public. <br />
<br />
For those who wish to get more involved, the grad student community also has monthly meetings to discuss center-wide issues, read and discuss articles we believe are relevant, plan future events, etc. Again, these are open to the public. <br />
<br />
Finally, each thrust has regular or semi-regular meetings to discuss the thrust's theoretical framework, set the research agenda, and discuss the progress of projects within that thrust. While these are open to anyone, they're probably of limited interest unless you currently have or have had a project affiliated with the thrust. <br />
<br />
<br />
<br />
'''3. What is expected of me as a PSLC grad student?'''<br />
<br />
If you receive funding from the PSLC, you are expected, to the extent it is possible, to attend the thrust meetings for your relevant thrust, and attend the monthly PSLC lunches. The grad student community also encourages you to come to the grad student monthly meetings, of course.<br />
<br />
If you don't receive funding from the PSLC, but still wish to be a part of the grad student community, your level of involvement is up to you. <br />
<br />
<br />
'''How do I find out about upcoming talks/meetings/events?'''<br />
<br />
One option is to check the Announcements section of this page. A possibly better option would be to get on our mailing list. To do that, e-mail Jo Bodnar at jobodnar AT cs.cmu.edu and ask to be put on the PSLC general mailing list and grad student mailing list. <br />
<br />
There is also a regularly updated calendar at our [http://www.learnlab.org main webpage] that is updated regularly and gives a fairly complete account of most PSLC events.<br />
<br />
<br />
<br />
4. '''I already consider myself a PSLC grad, and want to be included on this page! What do I have to do?'''<br />
<br />
Well the great thing about the wiki page is that anybody can update it whenever they want! So, if you have an account here, and you know how to edit tables, you can just log in and add yourself! <br />
<br />
The table formatting is a bit weird and hard to follow, so if you want to add yourself, the easiest thing to do is just copy this text:<br />
<br />
<pre><br />
|-<br />
| Name || University || Advisor || e-mail address || Bio || Personal Webpage || Link to PSLC project page [Project page URL Project page title]<br />
</pre><br />
<br />
and paste it into the appropriate place on the table. With your own information, of course. <br />
<br />
If you don't have an account already, you can easily request one (NOTE: I forget how to do it- I'll need to add that). Once you have an account, you can just click "Edit" above the table, and you can add yourself. <br />
<br />
<br />
<br />
5. '''But that's such a pain! Isn't there an easier way?!'''<br />
<br />
There sure is! If you don't want to make all that effort just to have your name and e-mail address on a page, just send your info (you could even put it in the format given above!) to our Wikimaster (yep, we made that word up!), Ben Friedline, at bef25 AT pitt.edu, and he'll put it on here.<br />
<br />
== Who are the PSLC grads? ==<br />
<br />
{| border=1 cellspacing="0" cellpadding="5" style="text-align: left;"<br />
|-<br />
! Grad Student Name<br />
! University/Department<br />
! Advisor<br />
! E-mail<br />
! Bio<br />
! Personal Webpage<br />
! PSLC Projects<br />
|-<br />
| Colleen Davy || Carnegie Mellon/Psychology || Brian MacWhinney || cdavy1@andrew.cmu.edu || I am interested in how adult second language learners develop fluent speaking skills in their second language. || N/A || [http://www.learnlab.org/research/wiki/index.php/Davy_%26_MacWhinney_-_Spanish_Sentence_Production Spanish Sentence Production]<br />
|-<br />
| Benjamin Friedline || University of Pittsburgh || Alan Juffs || bef25@pitt.edu || I am interested in how adult second language learners acquire morphology in a second language. || N/A || [http://www.learnlab.org/research/wiki/index.php/Juffs_-_Feature_Focus_in_Word_Learning Feature Focus in Word Learning]<br />
|-<br />
| Ruth Wylie || Carnegie Mellon, HCII || Ken Koedinger & Teruko Mitamura || rwylie@cs.cmu.edu || I'm interested in second language learning and self-explanation. || [http://ruthwylie.wordpress.com/ http://www.cs.cmu.edu/~rwylie] || [http://www.learnlab.org/research/wiki/index.php/Wylie_-_Intelligent_Writing_Tutor Self-Explanation and ESL]<br />
|-<br />
| Mary Lou Vercellotti || University of Pittsburgh || Dr. Nel de Jong || marylou.vercellotti@gmail.com || My research looks at complexity, accuracy, and fluency in the oral production of English as a second language. || N/A || [http://www.learnlab.org/research/wiki/index.php/Fostering_fluency_in_second_language_learning Refinement and Fluency]<br />
|-<br />
| Turadg Aleahmad || Carnegie Mellon, HCII || Ken Koedinger & John Zimmerman || turadg@cmu.edu || My research is in design methods for theory-driven educational technology. || [http://www.cs.cmu.edu/~taleahma] || <br />
|-<br />
| Nora Presson || Carnegie Mellon, Psychology || Brian MacWhinney || presson@cmu.edu || I am studying how practice conditions can improve learning of second language grammar, especially testing the effects of explicit instruction. || || [http://www.learnlab.org/research/wiki/index.php/Presson_%26_MacWhinney_-_Second_Language_Grammar Second Language Grammar Instruction]<br />
|-<br />
| Daniel Belenky || University of Pittsburgh || Timothy Nokes || dmb83@pitt.edu || I am interesting in issues of motivation and cognition. Specifically, I have been studying how achievement goals influence transfer. || N/A || [http://www.learnlab.org/research/wiki/index.php/Nokes_-_Dialectical_Interaction_and_Robust_Learning]<br />
|}<br />
<br />
== Science of Learning Relevant Courses ==<br />
The PIER program offers three courses -- see the [http://www.cmu.edu/pier PIER Web page]<br />
<br />
See also the courses taught be any of the PSLC faculty.<br />
<br />
(Please add the names of relevant courses and web pointers if possible!)<br />
<br />
<br />
<pre><br />
05832 / 05432 Cognitive Modeling & Intelligent Tutoring Systems<br />
3:00pm-4:20pm, Tuesdays and Thursdays, Fall 2010<br />
Room 3002, Newell-Simon Hall, Carnegie Mellon University<br />
9 units<br />
Dr. Vincent Aleven, aleven@cs.cmu.edu<br />
</pre><br />
<br />
Students in this course will learn about the Cognitive Tutor technology that has been demonstrated to dramatically enhance student learning in domains like math, science, and computer programming. This type of tutoring software is currently in use in 2,700 schools around the country and is used extensively as platform for learning sciences research. The technology is grounded in artificial intelligence, cognitive psychology, and cognitive task analysis. Students will learn data-driven and theoretical methods for analyzing human problem solving and will learn to use such data to inform the design of intelligent tutoring systems. Course projects will focus on the development of an intelligent tutor using CTAT, the Cognitive Tutor Authoring Tools (see http://ctat.pact.cs.cmu.edu). Some assignments will focus on creating cognitive models in the Jess production rule modeling language.<br />
<br />
Students should either have programming skills, or experience in the cognitive psychology of human problem solving, or HCI / design skills, or permission from the instructor.</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=PSLC_GradStudents&diff=11072PSLC GradStudents2010-09-28T15:14:34Z<p>Dmbelenk: </p>
<hr />
<div>The purpose of this page is to serve as a repository of information relevant for grad students. We hope to maintain this page as a repository of current and relevant information for graduate students currently affiliated with the PSLC, as well as grad students who hope to be in the PSLC. <br />
<br />
== Announcements==<br />
<br />
1) PSLC grads are now responsible for keeping the [http://www.learnlab.org/research/wiki/index.php/PSLC_People#Graduate_Students List of PSLC Grads] up to date. <br />
<br />
* If you know of someone who should be added (or deleted) from this list please e-mail the webmaster at bef25@pitt.edu. Alternatively, feel free to go in and update the list yourself!<br />
<br />
2) Please e-mail Mary Lou Vercellotti ASAP if you are interested in attending the iSLC conference in Washington, D.C. on October 13-15. Up to three graduate students may attend.<br />
<br />
3) Ultimate Block Party in Central Park, NY.<br />
<br />
* Description: This is an outreach event for PSLC research. Faculty and graduate students are invited to attend to serve as "experts" as families visit the workshops in the park. (You will receive a brightly colored lab coat if you decide to help out.)<br />
<br />
* How to sign up: E-mail Michael Bett at mbett@cs.cmu.edu if you are interested.<br />
<br />
4) PSLC Graduate Student Meetings are scheduled for the following days and will begin at noon.<br />
<br />
* Monday, September 20 in 408 LRDC - topic: grad student wiki pages<br />
* Monday, October 18 at CMU (location tba) - topic what is the PSLC and why should you care<br />
* Monday, November 15 in 408 LRDC - topic ?<br />
* Monday, December 6 at CMU topic ?<br />
<br />
== Meeting Notes==<br />
<br />
== FAQs==<br />
<br />
'''1. What does it take to be a PSLC grad student?'''<br />
<br />
Well, there are basically three ways you can be considered a PSLC grad student.<br />
<br />
a. You work on a project that receives funding from the PSLC.<br />
<br />
b. Your advisor or collaborator receives funding from the PSLC and asks you to be involved.<br />
<br />
c. You want to be a PSLC grad student.<br />
<br />
<br />
'''2. What types of opportunities does the PSLC have for a grad student like me?''' <br />
<br />
There are a variety of different levels of involvement and types of activities that the PSLC offers. <br />
<br />
For the casual grad student, the PSLC organizes a speaker series with talks that may be of interest to students interested in the learning sciences. These are open to whomever wishes to go. There are also monthly lunch meetings where people associated with the PSLC can give a talk on their work. <br />
<br />
The grad student community also hopes to organize events catered toward grad students, with topics like applying for grants, finding jobs, collaboration with people at other universities, etc. These are also open to the public. <br />
<br />
For those who wish to get more involved, the grad student community also has monthly meetings to discuss center-wide issues, read and discuss articles we believe are relevant, plan future events, etc. Again, these are open to the public. <br />
<br />
Finally, each thrust has regular or semi-regular meetings to discuss the thrust's theoretical framework, set the research agenda, and discuss the progress of projects within that thrust. While these are open to anyone, they're probably of limited interest unless you currently have or have had a project affiliated with the thrust. <br />
<br />
<br />
<br />
'''3. What is expected of me as a PSLC grad student?'''<br />
<br />
If you receive funding from the PSLC, you are expected, to the extent it is possible, to attend the thrust meetings for your relevant thrust, and attend the monthly PSLC lunches. The grad student community also encourages you to come to the grad student monthly meetings, of course.<br />
<br />
If you don't receive funding from the PSLC, but still wish to be a part of the grad student community, your level of involvement is up to you. <br />
<br />
<br />
'''How do I find out about upcoming talks/meetings/events?'''<br />
<br />
One option is to check the Announcements section of this page. A possibly better option would be to get on our mailing list. To do that, e-mail Jo Bodnar at jobodnar AT cs.cmu.edu and ask to be put on the PSLC general mailing list and grad student mailing list. <br />
<br />
There is also a regularly updated calendar at our [http://www.learnlab.org main webpage] that is updated regularly and gives a fairly complete account of most PSLC events.<br />
<br />
<br />
<br />
4. '''I already consider myself a PSLC grad, and want to be included on this page! What do I have to do?'''<br />
<br />
Well the great thing about the wiki page is that anybody can update it whenever they want! So, if you have an account here, and you know how to edit tables, you can just log in and add yourself! <br />
<br />
The table formatting is a bit weird and hard to follow, so if you want to add yourself, the easiest thing to do is just copy this text:<br />
<br />
<pre><br />
|-<br />
| Name || University || Advisor || e-mail address || Bio || Personal Webpage || Link to PSLC project page [Project page URL Project page title]<br />
</pre><br />
<br />
and paste it into the appropriate place on the table. With your own information, of course. <br />
<br />
If you don't have an account already, you can easily request one (NOTE: I forget how to do it- I'll need to add that). Once you have an account, you can just click "Edit" above the table, and you can add yourself. <br />
<br />
<br />
<br />
5. '''But that's such a pain! Isn't there an easier way?!'''<br />
<br />
There sure is! If you don't want to make all that effort just to have your name and e-mail address on a page, just send your info (you could even put it in the format given above!) to our Wikimaster (yep, we made that word up!), Ben Friedline, at bef25 AT pitt.edu, and he'll put it on here.<br />
<br />
== Who are the PSLC grads? ==<br />
<br />
{| border=1 cellspacing="0" cellpadding="5" style="text-align: left;"<br />
|-<br />
! Grad Student Name<br />
! University/Department<br />
! Advisor<br />
! E-mail<br />
! Bio<br />
! Personal Webpage<br />
! PSLC Projects<br />
|-<br />
| Colleen Davy || Carnegie Mellon/Psychology || Brian MacWhinney || cdavy1@andrew.cmu.edu || I am interested in how adult second language learners develop fluent speaking skills in their second language. || N/A || [http://www.learnlab.org/research/wiki/index.php/Davy_%26_MacWhinney_-_Spanish_Sentence_Production Spanish Sentence Production]<br />
|-<br />
| Benjamin Friedline || University of Pittsburgh || Alan Juffs || bef25@pitt.edu || I am interested in how adult second language learners acquire morphology in a second language. || N/A || [http://www.learnlab.org/research/wiki/index.php/Juffs_-_Feature_Focus_in_Word_Learning Feature Focus in Word Learning]<br />
|-<br />
| Ruth Wylie || Carnegie Mellon, HCII || Ken Koedinger & Teruko Mitamura || rwylie@cs.cmu.edu || I'm interested in second language learning and self-explanation. || [http://ruthwylie.wordpress.com/ http://www.cs.cmu.edu/~rwylie] || [http://www.learnlab.org/research/wiki/index.php/Wylie_-_Intelligent_Writing_Tutor Self-Explanation and ESL]<br />
|-<br />
| Mary Lou Vercellotti || University of Pittsburgh || Dr. Nel de Jong || marylou.vercellotti@gmail.com || My research looks at complexity, accuracy, and fluency in the oral production of English as a second language. || N/A || [http://www.learnlab.org/research/wiki/index.php/Fostering_fluency_in_second_language_learning Refinement and Fluency]<br />
|-<br />
| Turadg Aleahmad || Carnegie Mellon, HCII || Ken Koedinger & John Zimmerman || turadg@cmu.edu || My research is in design methods for theory-driven educational technology. || [http://www.cs.cmu.edu/~taleahma] || <br />
|-<br />
| Nora Presson || Carnegie Mellon, Psychology || Brian MacWhinney || presson@cmu.edu || I am studying how practice conditions can improve learning of second language grammar, especially testing the effects of explicit instruction. || || [http://www.learnlab.org/research/wiki/index.php/Presson_%26_MacWhinney_-_Second_Language_Grammar Second Language Grammar Instruction]<br />
|-<br />
| Daniel Belenky || University of Pittsburgh || Timothy Nokes || dmb83@pitt.edu || I am interesting in issues of motivation and cognition. Specifically, I have been studying how achievement goals influence transfer. || || http://www.learnlab.org/research/wiki/index.php/Nokes_-_Dialectical_Interaction_and_Robust_Learning]<br />
|}<br />
<br />
== Science of Learning Relevant Courses ==<br />
The PIER program offers three courses -- see the [http://www.cmu.edu/pier PIER Web page]<br />
<br />
See also the courses taught be any of the PSLC faculty.<br />
<br />
(Please add the names of relevant courses and web pointers if possible!)<br />
<br />
<br />
<pre><br />
05832 / 05432 Cognitive Modeling & Intelligent Tutoring Systems<br />
3:00pm-4:20pm, Tuesdays and Thursdays, Fall 2010<br />
Room 3002, Newell-Simon Hall, Carnegie Mellon University<br />
9 units<br />
Dr. Vincent Aleven, aleven@cs.cmu.edu<br />
</pre><br />
<br />
Students in this course will learn about the Cognitive Tutor technology that has been demonstrated to dramatically enhance student learning in domains like math, science, and computer programming. This type of tutoring software is currently in use in 2,700 schools around the country and is used extensively as platform for learning sciences research. The technology is grounded in artificial intelligence, cognitive psychology, and cognitive task analysis. Students will learn data-driven and theoretical methods for analyzing human problem solving and will learn to use such data to inform the design of intelligent tutoring systems. Course projects will focus on the development of an intelligent tutor using CTAT, the Cognitive Tutor Authoring Tools (see http://ctat.pact.cs.cmu.edu). Some assignments will focus on creating cognitive models in the Jess production rule modeling language.<br />
<br />
Students should either have programming skills, or experience in the cognitive psychology of human problem solving, or HCI / design skills, or permission from the instructor.</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=File:Strategy_Items_(MSLQ_and_others).pdf&diff=10667File:Strategy Items (MSLQ and others).pdf2010-03-14T23:53:40Z<p>Dmbelenk: Strategy Items (from Motivated Strategies for Learning Questionnaire, and from Nokes' classroom studies).</p>
<hr />
<div>Strategy Items (from Motivated Strategies for Learning Questionnaire, and from Nokes' classroom studies).</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=File:Catch_and_Hold_Interest.pdf&diff=10666File:Catch and Hold Interest.pdf2010-03-14T23:52:56Z<p>Dmbelenk: Interest Questionnaire (3 time points) (From Harackiewicz et al., 2008).</p>
<hr />
<div>Interest Questionnaire (3 time points) (From Harackiewicz et al., 2008).</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=File:Activitybased_achievement_goals_and_affect.pdf&diff=10665File:Activitybased achievement goals and affect.pdf2010-03-14T23:52:07Z<p>Dmbelenk: Achievement Goal-related behaviors and affects in an activity (from Belenky & Nokes, 2009).</p>
<hr />
<div>Achievement Goal-related behaviors and affects in an activity (from Belenky & Nokes, 2009).</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=File:Achievement_Goal_Questionnaire.pdf&diff=10664File:Achievement Goal Questionnaire.pdf2010-03-14T23:51:27Z<p>Dmbelenk: Achievement Goal Questionnaire-Revised (From Elliot & Murayama, 2008)</p>
<hr />
<div>Achievement Goal Questionnaire-Revised (From Elliot & Murayama, 2008)</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=File:Theories_of_Intelligence.pdf&diff=10640File:Theories of Intelligence.pdf2010-03-03T21:05:22Z<p>Dmbelenk: Dweck's Theories of Intelligence Scale</p>
<hr />
<div>Dweck's Theories of Intelligence Scale</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Nokes_-_Questionnaires&diff=10379Nokes - Questionnaires2009-12-11T17:56:37Z<p>Dmbelenk: </p>
<hr />
<div>==Summary Table==<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" style="text-align: left;"<br />
| '''PIs''' || Timothy Nokes, Vincent Aleven<br />
|-<br />
| '''Other Contributers''' || Daniel Belenky<br />
|-<br />
| '''Study Start Date''' || <br />
|-<br />
| '''Study End Date''' || <br />
|-<br />
| '''Site''' ||<br />
|-<br />
| '''Number of Students''' || <br />
|-<br />
| '''Total Participant Hours''' || <br />
|-<br />
| '''DataShop''' || <br />
|}<br />
<br><br />
<br />
==Abstract==<br />
We will develop infrastructure to collect variables related to [[metacognition]], affect, and motivation across all LearnLabs. The planned LearnLab instrumentation involves two innovations in measurement: We will use microgenetic approaches for the fine-grained sampling of constructs vis-à-vis 1) the repeated administering of brief questionnaire items and less frequent longitudinal sampling using longer questionnaires, and 2) moment-by-moment behavioral data, including automatic monitoring in learning software. Our unique strength in these areas will be the ability to combine rich layers of behavioral measures (cognition, metacognition, affect, motivation), which will be used to create online models that can predict moment-by-moment changes. In doing so, we will leverage DataShop capabilities; the DataShop has been designed explicitly to accommodate multiple interpretations of student interaction data, if necessary at different grain sizes.<br />
<br />
This project will enable us to collect data on metacognitive, motivational and affective states in naturalistic learning settings at an unprecedented level of fine-grained detail (both temporal as well as type, multiple simultaneous measures). This level of detail will enable the PSLC learning scientists and learning scientists at large (through the DataShop) to test novel questions and theoretical models of the relation between M&M behaviors and states and robust learning that have been previously unable to be tested. Furthermore, this project will enable us to test the generalizability of current theoretical models in the literature (e.g., Blackwell, Trzesniewski, & Dweck, 2007).<br />
<br />
==Plans to Assess the Relationship Between Motivation and Affect on Robust Learning==<br />
e will collect questionnaire data for a range of variables. This effort will have two components. First, we will take a microgenetic approach to collect questionnaire data with a small number of items that are administered frequently (i.e., dense data collection over a range of time periods, providing motivational / affective tracking from minutes to hours to weeks). These questionnaires will be embedded in the learning software and therefore can be administered between problems, or at beginning or end of session (and perhaps, subject to these constraints, randomly). This method of data collection will be applied to affective or motivational variables that are expected to vary more rapidly (e.g., interest, strategies, goal orientation towards the task, attitudes towards the learning materials). This approach will provide very fine-grained data as to how motivation and affective states change based on changes in the learning environment or task structure (e.g., difficulty, problem type, topic, domain, etc.), as well as student interaction with the tutor or peers (e.g., strategies, cognitive processing, etc.).<br />
<br />
Second, twice or three times a year we will administer questionnaires focused on constructs that may be semi-stable over time (e.g., self-efficacy, attitudes towards the domain, theory of intelligence, goal orientation towards the domain), a very traditional method in motivational research or research in SRL, although one whose shortcoming are increasingly being noticed (Zimmerman, 2008). Key to the current approach is that this more traditional type of data can be related to fine-grained data on PSLC measures of robust learning (instead of only using grades as a measure of learning which is typically the measure used in the literature in naturalistic learning settings). These questionnaires will be administered on paper, or perhaps electronically using SurveyMonkey or CTAT.<br />
<br />
The data from these two approaches will enable the [[Metacognition_and_Motivation | Metacogniton and Motivation]] thrust to test path and structural equation models of the relation of particular M&M states and behaviors to robust learning (see Blackwell, Trzesniewski, and Dweck, 2007 for an example). Critically we will be linking motivational and affect variables to cognitive processes (by which they are hypothesized to do their work) and robust learning outcome measures. One goal of this work is theoretical integration of past work at the PSLC on instructional principles (macro-level), cognitive processes / knowledge components (mirco-level) and measures of robust learning to research / work and results on motivation and affect. Furthermore, this project provides a unique opportunity to test the generalizability of current and new theories of learning and motivation and affect across a number of academic domains (LearnLabs). This project will also play a critical role in the Theoretical Integration project of the thrust described in section 1.3.<br />
<br />
These measures will be used in the experiments designed in the Social Communicative and Cognitive Factors Thrusts to provide across thrust integration. In addition, the collected data will be used to build and validate automated detectors for important aspects of students’ metacognition (described in the next section).<br />
<br />
Our strategy will be initially to focus on a small set of variables that both builds on prior work conducted at the PSLC and the literature has identified as particularly relevant for learning in academic contexts.<br />
<br />
*Awareness and use of SRL strategies (e.g., Motivated Strategies for Learning Questionnaire or its descendants) (Pintrich & de Groot, 1990)<br />
*Self-efficacy (Bandura , 1997)<br />
*Theory of intelligence (entity, incremental) (Dweck, 2006)<br />
*Achievement goals (performance-approach, performance-avoidance, learning) (Darnon, Butera, & Harackiewicz, 2007; Elliot & Dweck, 1988)<br />
*Interest (Hidi & Renninger, 2006)<br />
==Results==<br />
Forthcoming<br />
==Explanation==<br />
Forthcoming<br />
===Future Plans===<br />
===References===</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Nokes_-_Questionnaires&diff=10378Nokes - Questionnaires2009-12-11T17:55:40Z<p>Dmbelenk: </p>
<hr />
<div>==Summary Table==<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" style="text-align: left;"<br />
| '''PIs''' || Timothy Nokes, Vincent Aleven<br />
|-<br />
| '''Other Contributers''' || Daniel Belenky<br />
|-<br />
| '''Study Start Date''' || <br />
|-<br />
| '''Study End Date''' || <br />
|-<br />
| '''Site''' ||<br />
|-<br />
| '''Number of Students''' || <br />
|-<br />
| '''Total Participant Hours''' || <br />
|-<br />
| '''DataShop''' || <br />
|}<br />
<br><br />
<br />
==Abstract==<br />
We will develop infrastructure to collect variables related to metacognition, affect, and motivation across all LearnLabs. The planned LearnLab instrumentation involves two innovations in measurement: We will use microgenetic approaches for the fine-grained sampling of constructs vis-à-vis 1) the repeated administering of brief questionnaire items and less frequent longitudinal sampling using longer questionnaires, and 2) moment-by-moment behavioral data, including automatic monitoring in learning software. Our unique strength in these areas will be the ability to combine rich layers of behavioral measures (cognition, metacognition, affect, motivation), which will be used to create online models that can predict moment-by-moment changes. In doing so, we will leverage DataShop capabilities; the DataShop has been designed explicitly to accommodate multiple interpretations of student interaction data, if necessary at different grain sizes.<br />
<br />
This project will enable us to collect data on metacognitive, motivational and affective states in naturalistic learning settings at an unprecedented level of fine-grained detail (both temporal as well as type, multiple simultaneous measures). This level of detail will enable the PSLC learning scientists and learning scientists at large (through the DataShop) to test novel questions and theoretical models of the relation between M&M behaviors and states and robust learning that have been previously unable to be tested. Furthermore, this project will enable us to test the generalizability of current theoretical models in the literature (e.g., Blackwell, Trzesniewski, & Dweck, 2007).<br />
<br />
==Plans to Assess the Relationship Between Motivation and Affect on Robust Learning==<br />
e will collect questionnaire data for a range of variables. This effort will have two components. First, we will take a microgenetic approach to collect questionnaire data with a small number of items that are administered frequently (i.e., dense data collection over a range of time periods, providing motivational / affective tracking from minutes to hours to weeks). These questionnaires will be embedded in the learning software and therefore can be administered between problems, or at beginning or end of session (and perhaps, subject to these constraints, randomly). This method of data collection will be applied to affective or motivational variables that are expected to vary more rapidly (e.g., interest, strategies, goal orientation towards the task, attitudes towards the learning materials). This approach will provide very fine-grained data as to how motivation and affective states change based on changes in the learning environment or task structure (e.g., difficulty, problem type, topic, domain, etc.), as well as student interaction with the tutor or peers (e.g., strategies, cognitive processing, etc.).<br />
<br />
Second, twice or three times a year we will administer questionnaires focused on constructs that may be semi-stable over time (e.g., self-efficacy, attitudes towards the domain, theory of intelligence, goal orientation towards the domain), a very traditional method in motivational research or research in SRL, although one whose shortcoming are increasingly being noticed (Zimmerman, 2008). Key to the current approach is that this more traditional type of data can be related to fine-grained data on PSLC measures of robust learning (instead of only using grades as a measure of learning which is typically the measure used in the literature in naturalistic learning settings). These questionnaires will be administered on paper, or perhaps electronically using SurveyMonkey or CTAT.<br />
<br />
The data from these two approaches will enable the [[Metacognition_and_Motivation | Metacogniton and Motivation]] thrust to test path and structural equation models of the relation of particular M&M states and behaviors to robust learning (see Blackwell, Trzesniewski, and Dweck, 2007 for an example). Critically we will be linking motivational and affect variables to cognitive processes (by which they are hypothesized to do their work) and robust learning outcome measures. One goal of this work is theoretical integration of past work at the PSLC on instructional principles (macro-level), cognitive processes / knowledge components (mirco-level) and measures of robust learning to research / work and results on motivation and affect. Furthermore, this project provides a unique opportunity to test the generalizability of current and new theories of learning and motivation and affect across a number of academic domains (LearnLabs). This project will also play a critical role in the Theoretical Integration project of the thrust described in section 1.3.<br />
<br />
These measures will be used in the experiments designed in the Social Communicative and Cognitive Factors Thrusts to provide across thrust integration. In addition, the collected data will be used to build and validate automated detectors for important aspects of students’ metacognition (described in the next section).<br />
<br />
Our strategy will be initially to focus on a small set of variables that both builds on prior work conducted at the PSLC and the literature has identified as particularly relevant for learning in academic contexts.<br />
<br />
*Awareness and use of SRL strategies (e.g., Motivated Strategies for Learning Questionnaire or its descendants) (Pintrich & de Groot, 1990)<br />
*Self-efficacy (Bandura , 1997)<br />
*Theory of intelligence (entity, incremental) (Dweck, 2006)<br />
*Achievement goals (performance-approach, performance-avoidance, learning) (Darnon, Butera, & Harackiewicz, 2007; Elliot & Dweck, 1988)<br />
*Interest (Hidi & Renninger, 2006)<br />
==Results==<br />
Forthcoming<br />
==Explanation==<br />
Forthcoming<br />
===Future Plans===<br />
===References===</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Nokes_-_Questionnaires&diff=10377Nokes - Questionnaires2009-12-11T02:32:19Z<p>Dmbelenk: New page: ==Summary Table== {| border="1" cellspacing="0" cellpadding="5" style="text-align: left;" | '''PIs''' || Timothy Nokes, Vincent Aleven |- | '''Other Contributers''' || Daniel Belenky |- ...</p>
<hr />
<div>==Summary Table==<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" style="text-align: left;"<br />
| '''PIs''' || Timothy Nokes, Vincent Aleven<br />
|-<br />
| '''Other Contributers''' || Daniel Belenky<br />
|-<br />
| '''Study Start Date''' || <br />
|-<br />
| '''Study End Date''' || <br />
|-<br />
| '''Site''' ||<br />
|-<br />
| '''Number of Students''' || <br />
|-<br />
| '''Total Participant Hours''' || <br />
|-<br />
| '''DataShop''' || <br />
|}<br />
<br><br />
<br />
==Abstract==<br />
We will develop infrastructure to collect variables related to metacognition, affect, and motivation across all LearnLabs. The planned LearnLab instrumentation involves two innovations in measurement: We will use microgenetic approaches for the fine-grained sampling of constructs vis-à-vis 1) the repeated administering of brief questionnaire items and less frequent longitudinal sampling using longer questionnaires, and 2) moment-by-moment behavioral data, including automatic monitoring in learning software. Our unique strength in these areas will be the ability to combine rich layers of behavioral measures (cognition, metacognition, affect, motivation), which will be used to create online models that can predict moment-by-moment changes. In doing so, we will leverage DataShop capabilities; the DataShop has been designed explicitly to accommodate multiple interpretations of student interaction data, if necessary at different grain sizes.<br />
<br />
This project will enable us to collect data on metacognitive, motivational and affective states in naturalistic learning settings at an unprecedented level of fine-grained detail (both temporal as well as type, multiple simultaneous measures). This level of detail will enable the PSLC learning scientists and learning scientists at large (through the DataShop) to test novel questions and theoretical models of the relation between M&M behaviors and states and robust learning that have been previously unable to be tested. Furthermore, this project will enable us to test the generalizability of current theoretical models in the literature (e.g., Blackwell, Trzesniewski, & Dweck, 2007).<br />
<br />
==Plans to Assess the Relationship Between Motivation and Affect on Robust Learning==<br />
e will collect questionnaire data for a range of variables. This effort will have two components. First, we will take a microgenetic approach to collect questionnaire data with a small number of items that are administered frequently (i.e., dense data collection over a range of time periods, providing motivational / affective tracking from minutes to hours to weeks). These questionnaires will be embedded in the learning software and therefore can be administered between problems, or at beginning or end of session (and perhaps, subject to these constraints, randomly). This method of data collection will be applied to affective or motivational variables that are expected to vary more rapidly (e.g., interest, strategies, goal orientation towards the task, attitudes towards the learning materials). This approach will provide very fine-grained data as to how motivation and affective states change based on changes in the learning environment or task structure (e.g., difficulty, problem type, topic, domain, etc.), as well as student interaction with the tutor or peers (e.g., strategies, cognitive processing, etc.).<br />
<br />
Second, twice or three times a year we will administer questionnaires focused on constructs that may be semi-stable over time (e.g., self-efficacy, attitudes towards the domain, theory of intelligence, goal orientation towards the domain), a very traditional method in motivational research or research in SRL, although one whose shortcoming are increasingly being noticed (Zimmerman, 2008). Key to the current approach is that this more traditional type of data can be related to fine-grained data on PSLC measures of robust learning (instead of only using grades as a measure of learning which is typically the measure used in the literature in naturalistic learning settings). These questionnaires will be administered on paper, or perhaps electronically using SurveyMonkey or CTAT.<br />
<br />
The data from these two approaches will enable the M&M Thrust to test path and structural equation models of the relation of particular M&M states and behaviors to robust learning (see Blackwell, Trzesniewski, and Dweck, 2007 for an example). Critically we will be linking motivational and affect variables to cognitive processes (by which they are hypothesized to do their work) and robust learning outcome measures. One goal of this work is theoretical integration of past work at the PSLC on instructional principles (macro-level), cognitive processes / knowledge components (mirco-level) and measures of robust learning to research / work and results on motivation and affect. Furthermore, this project provides a unique opportunity to test the generalizability of current and new theories of learning and motivation and affect across a number of academic domains (LearnLabs). This project will also play a critical role in the Theoretical Integration project of the thrust described in section 1.3.<br />
<br />
These measures will be used in the experiments designed in the Social Communicative and Cognitive Factors Thrusts to provide across thrust integration. In addition, the collected data will be used to build and validate automated detectors for important aspects of students’ metacognition (described in the next section).<br />
<br />
Our strategy will be initially to focus on a small set of variables that both builds on prior work conducted at the PSLC and the literature has identified as particularly relevant for learning in academic contexts.<br />
<br />
*Awareness and use of SRL strategies (e.g., Motivated Strategies for Learning Questionnaire or its descendants) (Pintrich & de Groot, 1990)<br />
*Self-efficacy (Bandura , 1997)<br />
*Theory of intelligence (entity, incremental) (Dweck, 2006)<br />
*Achievement goals (performance-approach, performance-avoidance, learning) (Darnon, Butera, & Harackiewicz, 2007; Elliot & Dweck, 1988)<br />
*Interest (Hidi & Renninger, 2006)<br />
==Results==<br />
Forthcoming<br />
==Explanation==<br />
Forthcoming<br />
===Future Plans===<br />
===References===</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Nokes_-_Dialectical_Interaction_and_Robust_Learning&diff=10339Nokes - Dialectical Interaction and Robust Learning2009-12-05T22:13:02Z<p>Dmbelenk: </p>
<hr />
<div>Dialectical Interaction and Robust Learning<br />
==Summary Table==<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" style="text-align: left;"<br />
| '''PIs''' || Timothy Nokes, John Levine<br />
|-<br />
| '''Other Contributers''' || Daniel Belenky, Soniya Gadgil<br />
|-<br />
| '''Study Start Date''' || <br />
|-<br />
| '''Study End Date''' || <br />
|-<br />
| '''Site''' || University of Pittsburgh <br />
|-<br />
| '''Number of Students''' || <br />
|-<br />
| '''Total Participant Hours''' || <br />
|-<br />
| '''DataShop''' || <br />
|}<br />
<br><br />
<br />
==Abstract==<br />
This work builds on prior research investigating the relationship between cognitive conflict<br />
and learning (e.g., Doise & Mugny, 1984), the links between motivation, affect, and cognition (e.g.,<br />
Forgas, 2001; Schwarz & Clore, 2007), and the mechanisms underlying conceptual learning (e.g., Chi<br />
& Ohlsson, 2005; Nokes & Ross, 2007). Although much prior work has investigated each of these<br />
areas separately, few studies have tried to build connections across all three. We hypothesize that<br />
conflict scenarios that increase engagement, arousal, and positive affect will facilitate participants’<br />
deep processing of discourse through a variety of cognitive mechanisms including inference<br />
generation, elaboration, analogy, and the framing and re-framing of the information discussed.<br />
Participants in such scenarios are expected to develop more complex and coherent knowledge of the<br />
issue and to learn both their own and their opponent’s side of the issue. In contrast, conflict scenarios<br />
that decrease engagement, arousal, and induce negative affect should lead to less robust learning.<br />
Participants in these scenarios are expected to focus on their own side of the debate, ignoring their<br />
opponent’s view, and to engage in shallow cognitive processing strategies such as rehearsal of their<br />
own argument.<br />
==Background & Significance==<br />
==Glossary==<br />
==Research questions==<br />
How do students learn when engaged in a debate? Do they integrate their own viewpoint with that of their opponent, or focus only on their own side? Does the format of the debate affect this? Also, what motivational and affective factors play into this? How do student goals (like performance or mastery goals) influence what information gets processed? Do different affective experiences lead to different patterns of learning?<br />
==Independent Variables==<br />
Our first study has a 2 x 2 design. <br> Factor 1: Debate Format - Alternating Turns (1 minute each) or Free-Form <br> Factor 2: Debate Criterion - Substance or Rhetoric<br />
<br />
==Dependent Variables==<br />
Our dependent variables will consist of various measures of learning, gathered after the debate. These measures include a multiple-choice test, as well as an essay. Both of these will be evaluated in terms of how well a student has learned his side of the debate, as well as how well he has learned the other side, and how well he has integrated the two.<br />
<br />
We will also gather measures of affect during the debate. This will be used as a dependent variable to see if our manipulations relating to the debate structure influence the affective reactions experienced. We will also be able to affective response as a predictor of learning, or as mediating variable between debate and learning. These affective measures will come from analysis of the vocal parameters of speech of each participant, as well as by analysis of facial cues.<br />
==Hypothesis==<br />
We predict that focusing the debate on the substance of the arguments will produce a more coherent representation of both sides of the argument. We also predict that the free-form debate will lead to better learning of both sides, as the participants must be engaging with what a participant is saying more actively, and respond more immediately and thoroughly than when they have a minute between speaking turns.<br />
<br />
In terms of affect, we expect that positive affective reactions to cognitive conflict will produce systematic processing of an opponent’s arguments, which in turn will facilitate learning these arguments and developing a more complex cognitive representation of the discussion topic. In contrast, negative affective reactions will produce superficial processing of the opponent’s arguments coupled with rehearsal of one’s own arguments. When negative affect is mild, interactants are unlikely to learn the opponent’s arguments or to develop a complex representation of the topic. Moreover, when negative affect is strong, interactants may actually show cognitive regression -- less complex representations of the topic after interaction than before.<br />
<br />
==Results==<br />
Forthcoming<br />
==Explanation==<br />
Forthcoming<br />
===Future Plans===<br />
===References===</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Nokes_-_Dialectical_Interaction_and_Robust_Learning&diff=10335Nokes - Dialectical Interaction and Robust Learning2009-12-05T22:09:47Z<p>Dmbelenk: </p>
<hr />
<div>Dialectical Interaction and Robust Learning<br />
==Summary Table==<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" style="text-align: left;"<br />
| '''PIs''' || Timothy Nokes, John Levine<br />
|-<br />
| '''Other Contributers''' || Daniel Belenky, Soniya Gadgil<br />
|-<br />
| '''Study Start Date''' || Sep. 1, 2009<br />
|-<br />
| '''Study End Date''' || May. 31, 2010<br />
|-<br />
| '''Site''' || University of Pittsburgh <br />
|-<br />
| '''Number of Students''' || ''N'' = ~180<br />
|-<br />
| '''Total Participant Hours''' || ~360.<br />
|-<br />
| '''DataShop''' || no data yet<br />
|}<br />
<br><br />
<br />
==Abstract==<br />
This work builds on prior research investigating the relationship between cognitive conflict<br />
and learning (e.g., Doise & Mugny, 1984), the links between motivation, affect, and cognition (e.g.,<br />
Forgas, 2001; Schwarz & Clore, 2007), and the mechanisms underlying conceptual learning (e.g., Chi<br />
& Ohlsson, 2005; Nokes & Ross, 2007). Although much prior work has investigated each of these<br />
areas separately, few studies have tried to build connections across all three. We hypothesize that<br />
conflict scenarios that increase engagement, arousal, and positive affect will facilitate participants’<br />
deep processing of discourse through a variety of cognitive mechanisms including inference<br />
generation, elaboration, analogy, and the framing and re-framing of the information discussed.<br />
Participants in such scenarios are expected to develop more complex and coherent knowledge of the<br />
issue and to learn both their own and their opponent’s side of the issue. In contrast, conflict scenarios<br />
that decrease engagement, arousal, and induce negative affect should lead to less robust learning.<br />
Participants in these scenarios are expected to focus on their own side of the debate, ignoring their<br />
opponent’s view, and to engage in shallow cognitive processing strategies such as rehearsal of their<br />
own argument.<br />
==Background & Significance==<br />
==Glossary==<br />
==Research questions==<br />
How do students learn when engaged in a debate? Do they integrate their own viewpoint with that of their opponent, or focus only on their own side? Does the format of the debate affect this? Also, what motivational and affective factors play into this? How do student goals (like performance or mastery goals) influence what information gets processed? Do different affective experiences lead to different patterns of learning?<br />
==Independent Variables==<br />
Our first study has a 2 x 2 design. <br> Factor 1: Debate Format - Alternating Turns (1 minute each) or Free-Form <br> Factor 2: Debate Criterion - Substance or Rhetoric<br />
<br />
==Dependent Variables==<br />
Our dependent variables will consist of various measures of learning, gathered after the debate. These measures include a multiple-choice test, as well as an essay. Both of these will be evaluated in terms of how well a student has learned his side of the debate, as well as how well he has learned the other side, and how well he has integrated the two.<br />
<br />
We will also gather measures of affect during the debate. This will be used as a dependent variable to see if our manipulations relating to the debate structure influence the affective reactions experienced. We will also be able to affective response as a predictor of learning, or as mediating variable between debate and learning. These affective measures will come from analysis of the vocal parameters of speech of each participant, as well as by analysis of facial cues.<br />
==Hypothesis==<br />
We predict that focusing the debate on the substance of the arguments will produce a more coherent representation of both sides of the argument. We also predict that the free-form debate will lead to better learning of both sides, as the participants must be engaging with what a participant is saying more actively, and respond more immediately and thoroughly than when they have a minute between speaking turns.<br />
<br />
In terms of affect, we expect that positive affective reactions to cognitive conflict will produce systematic processing of an opponent’s arguments, which in turn will facilitate learning these arguments and developing a more complex cognitive representation of the discussion topic. In contrast, negative affective reactions will produce superficial processing of the opponent’s arguments coupled with rehearsal of one’s own arguments. When negative affect is mild, interactants are unlikely to learn the opponent’s arguments or to develop a complex representation of the topic. Moreover, when negative affect is strong, interactants may actually show cognitive regression -- less complex representations of the topic after interaction than before.<br />
<br />
==Results==<br />
==Explanation==<br />
==Further Information==<br />
===Connections to Other Studies===<br />
===Annotated Bibliography===<br />
===References===<br />
===Future Plans===</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Nokes_-_Dialectical_Interaction_and_Robust_Learning&diff=10331Nokes - Dialectical Interaction and Robust Learning2009-12-05T21:58:14Z<p>Dmbelenk: </p>
<hr />
<div>Dialectical Interaction and Robust Learning<br />
==Summary Table==<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" style="text-align: left;"<br />
| '''PIs''' || Timothy Nokes, John Levine<br />
|-<br />
| '''Other Contributers''' || Daniel Belenky, Soniya Gadgil<br />
|-<br />
| '''Study Start Date''' || Sep. 1, 2009<br />
|-<br />
| '''Study End Date''' || May. 31, 2010<br />
|-<br />
| '''Site''' || University of Pittsburgh <br />
|-<br />
| '''Number of Students''' || ''N'' = ~180<br />
|-<br />
| '''Total Participant Hours''' || ~360.<br />
|-<br />
| '''DataShop''' || no data yet<br />
|}<br />
<br><br />
<br />
==Abstract==<br />
==Background & Significance==<br />
This work, which lies at the intersection of motivation, affect, social interaction and conceptual learning, studies the role of affect in a learning situation in which it is hypothesized to play a particularly prominent role. We focus on dialectical interaction, in which two or more people with roughly equal status but alternative viewpoints work together to solve a problem, perform a task, or reach agreement on an issue. The term “alternative viewpoints” is used broadly to include different stances on a controversial issue and different strategies for solving a problem. We assume that dialectical interaction affects participants’ cognitive activity in large part through its impact on their motivational states / goals and affective responses during discussion.<br />
==Glossary==<br />
==Research questions==<br />
How do students learn when engaged in a debate? Do they integrate their own viewpoint with that of their opponent, or focus only on their own side? Does the format of the debate affect this? Also, what motivational and affective factors play into this? How do student goals (like performance or mastery goals) influence what information gets processed? Do different affective experiences lead to different patterns of learning?<br />
==Independent Variables==<br />
Our first study has a 2 x 2 design. <br> Factor 1: Debate Format - Alternating Turns (1 minute each) or Free-Form <br> Factor 2: Debate Criterion - Substance or Rhetoric<br />
<br />
==Dependent Variables==<br />
Our dependent variables will consist of various measures of learning, gathered after the debate. These measures include a multiple-choice test, as well as an essay. Both of these will be evaluated in terms of how well a student has learned his side of the debate, as well as how well he has learned the other side, and how well he has integrated the two.<br />
<br />
We will also gather measures of affect during the debate. This will be used as a dependent variable to see if our manipulations relating to the debate structure influence the affective reactions experienced. We will also be able to affective response as a predictor of learning, or as mediating variable between debate and learning. These affective measures will come from analysis of the vocal parameters of speech of each participant, as well as by analysis of facial cues.<br />
==Hypothesis==<br />
We predict that focusing the debate on the substance of the arguments will produce a more coherent representation of both sides of the argument. We also predict that the free-form debate will lead to better learning of both sides, as the participants must be engaging with what a participant is saying more actively, and respond more immediately and thoroughly than when they have a minute between speaking turns.<br />
<br />
In terms of affect, we expect that positive affective reactions to cognitive conflict will produce systematic processing of an opponent’s arguments, which in turn will facilitate learning these arguments and developing a more complex cognitive representation of the discussion topic. In contrast, negative affective reactions will produce superficial processing of the opponent’s arguments coupled with rehearsal of one’s own arguments. When negative affect is mild, interactants are unlikely to learn the opponent’s arguments or to develop a complex representation of the topic. Moreover, when negative affect is strong, interactants may actually show cognitive regression -- less complex representations of the topic after interaction than before.<br />
<br />
==Results==<br />
==Explanation==<br />
==Further Information==<br />
===Connections to Other Studies===<br />
===Annotated Bibliography===<br />
===References===<br />
===Future Plans===</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Nokes_-_Dialectical_Interaction_and_Robust_Learning&diff=10330Nokes - Dialectical Interaction and Robust Learning2009-12-05T21:56:45Z<p>Dmbelenk: /* Independent Variables */</p>
<hr />
<div>Dialectical Interaction and Robust Learning<br />
==Summary Table==<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" style="text-align: left;"<br />
| '''PIs''' || Timothy Nokes, John Levine<br />
|-<br />
| '''Other Contributers''' || Daniel Belenky, Soniya Gadgil<br />
|-<br />
| '''Study Start Date''' || Sep. 1, 2009<br />
|-<br />
| '''Study End Date''' || May. 31, 2010<br />
|-<br />
| '''Site''' || University of Pittsburgh <br />
|-<br />
| '''Number of Students''' || ''N'' = ~180<br />
|-<br />
| '''Total Participant Hours''' || ~360.<br />
|-<br />
| '''DataShop''' || no data yet<br />
|}<br />
<br><br />
<br />
==Abstract==<br />
This work, which lies at the intersection of motivation, affect, social interaction and conceptual learning, studies the role of affect in a learning situation in which it is hypothesized to play a particularly prominent role. We focus on dialectical interaction, in which two or more people with roughly equal status but alternative viewpoints work together to solve a problem, perform a task, or reach agreement on an issue. The term “alternative viewpoints” is used broadly to include different stances on a controversial issue and different strategies for solving a problem. We assume that dialectical interaction affects participants’ cognitive activity in large part through its impact on their motivational states / goals and affective responses during discussion.<br />
==Background & Significance==<br />
<br />
==Glossary==<br />
==Research questions==<br />
How do students learn when engaged in a debate? Do they integrate their own viewpoint with that of their opponent, or focus only on their own side? Does the format of the debate affect this? Also, what motivational and affective factors play into this? How do student goals (like performance or mastery goals) influence what information gets processed? Do different affective experiences lead to different patterns of learning?<br />
==Independent Variables==<br />
Our first study has a 2 x 2 design. <br> Factor 1: Debate Format - Alternating Turns (1 minute each) or Free-Form <br> Factor 2: Debate Criterion - Substance or Rhetoric<br />
<br />
==Dependent Variables==<br />
Our dependent variables will consist of various measures of learning, gathered after the debate. These measures include a multiple-choice test, as well as an essay. Both of these will be evaluated in terms of how well a student has learned his side of the debate, as well as how well he has learned the other side, and how well he has integrated the two.<br />
<br />
We will also gather measures of affect during the debate. This will be used as a dependent variable to see if our manipulations relating to the debate structure influence the affective reactions experienced. We will also be able to affective response as a predictor of learning, or as mediating variable between debate and learning. These affective measures will come from analysis of the vocal parameters of speech of each participant, as well as by analysis of facial cues.<br />
==Hypothesis==<br />
We predict that focusing the debate on the substance of the arguments will produce a more coherent representation of both sides of the argument. We also predict that the free-form debate will lead to better learning of both sides, as the participants must be engaging with what a participant is saying more actively, and respond more immediately and thoroughly than when they have a minute between speaking turns.<br />
<br />
In terms of affect, we expect that positive affective reactions to cognitive conflict will produce systematic processing of an opponent’s arguments, which in turn will facilitate learning these arguments and developing a more complex cognitive representation of the discussion topic. In contrast, negative affective reactions will produce superficial processing of the opponent’s arguments coupled with rehearsal of one’s own arguments. When negative affect is mild, interactants are unlikely to learn the opponent’s arguments or to develop a complex representation of the topic. Moreover, when negative affect is strong, interactants may actually show cognitive regression -- less complex representations of the topic after interaction than before.<br />
<br />
==Results==<br />
==Explanation==<br />
==Further Information==<br />
===Connections to Other Studies===<br />
===Annotated Bibliography===<br />
===References===<br />
===Future Plans===</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Nokes_-_Dialectical_Interaction_and_Robust_Learning&diff=10329Nokes - Dialectical Interaction and Robust Learning2009-12-05T21:56:08Z<p>Dmbelenk: /* Hypothesis */</p>
<hr />
<div>Dialectical Interaction and Robust Learning<br />
==Summary Table==<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" style="text-align: left;"<br />
| '''PIs''' || Timothy Nokes, John Levine<br />
|-<br />
| '''Other Contributers''' || Daniel Belenky, Soniya Gadgil<br />
|-<br />
| '''Study Start Date''' || Sep. 1, 2009<br />
|-<br />
| '''Study End Date''' || May. 31, 2010<br />
|-<br />
| '''Site''' || University of Pittsburgh <br />
|-<br />
| '''Number of Students''' || ''N'' = ~180<br />
|-<br />
| '''Total Participant Hours''' || ~360.<br />
|-<br />
| '''DataShop''' || no data yet<br />
|}<br />
<br><br />
<br />
==Abstract==<br />
This work, which lies at the intersection of motivation, affect, social interaction and conceptual learning, studies the role of affect in a learning situation in which it is hypothesized to play a particularly prominent role. We focus on dialectical interaction, in which two or more people with roughly equal status but alternative viewpoints work together to solve a problem, perform a task, or reach agreement on an issue. The term “alternative viewpoints” is used broadly to include different stances on a controversial issue and different strategies for solving a problem. We assume that dialectical interaction affects participants’ cognitive activity in large part through its impact on their motivational states / goals and affective responses during discussion.<br />
==Background & Significance==<br />
<br />
==Glossary==<br />
==Research questions==<br />
How do students learn when engaged in a debate? Do they integrate their own viewpoint with that of their opponent, or focus only on their own side? Does the format of the debate affect this? Also, what motivational and affective factors play into this? How do student goals (like performance or mastery goals) influence what information gets processed? Do different affective experiences lead to different patterns of learning?<br />
==Independent Variables==<br />
Our first study has a 2 x 2 design. <br> Factor 1: Debate Format - Alternating Turns or Free-Form <br> Factor 2: Debate Criterion - Substance or Rhetoric<br />
<br />
==Dependent Variables==<br />
Our dependent variables will consist of various measures of learning, gathered after the debate. These measures include a multiple-choice test, as well as an essay. Both of these will be evaluated in terms of how well a student has learned his side of the debate, as well as how well he has learned the other side, and how well he has integrated the two.<br />
<br />
We will also gather measures of affect during the debate. This will be used as a dependent variable to see if our manipulations relating to the debate structure influence the affective reactions experienced. We will also be able to affective response as a predictor of learning, or as mediating variable between debate and learning. These affective measures will come from analysis of the vocal parameters of speech of each participant, as well as by analysis of facial cues.<br />
==Hypothesis==<br />
We predict that focusing the debate on the substance of the arguments will produce a more coherent representation of both sides of the argument. We also predict that the free-form debate will lead to better learning of both sides, as the participants must be engaging with what a participant is saying more actively, and respond more immediately and thoroughly than when they have a minute between speaking turns.<br />
<br />
In terms of affect, we expect that positive affective reactions to cognitive conflict will produce systematic processing of an opponent’s arguments, which in turn will facilitate learning these arguments and developing a more complex cognitive representation of the discussion topic. In contrast, negative affective reactions will produce superficial processing of the opponent’s arguments coupled with rehearsal of one’s own arguments. When negative affect is mild, interactants are unlikely to learn the opponent’s arguments or to develop a complex representation of the topic. Moreover, when negative affect is strong, interactants may actually show cognitive regression -- less complex representations of the topic after interaction than before.<br />
<br />
==Results==<br />
==Explanation==<br />
==Further Information==<br />
===Connections to Other Studies===<br />
===Annotated Bibliography===<br />
===References===<br />
===Future Plans===</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Nokes_-_Dialectical_Interaction_and_Robust_Learning&diff=10328Nokes - Dialectical Interaction and Robust Learning2009-12-05T21:50:35Z<p>Dmbelenk: </p>
<hr />
<div>Dialectical Interaction and Robust Learning<br />
==Summary Table==<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" style="text-align: left;"<br />
| '''PIs''' || Timothy Nokes, John Levine<br />
|-<br />
| '''Other Contributers''' || Daniel Belenky, Soniya Gadgil<br />
|-<br />
| '''Study Start Date''' || Sep. 1, 2009<br />
|-<br />
| '''Study End Date''' || May. 31, 2010<br />
|-<br />
| '''Site''' || University of Pittsburgh <br />
|-<br />
| '''Number of Students''' || ''N'' = ~180<br />
|-<br />
| '''Total Participant Hours''' || ~360.<br />
|-<br />
| '''DataShop''' || no data yet<br />
|}<br />
<br><br />
<br />
==Abstract==<br />
This work, which lies at the intersection of motivation, affect, social interaction and conceptual learning, studies the role of affect in a learning situation in which it is hypothesized to play a particularly prominent role. We focus on dialectical interaction, in which two or more people with roughly equal status but alternative viewpoints work together to solve a problem, perform a task, or reach agreement on an issue. The term “alternative viewpoints” is used broadly to include different stances on a controversial issue and different strategies for solving a problem. We assume that dialectical interaction affects participants’ cognitive activity in large part through its impact on their motivational states / goals and affective responses during discussion.<br />
==Background & Significance==<br />
<br />
==Glossary==<br />
==Research questions==<br />
How do students learn when engaged in a debate? Do they integrate their own viewpoint with that of their opponent, or focus only on their own side? Does the format of the debate affect this? Also, what motivational and affective factors play into this? How do student goals (like performance or mastery goals) influence what information gets processed? Do different affective experiences lead to different patterns of learning?<br />
==Independent Variables==<br />
Our first study has a 2 x 2 design. <br> Factor 1: Debate Format - Alternating Turns or Free-Form <br> Factor 2: Debate Criterion - Substance or Rhetoric<br />
<br />
==Dependent Variables==<br />
Our dependent variables will consist of various measures of learning, gathered after the debate. These measures include a multiple-choice test, as well as an essay. Both of these will be evaluated in terms of how well a student has learned his side of the debate, as well as how well he has learned the other side, and how well he has integrated the two.<br />
<br />
We will also gather measures of affect during the debate. This will be used as a dependent variable to see if our manipulations relating to the debate structure influence the affective reactions experienced. We will also be able to affective response as a predictor of learning, or as mediating variable between debate and learning. These affective measures will come from analysis of the vocal parameters of speech of each participant, as well as by analysis of facial cues.<br />
==Hypothesis==<br />
==Results==<br />
==Explanation==<br />
==Further Information==<br />
===Connections to Other Studies===<br />
===Annotated Bibliography===<br />
===References===<br />
===Future Plans===</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Nokes_-_Dialectical_Interaction_and_Robust_Learning&diff=10327Nokes - Dialectical Interaction and Robust Learning2009-12-05T21:40:53Z<p>Dmbelenk: /* Independent Variables */</p>
<hr />
<div>Dialectical Interaction and Robust Learning<br />
==Summary Table==<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" style="text-align: left;"<br />
| '''PIs''' || Timothy Nokes, John Levine<br />
|-<br />
| '''Other Contributers''' || Daniel Belenky, Soniya Gadgil<br />
|-<br />
| '''Study Start Date''' || Sep. 1, 2009<br />
|-<br />
| '''Study End Date''' || May. 31, 2010<br />
|-<br />
| '''Site''' || University of Pittsburgh <br />
|-<br />
| '''Number of Students''' || ''N'' = ~180<br />
|-<br />
| '''Total Participant Hours''' || ~360.<br />
|-<br />
| '''DataShop''' || no data yet<br />
|}<br />
<br><br />
<br />
==Abstract==<br />
This work, which lies at the intersection of motivation, affect, social interaction and conceptual learning, studies the role of affect in a learning situation in which it is hypothesized to play a particularly prominent role. We focus on dialectical interaction, in which two or more people with roughly equal status but alternative viewpoints work together to solve a problem, perform a task, or reach agreement on an issue. The term “alternative viewpoints” is used broadly to include different stances on a controversial issue and different strategies for solving a problem. We assume that dialectical interaction affects participants’ cognitive activity in large part through its impact on their motivational states / goals and affective responses during discussion.<br />
==Background & Significance==<br />
<br />
==Glossary==<br />
==Research questions==<br />
How do students learn when engaged in a debate? Do they integrate their own viewpoint with that of their opponent, or focus only on their own side? Does the format of the debate affect this? Also, what motivational and affective factors play into this? How do student goals (like performance or mastery goals) influence what information gets processed? Do different affective experiences lead to different patterns of learning?<br />
==Independent Variables==<br />
Our first study has a 2 x 2 design. <br> Factor 1: Debate Format - Alternating Turns or Free-Form <br> Factor 2: Debate Criterion - Substance or Rhetoric<br />
<br />
==Dependent Variables==<br />
==Hypothesis==<br />
==Results==<br />
==Explanation==<br />
==Further Information==<br />
===Connections to Other Studies===<br />
===Annotated Bibliography===<br />
===References===<br />
===Future Plans===</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Nokes_-_Dialectical_Interaction_and_Robust_Learning&diff=10325Nokes - Dialectical Interaction and Robust Learning2009-12-05T21:38:13Z<p>Dmbelenk: </p>
<hr />
<div>Dialectical Interaction and Robust Learning<br />
==Summary Table==<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" style="text-align: left;"<br />
| '''PIs''' || Timothy Nokes, John Levine<br />
|-<br />
| '''Other Contributers''' || Daniel Belenky, Soniya Gadgil<br />
|-<br />
| '''Study Start Date''' || Sep. 1, 2009<br />
|-<br />
| '''Study End Date''' || May. 31, 2010<br />
|-<br />
| '''Site''' || University of Pittsburgh <br />
|-<br />
| '''Number of Students''' || ''N'' = ~180<br />
|-<br />
| '''Total Participant Hours''' || ~360.<br />
|-<br />
| '''DataShop''' || no data yet<br />
|}<br />
<br><br />
<br />
==Abstract==<br />
This work, which lies at the intersection of motivation, affect, social interaction and conceptual learning, studies the role of affect in a learning situation in which it is hypothesized to play a particularly prominent role. We focus on dialectical interaction, in which two or more people with roughly equal status but alternative viewpoints work together to solve a problem, perform a task, or reach agreement on an issue. The term “alternative viewpoints” is used broadly to include different stances on a controversial issue and different strategies for solving a problem. We assume that dialectical interaction affects participants’ cognitive activity in large part through its impact on their motivational states / goals and affective responses during discussion.<br />
==Background & Significance==<br />
<br />
==Glossary==<br />
==Research questions==<br />
How do students learn when engaged in a debate? Do they integrate their own viewpoint with that of their opponent, or focus only on their own side? Does the format of the debate affect this? Also, what motivational and affective factors play into this? How do student goals (like performance or mastery goals) influence what information gets processed? Do different affective experiences lead to different patterns of learning?<br />
==Independent Variables==<br />
Our first study has a 2 x 2 design.<br />
Factor 1: Debate Format - Alternating Turns or Free-Form <br />
Factor 2: Debate Criterion - Substance or Rhetoric<br />
==Dependent Variables==<br />
==Hypothesis==<br />
==Results==<br />
==Explanation==<br />
==Further Information==<br />
===Connections to Other Studies===<br />
===Annotated Bibliography===<br />
===References===<br />
===Future Plans===</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Nokes_-_Dialectical_Interaction_and_Robust_Learning&diff=10322Nokes - Dialectical Interaction and Robust Learning2009-12-05T21:35:04Z<p>Dmbelenk: </p>
<hr />
<div>Dialectical Interaction and Robust Learning<br />
==Summary Table==<br />
<br />
{| border="1" cellspacing="0" cellpadding="5" style="text-align: left;"<br />
| '''PIs''' || Timothy Nokes, John Levine<br />
|-<br />
| '''Other Contributers''' || Daniel Belenky, Soniya Gadgil<br />
|-<br />
| '''Study Start Date''' || Sep. 1, 2009<br />
|-<br />
| '''Study End Date''' || May. 31, 2010<br />
|-<br />
| '''Site''' || University of Pittsburgh <br />
|-<br />
| '''Number of Students''' || ''N'' = ~180<br />
|-<br />
| '''Total Participant Hours''' || ~360.<br />
|-<br />
| '''DataShop''' || no data yet<br />
|}<br />
<br><br />
<br />
==Abstract==<br />
This work, which lies at the intersection of motivation, affect, social interaction and conceptual learning, studies the role of affect in a learning situation in which it is hypothesized to play a particularly prominent role. We focus on dialectical interaction, in which two or more people with roughly equal status but alternative viewpoints work together to solve a problem, perform a task, or reach agreement on an issue. The term “alternative viewpoints” is used broadly to include different stances on a controversial issue and different strategies for solving a problem. We assume that dialectical interaction affects participants’ cognitive activity in large part through its impact on their motivational states / goals and affective responses during discussion.<br />
==Background & Significance==<br />
<br />
==Glossary==<br />
==Research questions==<br />
How do students learn when engaged in a debate? Do they integrate their own viewpoint with that of their opponent, or focus only on their own side? What factors play into this? Namely, does the format of the debate matter? What role does a student's affective experience play in this?<br />
==Independent Variables==<br />
==Dependent Variables==<br />
==Hypothesis==<br />
==Results==<br />
==Explanation==<br />
==Further Information==<br />
===Connections to Other Studies===<br />
===Annotated Bibliography===<br />
===References===<br />
===Future Plans===</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Nokes_-_Dialectical_Interaction_and_Robust_Learning&diff=10320Nokes - Dialectical Interaction and Robust Learning2009-12-05T21:30:42Z<p>Dmbelenk: </p>
<hr />
<div>Dialectical Interaction and Robust Learning<br />
==Summary Table==<br />
==Abstract==<br />
This work, which lies at the intersection of motivation, affect, social interaction and conceptual learning, studies the role of affect in a learning situation in which it is hypothesized to play a particularly prominent role. We focus on dialectical interaction, in which two or more people with roughly equal status but alternative viewpoints work together to solve a problem, perform a task, or reach agreement on an issue. The term “alternative viewpoints” is used broadly to include different stances on a controversial issue and different strategies for solving a problem. We assume that dialectical interaction affects participants’ cognitive activity in large part through its impact on their motivational states / goals and affective responses during discussion.<br />
==Background & Significance==<br />
<br />
==Glossary==<br />
==Research questions==<br />
How do students learn when engaged in a debate? Do they integrate their own viewpoint with that of their opponent, or focus only on their own side? What factors play into this? Namely, does the format of the debate matter? What role does a student's affective experience play in this?<br />
==Independent Variables==<br />
==Dependent Variables==<br />
==Hypothesis==<br />
==Results==<br />
==Explanation==<br />
==Further Information==<br />
===Connections to Other Studies===<br />
===Annotated Bibliography===<br />
===References===<br />
===Future Plans===</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Nokes_-_Dialectical_Interaction_and_Robust_Learning&diff=10318Nokes - Dialectical Interaction and Robust Learning2009-12-05T21:29:41Z<p>Dmbelenk: New page: Dialectical Interaction and Robust Learning ==Summary Table== ==Abstract== This work, which lies at the intersection of motivation, affect, social interaction and conceptual learning, st...</p>
<hr />
<div>Dialectical Interaction and Robust Learning<br />
==Summary Table==<br />
==Abstract==<br />
This work, which lies at the intersection of motivation, affect, social interaction and conceptual learning, studies the role of affect in a learning situation in which it is hypothesized to play a particularly prominent role. We focus on dialectical interaction, in which two or more people with roughly equal status but alternative viewpoints work together to solve a problem, perform a task, or reach agreement on an issue. The term “alternative viewpoints” is used broadly to include different stances on a controversial issue and different strategies for solving a problem. We assume that dialectical interaction affects participants’ cognitive activity in large part through its impact on their motivational states / goals and affective responses during discussion.<br />
==Background & Significance==<br />
<br />
==Glossary==<br />
==Research questions==<br />
How do students learn when engaged in a debate? Do they integrate their own viewpoint with that of their opponent, or focus only on their own side? What factors play into this? Namely, does the format of the debate matter? What role does a student's affective experience play in this?<br />
<br />
==Independent Variables==<br />
==Dependent Variables==<br />
==Hypothesis==<br />
==Results==<br />
==Explanation==<br />
==Further Information==<br />
===Connections to Other Studies===<br />
===Annotated Bibliography===<br />
===References===<br />
===Future Plans===</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Achievement_Goals&diff=8880Achievement Goals2009-03-24T03:01:36Z<p>Dmbelenk: /* Approach/Avoidance Distinction */</p>
<hr />
<div>Achievement goals are the orientations for how and why people engage in achievement situations. They refer to the underlying aims a person has while engaging in an achievement setting, whether they are academic (such as in-class assignments or test preparation) or not (such as sports, work settings, etc.). These orientations guide interpretation of events in the achievement environment, and produce characteristic patterns of cognition, emotion and behaviors (Kaplan & Maehr, 2007). <br />
Early theory and research on achievement goals led to the proposal of two broad classes of goals, mastery and performance (i.e. Dweck & Leggett, 1988). Subsequent work contributed a differentiation between approach and avoidance orientations in addition to the mastery/performance split, creating a 2X2 framework (i.e. Elliot & McGregor, 2001). These four goals (mastery-approach, mastery-avoidance, performance-approach, and performance-avoidance) have been empirically tested and found to predict different patterns of outcomes, in terms of achievement, learning, cognitions, emotions, and behaviors, both in classroom and laboratory settings. <br />
<br />
==Achievement Goals==<br />
<br />
===Mastery Goals===<br />
Mastery goals (alternatively called learning goals, or task-focused goals) are concerned with the development of skill or competence. A mastery-oriented student is one whose primary goal is to improve her ability. Adoption of mastery goals has been found to be correlated with better self-regulation, deeper processing strategies, more positive affect, and increased topic interest (Harackiewicz et al., 2002; Kaplan & Maehr, 2007). However, mastery goals are less well correlated to measures of actual achievement, such as grades (Harackiewicz et al., 2002). <br />
<br />
===Performance Goals===<br />
Performance goals (alternatively called normative goals, or ego-focused goals) are concerned with demonstrations of skill. A performance-oriented student is one whose primary goal is to ensure an acceptable demonstration of her ability. Adoption of performance goals has been linked with a variety of effects, some positive and some negative. Performance goals are generally correlated with surface processing strategies, and negative affect and off-task behaviors following failures (Kaplan & Maehr, 2007; Dweck & Leggett, 1988). However, performance goals have also resulted in less clear links with achievement scores (such as grades), topic interest, and affect in general. Performance goals sometimes have a positive correlation with these outcomes, and sometimes have a negative correlation (see Midgley et al., 2001; Harackiewicz et al., 2002, for a discussion on the consistency of findings).<br />
<br />
===Approach/Avoidance Distinction===<br />
To address the mixed findings regarding performance goals, Andrew Elliot and colleagues proposed incorporating a distinction between approach goals and avoidance goals (e.g. Elliot, 1999; Elliot & McGregor, 2001). This idea was inspired by earlier research on motivational drives, which included such a distinction. Approach in this case refers to an orientation towards seeking positive outcomes, while avoidance refers to preventing negative outcomes. These dimensions were originally only added to performance goals to help make sense of the conflicting findings, leading to a trichotomous framework of mastery, performance-approach, and performance-avoidance goals. Subsequent studies have used factor analysis and extended this distinction into a full 2 X 2 framework (Elliot & McGregor, 2001; see [[Achievement Goals#Appendix|Appendix]] for the questionnaire). The four goals in this framework are:<br />
<br />
*Mastery-approach: This goal refers to wanting to develop skill or competence.<br />
*Mastery-avoidance: This goal refers to not wanting to lose competence or miss an opportunity to improve skill.<br />
*Performance-approach: This goal refers to wanting to demonstrate skill or competence.<br />
*Performance-avoidance: This goal refers to not wanting to demonstrate a lack of skill or competence. <br />
<br />
It is important to note that all of these goals are frameworks to understand the purposes a person has in engaging in achievement situations. They do not refer to the activities a person may engage in in service of these goals. For example, a performance-avoidance motivated student may still expend a lot of energy studying for a test. The important distinction is that this student's goal of not looking bad will lead him to engage, behave, think, and feel very differently than a student who studies with the goal of looking good, or one who is concerned with making sure he has mastered the material. <br />
<br />
Performance-avoidance goals generally lead to negative outcomes, while performance-approach seem to lead to positive outcomes in terms of achievement (Harackiewicz et al., 2002; but see Midgley et al., 2001 for a discussion of negative effects of performance-approach goals). Elliot (1999) was able to re-examine existing research to show that the prior mixed results for performance goals was due to this conflating of performance-approach and performance-avoidance goals. Most prior research had looked at mastery in exclusively approach terms, so the research that had shown a benefit for deeper processing, improved interest and affective response, and only small correlations with achievement generally applies to mastery-approach goals. Less is known about the effect of mastery-avoidance goals on cognition, emotion and behavior.<br />
<br />
==Experimental Manipulations==<br />
A fair amount of research on the effect of achievement goals has been correlational, administering questionnaires at the beginning of a semester and then observing the outcomes (i.e. via subsequent questionnaires and achievement measures, like final grades). However, experimental work has been done as well. These manipulations are usually instantiated by giving a set of instructions that explain the purpose or goal of some learning or test episode. Mastery manipulations usually stress that the work will be challenging, but that it can help one learn the material. Performance manipulations usually stress the evaluative nature of the task (i.e. "it will really show me what kids can do;" Elliott & Dweck, 1988) A meta-analysis (Utman, 1997) synthesized the results on experimentally-induced mastery and performance goals. It showed an advantage for mastery goals but mainly on complicated tasks, in older children, and for those working in groups. It should be noted that not every study found this advantage; performance goals were better than mastery in some of the studies included in the meta-analysis.<br />
<br />
==Links to Other Theories==<br />
Achievement goals have been linked to other theories as well. The strongest connection has been between achievement goals and implicit theories of intelligence (i.e. Blackwell, Trzesniewski, & Dweck, 2007). Implicit theories of intelligence are the beliefs people intuitively have about intelligence. An entity theory of intelligence holds that intelligence is set; a person has a certain "amount" of intelligence, and there is nothing else one can do about it. An incremental theory of intelligence holds that intelligence is malleable; a person's intelligence is a measure of his skill and effort, both of which can change. People who maintain an entity theory of intelligence are more likely to develop performance goals, as they would be more focused on demonstrations of existing ability, while those who hold incremental theories are more likely to develop mastery goals, since they are more focused on changing their skill levels, which are considered malleable. <br />
<br />
[[Self-efficacy]] is another theory of motivation which could play a role in achievement goals. [[Self-efficacy]] is the belief a person has about whether or not she can complete a given task. There is a role for this construct in achievement goal theory because achievement goals are fundamentally concerned with a person's competencies; if a person believes she can do something or not will influence a person's reactions to the environment. For example, two performance-approach oriented students may behave very similarly when they are both high in [[self-efficacy]], but very differently if one is low in [[self-efficacy]]. Self-efficacy has an influence on competence evaluations, which directly affects achievement goals. <br />
<br />
==Open Questions==<br />
Although achievement goals have been a major area of research over the past 30 years, much of that time has dealt with reconciling opposing viewpoints and findings. Today, a general consensus seems to exist in terms of the number of achievement goals (3 or 4, depending on the inclusion of mastery-avoidance), and some of their outcomes. However, there are still some open questions, some of which are particularly relevant to the PSLC:<br />
<br />
*Are some motivations more beneficial in certain situations? It seems like there could be a strong link between the type of learning outcomes sought (and the style of assessment used) and achievement goals. If a teacher is particularly interested in developing fluency, such as learning one's multiplication tables, or memorizing all of the state capitals, perhaps fostering performance-approach goals would be beneficial, as they seem to be linked to effort and surface strategies such as rehearsal, which are good for such tasks. However, if the goal is to develop a conceptual understanding that allows one to make good inferences about a complex topic, then mastery goals would seem to be more beneficial. This potential discrepancy between learning outcomes sought and achievement goals introduced could be a fruitful area of study, as well provide real value for [[optimized scheduling]] of learning environments.<br />
*Laboratory experiments have shown a benefit for mastery orientations (see Utman, 1997, for a review), but classroom studies have been less clear about those benefits, specifically in terms of achievement. This may also be due to a mismatch between the type of learning that occurs with mastery orientation and the type of assessments used. Could assessments of [[robust learning]] account for this? <br />
<br />
There are other open questions that may be less particularly relevant to the PSLC:<br />
<br />
*Many studies look at achievement goal orientations in exclusive terms, but students may in fact be adopting a variety of them. What would it mean for a student to be high in both mastery-approach and performance-approach? Or for someone to be very performance-approach oriented but particularly not mastery-avoidance oriented? Are the effects that have been reported in the extant literature additive? Or do they interact to create unique profiles?<br />
*Just how flexible are these orientations? Achievement goals were originally conceived of as a response to motivation theories that relied heavily on dispositional constructs, and were more heavily focused on “a more specific, contextual level of analysis” (Elliot, 2005). However, much of the more recent research has used a more dispositional assessment level of achievement goals. It is unclear exactly how predictive a dispositional assessment at the beginning of a semester is on how an individual will respond in any given situation. How much of the response will come from the disposition, and how much from the situation-specific aspects of the environment? <br />
*Do achievement goals produce fundamentally different outcomes in different age groups? For example, do performance-oriented college students have a different pattern of cognitions, strategies, and affect than performance-oriented middle-school students?<br />
<br />
==References==<br />
*Blackwell, L.S., Trzesniewski, K. H., & Dweck, C.S. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. ''Child Development, 78,'' 246-263.<br />
*Dweck, C.S., & Leggett, E.L. (1988). A social-cognitive approach to motivation and personality. ''Psychological Review, 95,'' 256-273. <br />
*Elliot, A.J. (1999). Approach and avoidance motivation and achievement goals. ''Educational Psychologist, 34,'' 149-169. <br />
*Elliot, A.J. (2005). A conceptual history of the achievement goal construct. In A.J. Elliot & Dweck C. S. (Eds.), ''Handbook of Competence and Motivation,'' (52-73). New York: Guilford Press.<br />
*Elliot, A.J., & McGregor, H. A. (2001). A 2 X 2 achievement goal framework. ''Journal of Personailty and Social Psychology, 80,'' 501-519.<br />
*Elliott, E.S., & Dweck, C.S. (1988). Goals: An approach to motivation and achievement. ''Journal of Personality and Social Psychology, 54,'' 5-12. <br />
*Kaplan, A., & Maehr, M.L. (2007). The contributions and prospects of goal orientation theory. ''Educational Psychology Review, 19,'' 141-184. <br />
*Harackiewicz, J. M., Barron, K. E., Pintrich, P. R., Elliot, A. J., & Thrash, T. M. (2002). Revision of achievement goal theory: Necessary and illuminating. ''Journal of Educational Psychology, 94,'' 638–645.<br />
*Midgley, C., Kaplan, A., & Middleton, M. (2001). Performance-approach goals; Good for what, for whom, under what circumstances, and at what cost? ''Journal of Educational Psychology, 93,'' 77-86. <br />
*Utman, C.H. (1997). Performance effects of motivational state: A meta-analysis. ''Personality and Social Psychology Review, 1,'' 170-182.<br />
<br />
==Appendix==<br />
Here is the 12-item measure used by Elliot & McGregor (2001). The first three items measure performance-approach(P.Ap), the next three mastery-avoidance(M.Av), then mastery-approach (M.Ap), and then performance-avoidance(P.Av).<br />
#It is important for me to do better than other students(P.Ap).<br />
#It is important for me to do well compared to others in this class(P.Ap).<br />
#My goal in in this class is to get a better grade than most of the other students(P.Ap).<br />
#I worry that I may not learn all that I possibly could in this class(M.Av).<br />
#Sometimes I'm afraid that I may not understand the content of this class as thoroughly as I'd like(M.Av).<br />
#I am often concerned that I may not learn all that there is to learn in this class(M.Av).<br />
#I want to learn as much as possible from this class(M.Ap).<br />
#It is important for me to understand the content of this course as thoroughly as possible(M.Ap).<br />
#I desire to completely master the material presented in this class(M.Ap).<br />
#I just want to avoid doing poorly in this class(P.Av).<br />
#My goal in this class is to avoid performing poorly(P.Av).<br />
#My fear of performing poorly in this class is often what motivates(P.Av).</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Achievement_Goals&diff=8879Achievement Goals2009-03-24T02:56:14Z<p>Dmbelenk: /* Open Questions */</p>
<hr />
<div>Achievement goals are the orientations for how and why people engage in achievement situations. They refer to the underlying aims a person has while engaging in an achievement setting, whether they are academic (such as in-class assignments or test preparation) or not (such as sports, work settings, etc.). These orientations guide interpretation of events in the achievement environment, and produce characteristic patterns of cognition, emotion and behaviors (Kaplan & Maehr, 2007). <br />
Early theory and research on achievement goals led to the proposal of two broad classes of goals, mastery and performance (i.e. Dweck & Leggett, 1988). Subsequent work contributed a differentiation between approach and avoidance orientations in addition to the mastery/performance split, creating a 2X2 framework (i.e. Elliot & McGregor, 2001). These four goals (mastery-approach, mastery-avoidance, performance-approach, and performance-avoidance) have been empirically tested and found to predict different patterns of outcomes, in terms of achievement, learning, cognitions, emotions, and behaviors, both in classroom and laboratory settings. <br />
<br />
==Achievement Goals==<br />
<br />
===Mastery Goals===<br />
Mastery goals (alternatively called learning goals, or task-focused goals) are concerned with the development of skill or competence. A mastery-oriented student is one whose primary goal is to improve her ability. Adoption of mastery goals has been found to be correlated with better self-regulation, deeper processing strategies, more positive affect, and increased topic interest (Harackiewicz et al., 2002; Kaplan & Maehr, 2007). However, mastery goals are less well correlated to measures of actual achievement, such as grades (Harackiewicz et al., 2002). <br />
<br />
===Performance Goals===<br />
Performance goals (alternatively called normative goals, or ego-focused goals) are concerned with demonstrations of skill. A performance-oriented student is one whose primary goal is to ensure an acceptable demonstration of her ability. Adoption of performance goals has been linked with a variety of effects, some positive and some negative. Performance goals are generally correlated with surface processing strategies, and negative affect and off-task behaviors following failures (Kaplan & Maehr, 2007; Dweck & Leggett, 1988). However, performance goals have also resulted in less clear links with achievement scores (such as grades), topic interest, and affect in general. Performance goals sometimes have a positive correlation with these outcomes, and sometimes have a negative correlation (see Midgley et al., 2001; Harackiewicz et al., 2002, for a discussion on the consistency of findings).<br />
<br />
===Approach/Avoidance Distinction===<br />
To address the mixed findings regarding performance goals, Andrew Elliot and colleagues proposed incorporating a distinction between approach goals and avoidance goals (e.g. Elliot, 1999; Elliot & McGregor, 2001). This idea was inspired by earlier research on motivational drives, which included such a distinction. Approach in this case refers to an orientation towards seeking positive outcomes, while avoidance refers to preventing negative outcomes. These dimensions were originally only added to performance goals to help make sense of the conflicting findings, leading to a trichotomous framework of mastery, performance-approach, and performance-avoidance goals. Subsequent studies have used factor analysis and extended this distinction into a full 2 X 2 framework (Elliot & McGregor, 2001; see Appendix for the questionnaire). The four goals in this framework are:<br />
<br />
*Mastery-approach: This goal refers to wanting to develop skill or competence.<br />
*Mastery-avoidance: This goal refers to not wanting to lose competence or miss an opportunity to improve skill.<br />
*Performance-approach: This goal refers to wanting to demonstrate skill or competence.<br />
*Performance-avoidance: This goal refers to not wanting to demonstrate a lack of skill or competence. <br />
<br />
It is important to note that all of these goals are frameworks to understand the purposes a person has in engaging in achievement situations. They do not refer to the activities a person may engage in in service of these goals. For example, a performance-avoidance motivated student may still expend a lot of energy studying for a test. The important distinction is that this student's goal of not looking bad will lead him to engage, behave, think, and feel very differently than a student who studies with the goal of looking good, or one who is concerned with making sure he has mastered the material. <br />
<br />
Performance-avoidance goals generally lead to negative outcomes, while performance-approach seem to lead to positive outcomes in terms of achievement (Harackiewicz et al., 2002; but see Midgley et al., 2001 for a discussion of negative effects of performance-approach goals). Elliot (1999) was able to re-examine existing research to show that the prior mixed results for performance goals was due to this conflating of performance-approach and performance-avoidance goals. Most prior research had looked at mastery in exclusively approach terms, so the research that had shown a benefit for deeper processing, improved interest and affective response, and only small correlations with achievement generally applies to mastery-approach goals. Less is known about the effect of mastery-avoidance goals on cognition, emotion and behavior.<br />
<br />
==Experimental Manipulations==<br />
A fair amount of research on the effect of achievement goals has been correlational, administering questionnaires at the beginning of a semester and then observing the outcomes (i.e. via subsequent questionnaires and achievement measures, like final grades). However, experimental work has been done as well. These manipulations are usually instantiated by giving a set of instructions that explain the purpose or goal of some learning or test episode. Mastery manipulations usually stress that the work will be challenging, but that it can help one learn the material. Performance manipulations usually stress the evaluative nature of the task (i.e. "it will really show me what kids can do;" Elliott & Dweck, 1988) A meta-analysis (Utman, 1997) synthesized the results on experimentally-induced mastery and performance goals. It showed an advantage for mastery goals but mainly on complicated tasks, in older children, and for those working in groups. It should be noted that not every study found this advantage; performance goals were better than mastery in some of the studies included in the meta-analysis.<br />
<br />
==Links to Other Theories==<br />
Achievement goals have been linked to other theories as well. The strongest connection has been between achievement goals and implicit theories of intelligence (i.e. Blackwell, Trzesniewski, & Dweck, 2007). Implicit theories of intelligence are the beliefs people intuitively have about intelligence. An entity theory of intelligence holds that intelligence is set; a person has a certain "amount" of intelligence, and there is nothing else one can do about it. An incremental theory of intelligence holds that intelligence is malleable; a person's intelligence is a measure of his skill and effort, both of which can change. People who maintain an entity theory of intelligence are more likely to develop performance goals, as they would be more focused on demonstrations of existing ability, while those who hold incremental theories are more likely to develop mastery goals, since they are more focused on changing their skill levels, which are considered malleable. <br />
<br />
[[Self-efficacy]] is another theory of motivation which could play a role in achievement goals. [[Self-efficacy]] is the belief a person has about whether or not she can complete a given task. There is a role for this construct in achievement goal theory because achievement goals are fundamentally concerned with a person's competencies; if a person believes she can do something or not will influence a person's reactions to the environment. For example, two performance-approach oriented students may behave very similarly when they are both high in [[self-efficacy]], but very differently if one is low in [[self-efficacy]]. Self-efficacy has an influence on competence evaluations, which directly affects achievement goals. <br />
<br />
==Open Questions==<br />
Although achievement goals have been a major area of research over the past 30 years, much of that time has dealt with reconciling opposing viewpoints and findings. Today, a general consensus seems to exist in terms of the number of achievement goals (3 or 4, depending on the inclusion of mastery-avoidance), and some of their outcomes. However, there are still some open questions, some of which are particularly relevant to the PSLC:<br />
<br />
*Are some motivations more beneficial in certain situations? It seems like there could be a strong link between the type of learning outcomes sought (and the style of assessment used) and achievement goals. If a teacher is particularly interested in developing fluency, such as learning one's multiplication tables, or memorizing all of the state capitals, perhaps fostering performance-approach goals would be beneficial, as they seem to be linked to effort and surface strategies such as rehearsal, which are good for such tasks. However, if the goal is to develop a conceptual understanding that allows one to make good inferences about a complex topic, then mastery goals would seem to be more beneficial. This potential discrepancy between learning outcomes sought and achievement goals introduced could be a fruitful area of study, as well provide real value for [[optimized scheduling]] of learning environments.<br />
*Laboratory experiments have shown a benefit for mastery orientations (see Utman, 1997, for a review), but classroom studies have been less clear about those benefits, specifically in terms of achievement. This may also be due to a mismatch between the type of learning that occurs with mastery orientation and the type of assessments used. Could assessments of [[robust learning]] account for this? <br />
<br />
There are other open questions that may be less particularly relevant to the PSLC:<br />
<br />
*Many studies look at achievement goal orientations in exclusive terms, but students may in fact be adopting a variety of them. What would it mean for a student to be high in both mastery-approach and performance-approach? Or for someone to be very performance-approach oriented but particularly not mastery-avoidance oriented? Are the effects that have been reported in the extant literature additive? Or do they interact to create unique profiles?<br />
*Just how flexible are these orientations? Achievement goals were originally conceived of as a response to motivation theories that relied heavily on dispositional constructs, and were more heavily focused on “a more specific, contextual level of analysis” (Elliot, 2005). However, much of the more recent research has used a more dispositional assessment level of achievement goals. It is unclear exactly how predictive a dispositional assessment at the beginning of a semester is on how an individual will respond in any given situation. How much of the response will come from the disposition, and how much from the situation-specific aspects of the environment? <br />
*Do achievement goals produce fundamentally different outcomes in different age groups? For example, do performance-oriented college students have a different pattern of cognitions, strategies, and affect than performance-oriented middle-school students?<br />
<br />
==References==<br />
*Blackwell, L.S., Trzesniewski, K. H., & Dweck, C.S. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. ''Child Development, 78,'' 246-263.<br />
*Dweck, C.S., & Leggett, E.L. (1988). A social-cognitive approach to motivation and personality. ''Psychological Review, 95,'' 256-273. <br />
*Elliot, A.J. (1999). Approach and avoidance motivation and achievement goals. ''Educational Psychologist, 34,'' 149-169. <br />
*Elliot, A.J. (2005). A conceptual history of the achievement goal construct. In A.J. Elliot & Dweck C. S. (Eds.), ''Handbook of Competence and Motivation,'' (52-73). New York: Guilford Press.<br />
*Elliot, A.J., & McGregor, H. A. (2001). A 2 X 2 achievement goal framework. ''Journal of Personailty and Social Psychology, 80,'' 501-519.<br />
*Elliott, E.S., & Dweck, C.S. (1988). Goals: An approach to motivation and achievement. ''Journal of Personality and Social Psychology, 54,'' 5-12. <br />
*Kaplan, A., & Maehr, M.L. (2007). The contributions and prospects of goal orientation theory. ''Educational Psychology Review, 19,'' 141-184. <br />
*Harackiewicz, J. M., Barron, K. E., Pintrich, P. R., Elliot, A. J., & Thrash, T. M. (2002). Revision of achievement goal theory: Necessary and illuminating. ''Journal of Educational Psychology, 94,'' 638–645.<br />
*Midgley, C., Kaplan, A., & Middleton, M. (2001). Performance-approach goals; Good for what, for whom, under what circumstances, and at what cost? ''Journal of Educational Psychology, 93,'' 77-86. <br />
*Utman, C.H. (1997). Performance effects of motivational state: A meta-analysis. ''Personality and Social Psychology Review, 1,'' 170-182.<br />
<br />
==Appendix==<br />
Here is the 12-item measure used by Elliot & McGregor (2001). The first three items measure performance-approach(P.Ap), the next three mastery-avoidance(M.Av), then mastery-approach (M.Ap), and then performance-avoidance(P.Av).<br />
#It is important for me to do better than other students(P.Ap).<br />
#It is important for me to do well compared to others in this class(P.Ap).<br />
#My goal in in this class is to get a better grade than most of the other students(P.Ap).<br />
#I worry that I may not learn all that I possibly could in this class(M.Av).<br />
#Sometimes I'm afraid that I may not understand the content of this class as thoroughly as I'd like(M.Av).<br />
#I am often concerned that I may not learn all that there is to learn in this class(M.Av).<br />
#I want to learn as much as possible from this class(M.Ap).<br />
#It is important for me to understand the content of this course as thoroughly as possible(M.Ap).<br />
#I desire to completely master the material presented in this class(M.Ap).<br />
#I just want to avoid doing poorly in this class(P.Av).<br />
#My goal in this class is to avoid performing poorly(P.Av).<br />
#My fear of performing poorly in this class is often what motivates(P.Av).</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Achievement_Goals&diff=8878Achievement Goals2009-03-24T02:53:37Z<p>Dmbelenk: /* Performance Goals */</p>
<hr />
<div>Achievement goals are the orientations for how and why people engage in achievement situations. They refer to the underlying aims a person has while engaging in an achievement setting, whether they are academic (such as in-class assignments or test preparation) or not (such as sports, work settings, etc.). These orientations guide interpretation of events in the achievement environment, and produce characteristic patterns of cognition, emotion and behaviors (Kaplan & Maehr, 2007). <br />
Early theory and research on achievement goals led to the proposal of two broad classes of goals, mastery and performance (i.e. Dweck & Leggett, 1988). Subsequent work contributed a differentiation between approach and avoidance orientations in addition to the mastery/performance split, creating a 2X2 framework (i.e. Elliot & McGregor, 2001). These four goals (mastery-approach, mastery-avoidance, performance-approach, and performance-avoidance) have been empirically tested and found to predict different patterns of outcomes, in terms of achievement, learning, cognitions, emotions, and behaviors, both in classroom and laboratory settings. <br />
<br />
==Achievement Goals==<br />
<br />
===Mastery Goals===<br />
Mastery goals (alternatively called learning goals, or task-focused goals) are concerned with the development of skill or competence. A mastery-oriented student is one whose primary goal is to improve her ability. Adoption of mastery goals has been found to be correlated with better self-regulation, deeper processing strategies, more positive affect, and increased topic interest (Harackiewicz et al., 2002; Kaplan & Maehr, 2007). However, mastery goals are less well correlated to measures of actual achievement, such as grades (Harackiewicz et al., 2002). <br />
<br />
===Performance Goals===<br />
Performance goals (alternatively called normative goals, or ego-focused goals) are concerned with demonstrations of skill. A performance-oriented student is one whose primary goal is to ensure an acceptable demonstration of her ability. Adoption of performance goals has been linked with a variety of effects, some positive and some negative. Performance goals are generally correlated with surface processing strategies, and negative affect and off-task behaviors following failures (Kaplan & Maehr, 2007; Dweck & Leggett, 1988). However, performance goals have also resulted in less clear links with achievement scores (such as grades), topic interest, and affect in general. Performance goals sometimes have a positive correlation with these outcomes, and sometimes have a negative correlation (see Midgley et al., 2001; Harackiewicz et al., 2002, for a discussion on the consistency of findings).<br />
<br />
===Approach/Avoidance Distinction===<br />
To address the mixed findings regarding performance goals, Andrew Elliot and colleagues proposed incorporating a distinction between approach goals and avoidance goals (e.g. Elliot, 1999; Elliot & McGregor, 2001). This idea was inspired by earlier research on motivational drives, which included such a distinction. Approach in this case refers to an orientation towards seeking positive outcomes, while avoidance refers to preventing negative outcomes. These dimensions were originally only added to performance goals to help make sense of the conflicting findings, leading to a trichotomous framework of mastery, performance-approach, and performance-avoidance goals. Subsequent studies have used factor analysis and extended this distinction into a full 2 X 2 framework (Elliot & McGregor, 2001; see Appendix for the questionnaire). The four goals in this framework are:<br />
<br />
*Mastery-approach: This goal refers to wanting to develop skill or competence.<br />
*Mastery-avoidance: This goal refers to not wanting to lose competence or miss an opportunity to improve skill.<br />
*Performance-approach: This goal refers to wanting to demonstrate skill or competence.<br />
*Performance-avoidance: This goal refers to not wanting to demonstrate a lack of skill or competence. <br />
<br />
It is important to note that all of these goals are frameworks to understand the purposes a person has in engaging in achievement situations. They do not refer to the activities a person may engage in in service of these goals. For example, a performance-avoidance motivated student may still expend a lot of energy studying for a test. The important distinction is that this student's goal of not looking bad will lead him to engage, behave, think, and feel very differently than a student who studies with the goal of looking good, or one who is concerned with making sure he has mastered the material. <br />
<br />
Performance-avoidance goals generally lead to negative outcomes, while performance-approach seem to lead to positive outcomes in terms of achievement (Harackiewicz et al., 2002; but see Midgley et al., 2001 for a discussion of negative effects of performance-approach goals). Elliot (1999) was able to re-examine existing research to show that the prior mixed results for performance goals was due to this conflating of performance-approach and performance-avoidance goals. Most prior research had looked at mastery in exclusively approach terms, so the research that had shown a benefit for deeper processing, improved interest and affective response, and only small correlations with achievement generally applies to mastery-approach goals. Less is known about the effect of mastery-avoidance goals on cognition, emotion and behavior.<br />
<br />
==Experimental Manipulations==<br />
A fair amount of research on the effect of achievement goals has been correlational, administering questionnaires at the beginning of a semester and then observing the outcomes (i.e. via subsequent questionnaires and achievement measures, like final grades). However, experimental work has been done as well. These manipulations are usually instantiated by giving a set of instructions that explain the purpose or goal of some learning or test episode. Mastery manipulations usually stress that the work will be challenging, but that it can help one learn the material. Performance manipulations usually stress the evaluative nature of the task (i.e. "it will really show me what kids can do;" Elliott & Dweck, 1988) A meta-analysis (Utman, 1997) synthesized the results on experimentally-induced mastery and performance goals. It showed an advantage for mastery goals but mainly on complicated tasks, in older children, and for those working in groups. It should be noted that not every study found this advantage; performance goals were better than mastery in some of the studies included in the meta-analysis.<br />
<br />
==Links to Other Theories==<br />
Achievement goals have been linked to other theories as well. The strongest connection has been between achievement goals and implicit theories of intelligence (i.e. Blackwell, Trzesniewski, & Dweck, 2007). Implicit theories of intelligence are the beliefs people intuitively have about intelligence. An entity theory of intelligence holds that intelligence is set; a person has a certain "amount" of intelligence, and there is nothing else one can do about it. An incremental theory of intelligence holds that intelligence is malleable; a person's intelligence is a measure of his skill and effort, both of which can change. People who maintain an entity theory of intelligence are more likely to develop performance goals, as they would be more focused on demonstrations of existing ability, while those who hold incremental theories are more likely to develop mastery goals, since they are more focused on changing their skill levels, which are considered malleable. <br />
<br />
[[Self-efficacy]] is another theory of motivation which could play a role in achievement goals. [[Self-efficacy]] is the belief a person has about whether or not she can complete a given task. There is a role for this construct in achievement goal theory because achievement goals are fundamentally concerned with a person's competencies; if a person believes she can do something or not will influence a person's reactions to the environment. For example, two performance-approach oriented students may behave very similarly when they are both high in [[self-efficacy]], but very differently if one is low in [[self-efficacy]]. Self-efficacy has an influence on competence evaluations, which directly affects achievement goals. <br />
<br />
==Open Questions==<br />
Although achievement goals have been a major area of research over the past 30 years, much of that time has dealt with reconciling opposing viewpoints and findings. Today, a general consensus seems to exist in terms of the number of achievement goals (3 or 4, depending on the inclusion of mastery-avoidance), and some of their outcomes. However, there are still some open questions, some of which are particularly relevant to the PSLC:<br />
<br />
*Are some motivations more beneficial in certain situations? It seems like there could be a strong link between the type of learning outcomes sought (and the style of assessment used) and achievement goals. If a teacher is particularly interested in developing fluency, such as learning one's multiplication tables, or memorizing all of the state capitals, perhaps fostering performance-approach goals would be beneficial, as they seem to be linked to effort and surface strategies such as rehearsal, which are good for such tasks. However, if the goal is to develop a conceptual understanding that allows one to make good inferences about a complex topic, then mastery goals would seem to be more beneficial. This potential discrepancy between learning outcomes sought and achievement goals introduced could be a fruitful area of study, as well provide real value for optimizing learning environments.<br />
*Laboratory experiments have shown a benefit for mastery orientations (see Utman, 1997, for a review), but classroom studies have been less clear about those benefits, specifically in terms of achievement. This may also be due to a mismatch between the type of learning that occurs with mastery orientation and the type of assessments used. Could assessments of [[robust learning]] account for this? <br />
<br />
There are other open questions that may be less particularly relevant to the PSLC:<br />
<br />
*Many studies look at achievement goal orientations in exclusive terms, but students may in fact be adopting a variety of them. What would it mean for a student to be high in both mastery-approach and performance-approach? Or for someone to be very performance-approach oriented but particularly not mastery-avoidance oriented? Are the effects that have been reported in the extant literature additive? Or do they interact to create unique profiles?<br />
*Just how flexible are these orientations? Achievement goals were originally conceived of as a response to motivation theories that relied heavily on dispositional constructs, and were more heavily focused on “a more specific, contextual level of analysis” (Elliot, 2005). However, much of the more recent research has used a more dispositional assessment level of achievement goals. It is unclear exactly how predictive a dispositional assessment at the beginning of a semester is on how an individual will respond in any given situation. How much of the response will come from the disposition, and how much from the situation-specific aspects of the environment? <br />
*Do achievement goals produce fundamentally different outcomes in different age groups? For example, do performance-oriented college students have a different pattern of cognitions, strategies, and affect than performance-oriented middle-school students?<br />
<br />
<br />
==References==<br />
*Blackwell, L.S., Trzesniewski, K. H., & Dweck, C.S. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. ''Child Development, 78,'' 246-263.<br />
*Dweck, C.S., & Leggett, E.L. (1988). A social-cognitive approach to motivation and personality. ''Psychological Review, 95,'' 256-273. <br />
*Elliot, A.J. (1999). Approach and avoidance motivation and achievement goals. ''Educational Psychologist, 34,'' 149-169. <br />
*Elliot, A.J. (2005). A conceptual history of the achievement goal construct. In A.J. Elliot & Dweck C. S. (Eds.), ''Handbook of Competence and Motivation,'' (52-73). New York: Guilford Press.<br />
*Elliot, A.J., & McGregor, H. A. (2001). A 2 X 2 achievement goal framework. ''Journal of Personailty and Social Psychology, 80,'' 501-519.<br />
*Elliott, E.S., & Dweck, C.S. (1988). Goals: An approach to motivation and achievement. ''Journal of Personality and Social Psychology, 54,'' 5-12. <br />
*Kaplan, A., & Maehr, M.L. (2007). The contributions and prospects of goal orientation theory. ''Educational Psychology Review, 19,'' 141-184. <br />
*Harackiewicz, J. M., Barron, K. E., Pintrich, P. R., Elliot, A. J., & Thrash, T. M. (2002). Revision of achievement goal theory: Necessary and illuminating. ''Journal of Educational Psychology, 94,'' 638–645.<br />
*Midgley, C., Kaplan, A., & Middleton, M. (2001). Performance-approach goals; Good for what, for whom, under what circumstances, and at what cost? ''Journal of Educational Psychology, 93,'' 77-86. <br />
*Utman, C.H. (1997). Performance effects of motivational state: A meta-analysis. ''Personality and Social Psychology Review, 1,'' 170-182.<br />
<br />
==Appendix==<br />
Here is the 12-item measure used by Elliot & McGregor (2001). The first three items measure performance-approach(P.Ap), the next three mastery-avoidance(M.Av), then mastery-approach (M.Ap), and then performance-avoidance(P.Av).<br />
#It is important for me to do better than other students(P.Ap).<br />
#It is important for me to do well compared to others in this class(P.Ap).<br />
#My goal in in this class is to get a better grade than most of the other students(P.Ap).<br />
#I worry that I may not learn all that I possibly could in this class(M.Av).<br />
#Sometimes I'm afraid that I may not understand the content of this class as thoroughly as I'd like(M.Av).<br />
#I am often concerned that I may not learn all that there is to learn in this class(M.Av).<br />
#I want to learn as much as possible from this class(M.Ap).<br />
#It is important for me to understand the content of this course as thoroughly as possible(M.Ap).<br />
#I desire to completely master the material presented in this class(M.Ap).<br />
#I just want to avoid doing poorly in this class(P.Av).<br />
#My goal in this class is to avoid performing poorly(P.Av).<br />
#My fear of performing poorly in this class is often what motivates(P.Av).</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Achievement_Goals&diff=8877Achievement Goals2009-03-24T02:50:06Z<p>Dmbelenk: /* Experimental Manipulations */</p>
<hr />
<div>Achievement goals are the orientations for how and why people engage in achievement situations. They refer to the underlying aims a person has while engaging in an achievement setting, whether they are academic (such as in-class assignments or test preparation) or not (such as sports, work settings, etc.). These orientations guide interpretation of events in the achievement environment, and produce characteristic patterns of cognition, emotion and behaviors (Kaplan & Maehr, 2007). <br />
Early theory and research on achievement goals led to the proposal of two broad classes of goals, mastery and performance (i.e. Dweck & Leggett, 1988). Subsequent work contributed a differentiation between approach and avoidance orientations in addition to the mastery/performance split, creating a 2X2 framework (i.e. Elliot & McGregor, 2001). These four goals (mastery-approach, mastery-avoidance, performance-approach, and performance-avoidance) have been empirically tested and found to predict different patterns of outcomes, in terms of achievement, learning, cognitions, emotions, and behaviors, both in classroom and laboratory settings. <br />
<br />
==Achievement Goals==<br />
<br />
===Mastery Goals===<br />
Mastery goals (alternatively called learning goals, or task-focused goals) are concerned with the development of skill or competence. A mastery-oriented student is one whose primary goal is to improve her ability. Adoption of mastery goals has been found to be correlated with better self-regulation, deeper processing strategies, more positive affect, and increased topic interest (Harackiewicz et al., 2002; Kaplan & Maehr, 2007). However, mastery goals are less well correlated to measures of actual achievement, such as grades (Harackiewicz et al., 2002). <br />
<br />
===Performance Goals===<br />
Performance goals (alternatively called normative goals, or ego-focused goals) are concerned with demonstrations of skill. A performance-oriented student is one whose primary goal is to ensure an acceptable demonstration of her ability. Adoption of performance goals has been linked with a variety of effects, some positive and some negative. Performance goals are generally correlated with surface processing strategies, and negative affect and off-task behaviors following failures (Kaplan & Maehr, 2007; Dweck & Leggett, 1988). However, performance goals have also resulted in less clear links with achievement scores (such as grades), topic interest, and affect in general. Performance goals sometimes have a positive correlation with these outcomes, and sometimes have a negative correlation (see Midgley et al., 2001; and Harackiewicz et al., 2002, for a discussion on the consistency of findings).<br />
<br />
===Approach/Avoidance Distinction===<br />
To address the mixed findings regarding performance goals, Andrew Elliot and colleagues proposed incorporating a distinction between approach goals and avoidance goals (e.g. Elliot, 1999; Elliot & McGregor, 2001). This idea was inspired by earlier research on motivational drives, which included such a distinction. Approach in this case refers to an orientation towards seeking positive outcomes, while avoidance refers to preventing negative outcomes. These dimensions were originally only added to performance goals to help make sense of the conflicting findings, leading to a trichotomous framework of mastery, performance-approach, and performance-avoidance goals. Subsequent studies have used factor analysis and extended this distinction into a full 2 X 2 framework (Elliot & McGregor, 2001; see Appendix for the questionnaire). The four goals in this framework are:<br />
<br />
*Mastery-approach: This goal refers to wanting to develop skill or competence.<br />
*Mastery-avoidance: This goal refers to not wanting to lose competence or miss an opportunity to improve skill.<br />
*Performance-approach: This goal refers to wanting to demonstrate skill or competence.<br />
*Performance-avoidance: This goal refers to not wanting to demonstrate a lack of skill or competence. <br />
<br />
It is important to note that all of these goals are frameworks to understand the purposes a person has in engaging in achievement situations. They do not refer to the activities a person may engage in in service of these goals. For example, a performance-avoidance motivated student may still expend a lot of energy studying for a test. The important distinction is that this student's goal of not looking bad will lead him to engage, behave, think, and feel very differently than a student who studies with the goal of looking good, or one who is concerned with making sure he has mastered the material. <br />
<br />
Performance-avoidance goals generally lead to negative outcomes, while performance-approach seem to lead to positive outcomes in terms of achievement (Harackiewicz et al., 2002; but see Midgley et al., 2001 for a discussion of negative effects of performance-approach goals). Elliot (1999) was able to re-examine existing research to show that the prior mixed results for performance goals was due to this conflating of performance-approach and performance-avoidance goals. Most prior research had looked at mastery in exclusively approach terms, so the research that had shown a benefit for deeper processing, improved interest and affective response, and only small correlations with achievement generally applies to mastery-approach goals. Less is known about the effect of mastery-avoidance goals on cognition, emotion and behavior.<br />
<br />
==Experimental Manipulations==<br />
A fair amount of research on the effect of achievement goals has been correlational, administering questionnaires at the beginning of a semester and then observing the outcomes (i.e. via subsequent questionnaires and achievement measures, like final grades). However, experimental work has been done as well. These manipulations are usually instantiated by giving a set of instructions that explain the purpose or goal of some learning or test episode. Mastery manipulations usually stress that the work will be challenging, but that it can help one learn the material. Performance manipulations usually stress the evaluative nature of the task (i.e. "it will really show me what kids can do;" Elliott & Dweck, 1988) A meta-analysis (Utman, 1997) synthesized the results on experimentally-induced mastery and performance goals. It showed an advantage for mastery goals but mainly on complicated tasks, in older children, and for those working in groups. It should be noted that not every study found this advantage; performance goals were better than mastery in some of the studies included in the meta-analysis.<br />
<br />
==Links to Other Theories==<br />
Achievement goals have been linked to other theories as well. The strongest connection has been between achievement goals and implicit theories of intelligence (i.e. Blackwell, Trzesniewski, & Dweck, 2007). Implicit theories of intelligence are the beliefs people intuitively have about intelligence. An entity theory of intelligence holds that intelligence is set; a person has a certain "amount" of intelligence, and there is nothing else one can do about it. An incremental theory of intelligence holds that intelligence is malleable; a person's intelligence is a measure of his skill and effort, both of which can change. People who maintain an entity theory of intelligence are more likely to develop performance goals, as they would be more focused on demonstrations of existing ability, while those who hold incremental theories are more likely to develop mastery goals, since they are more focused on changing their skill levels, which are considered malleable. <br />
<br />
[[Self-efficacy]] is another theory of motivation which could play a role in achievement goals. [[Self-efficacy]] is the belief a person has about whether or not she can complete a given task. There is a role for this construct in achievement goal theory because achievement goals are fundamentally concerned with a person's competencies; if a person believes she can do something or not will influence a person's reactions to the environment. For example, two performance-approach oriented students may behave very similarly when they are both high in [[self-efficacy]], but very differently if one is low in [[self-efficacy]]. Self-efficacy has an influence on competence evaluations, which directly affects achievement goals. <br />
<br />
==Open Questions==<br />
Although achievement goals have been a major area of research over the past 30 years, much of that time has dealt with reconciling opposing viewpoints and findings. Today, a general consensus seems to exist in terms of the number of achievement goals (3 or 4, depending on the inclusion of mastery-avoidance), and some of their outcomes. However, there are still some open questions, some of which are particularly relevant to the PSLC:<br />
<br />
*Are some motivations more beneficial in certain situations? It seems like there could be a strong link between the type of learning outcomes sought (and the style of assessment used) and achievement goals. If a teacher is particularly interested in developing fluency, such as learning one's multiplication tables, or memorizing all of the state capitals, perhaps fostering performance-approach goals would be beneficial, as they seem to be linked to effort and surface strategies such as rehearsal, which are good for such tasks. However, if the goal is to develop a conceptual understanding that allows one to make good inferences about a complex topic, then mastery goals would seem to be more beneficial. This potential discrepancy between learning outcomes sought and achievement goals introduced could be a fruitful area of study, as well provide real value for optimizing learning environments.<br />
*Laboratory experiments have shown a benefit for mastery orientations (see Utman, 1997, for a review), but classroom studies have been less clear about those benefits, specifically in terms of achievement. This may also be due to a mismatch between the type of learning that occurs with mastery orientation and the type of assessments used. Could assessments of [[robust learning]] account for this? <br />
<br />
There are other open questions that may be less particularly relevant to the PSLC:<br />
<br />
*Many studies look at achievement goal orientations in exclusive terms, but students may in fact be adopting a variety of them. What would it mean for a student to be high in both mastery-approach and performance-approach? Or for someone to be very performance-approach oriented but particularly not mastery-avoidance oriented? Are the effects that have been reported in the extant literature additive? Or do they interact to create unique profiles?<br />
*Just how flexible are these orientations? Achievement goals were originally conceived of as a response to motivation theories that relied heavily on dispositional constructs, and were more heavily focused on “a more specific, contextual level of analysis” (Elliot, 2005). However, much of the more recent research has used a more dispositional assessment level of achievement goals. It is unclear exactly how predictive a dispositional assessment at the beginning of a semester is on how an individual will respond in any given situation. How much of the response will come from the disposition, and how much from the situation-specific aspects of the environment? <br />
*Do achievement goals produce fundamentally different outcomes in different age groups? For example, do performance-oriented college students have a different pattern of cognitions, strategies, and affect than performance-oriented middle-school students?<br />
<br />
<br />
==References==<br />
*Blackwell, L.S., Trzesniewski, K. H., & Dweck, C.S. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. ''Child Development, 78,'' 246-263.<br />
*Dweck, C.S., & Leggett, E.L. (1988). A social-cognitive approach to motivation and personality. ''Psychological Review, 95,'' 256-273. <br />
*Elliot, A.J. (1999). Approach and avoidance motivation and achievement goals. ''Educational Psychologist, 34,'' 149-169. <br />
*Elliot, A.J. (2005). A conceptual history of the achievement goal construct. In A.J. Elliot & Dweck C. S. (Eds.), ''Handbook of Competence and Motivation,'' (52-73). New York: Guilford Press.<br />
*Elliot, A.J., & McGregor, H. A. (2001). A 2 X 2 achievement goal framework. ''Journal of Personailty and Social Psychology, 80,'' 501-519.<br />
*Elliott, E.S., & Dweck, C.S. (1988). Goals: An approach to motivation and achievement. ''Journal of Personality and Social Psychology, 54,'' 5-12. <br />
*Kaplan, A., & Maehr, M.L. (2007). The contributions and prospects of goal orientation theory. ''Educational Psychology Review, 19,'' 141-184. <br />
*Harackiewicz, J. M., Barron, K. E., Pintrich, P. R., Elliot, A. J., & Thrash, T. M. (2002). Revision of achievement goal theory: Necessary and illuminating. ''Journal of Educational Psychology, 94,'' 638–645.<br />
*Midgley, C., Kaplan, A., & Middleton, M. (2001). Performance-approach goals; Good for what, for whom, under what circumstances, and at what cost? ''Journal of Educational Psychology, 93,'' 77-86. <br />
*Utman, C.H. (1997). Performance effects of motivational state: A meta-analysis. ''Personality and Social Psychology Review, 1,'' 170-182.<br />
<br />
==Appendix==<br />
Here is the 12-item measure used by Elliot & McGregor (2001). The first three items measure performance-approach(P.Ap), the next three mastery-avoidance(M.Av), then mastery-approach (M.Ap), and then performance-avoidance(P.Av).<br />
#It is important for me to do better than other students(P.Ap).<br />
#It is important for me to do well compared to others in this class(P.Ap).<br />
#My goal in in this class is to get a better grade than most of the other students(P.Ap).<br />
#I worry that I may not learn all that I possibly could in this class(M.Av).<br />
#Sometimes I'm afraid that I may not understand the content of this class as thoroughly as I'd like(M.Av).<br />
#I am often concerned that I may not learn all that there is to learn in this class(M.Av).<br />
#I want to learn as much as possible from this class(M.Ap).<br />
#It is important for me to understand the content of this course as thoroughly as possible(M.Ap).<br />
#I desire to completely master the material presented in this class(M.Ap).<br />
#I just want to avoid doing poorly in this class(P.Av).<br />
#My goal in this class is to avoid performing poorly(P.Av).<br />
#My fear of performing poorly in this class is often what motivates(P.Av).</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Achievement_Goals&diff=8876Achievement Goals2009-03-24T02:49:26Z<p>Dmbelenk: /* Approach/Avoidance Distinction */</p>
<hr />
<div>Achievement goals are the orientations for how and why people engage in achievement situations. They refer to the underlying aims a person has while engaging in an achievement setting, whether they are academic (such as in-class assignments or test preparation) or not (such as sports, work settings, etc.). These orientations guide interpretation of events in the achievement environment, and produce characteristic patterns of cognition, emotion and behaviors (Kaplan & Maehr, 2007). <br />
Early theory and research on achievement goals led to the proposal of two broad classes of goals, mastery and performance (i.e. Dweck & Leggett, 1988). Subsequent work contributed a differentiation between approach and avoidance orientations in addition to the mastery/performance split, creating a 2X2 framework (i.e. Elliot & McGregor, 2001). These four goals (mastery-approach, mastery-avoidance, performance-approach, and performance-avoidance) have been empirically tested and found to predict different patterns of outcomes, in terms of achievement, learning, cognitions, emotions, and behaviors, both in classroom and laboratory settings. <br />
<br />
==Achievement Goals==<br />
<br />
===Mastery Goals===<br />
Mastery goals (alternatively called learning goals, or task-focused goals) are concerned with the development of skill or competence. A mastery-oriented student is one whose primary goal is to improve her ability. Adoption of mastery goals has been found to be correlated with better self-regulation, deeper processing strategies, more positive affect, and increased topic interest (Harackiewicz et al., 2002; Kaplan & Maehr, 2007). However, mastery goals are less well correlated to measures of actual achievement, such as grades (Harackiewicz et al., 2002). <br />
<br />
===Performance Goals===<br />
Performance goals (alternatively called normative goals, or ego-focused goals) are concerned with demonstrations of skill. A performance-oriented student is one whose primary goal is to ensure an acceptable demonstration of her ability. Adoption of performance goals has been linked with a variety of effects, some positive and some negative. Performance goals are generally correlated with surface processing strategies, and negative affect and off-task behaviors following failures (Kaplan & Maehr, 2007; Dweck & Leggett, 1988). However, performance goals have also resulted in less clear links with achievement scores (such as grades), topic interest, and affect in general. Performance goals sometimes have a positive correlation with these outcomes, and sometimes have a negative correlation (see Midgley et al., 2001; and Harackiewicz et al., 2002, for a discussion on the consistency of findings).<br />
<br />
===Approach/Avoidance Distinction===<br />
To address the mixed findings regarding performance goals, Andrew Elliot and colleagues proposed incorporating a distinction between approach goals and avoidance goals (e.g. Elliot, 1999; Elliot & McGregor, 2001). This idea was inspired by earlier research on motivational drives, which included such a distinction. Approach in this case refers to an orientation towards seeking positive outcomes, while avoidance refers to preventing negative outcomes. These dimensions were originally only added to performance goals to help make sense of the conflicting findings, leading to a trichotomous framework of mastery, performance-approach, and performance-avoidance goals. Subsequent studies have used factor analysis and extended this distinction into a full 2 X 2 framework (Elliot & McGregor, 2001; see Appendix for the questionnaire). The four goals in this framework are:<br />
<br />
*Mastery-approach: This goal refers to wanting to develop skill or competence.<br />
*Mastery-avoidance: This goal refers to not wanting to lose competence or miss an opportunity to improve skill.<br />
*Performance-approach: This goal refers to wanting to demonstrate skill or competence.<br />
*Performance-avoidance: This goal refers to not wanting to demonstrate a lack of skill or competence. <br />
<br />
It is important to note that all of these goals are frameworks to understand the purposes a person has in engaging in achievement situations. They do not refer to the activities a person may engage in in service of these goals. For example, a performance-avoidance motivated student may still expend a lot of energy studying for a test. The important distinction is that this student's goal of not looking bad will lead him to engage, behave, think, and feel very differently than a student who studies with the goal of looking good, or one who is concerned with making sure he has mastered the material. <br />
<br />
Performance-avoidance goals generally lead to negative outcomes, while performance-approach seem to lead to positive outcomes in terms of achievement (Harackiewicz et al., 2002; but see Midgley et al., 2001 for a discussion of negative effects of performance-approach goals). Elliot (1999) was able to re-examine existing research to show that the prior mixed results for performance goals was due to this conflating of performance-approach and performance-avoidance goals. Most prior research had looked at mastery in exclusively approach terms, so the research that had shown a benefit for deeper processing, improved interest and affective response, and only small correlations with achievement generally applies to mastery-approach goals. Less is known about the effect of mastery-avoidance goals on cognition, emotion and behavior.<br />
<br />
==Experimental Manipulations==<br />
A fair amount of research on the effect of achievement goals has been correlational, administering questionnaires at the beginning of a semester and then observing the outcomes (i.e. via subsequent questionnaires and achievement measures, like final grades). However, experimental work has been done as well. These are usually instantiated by giving a set of instructions that explain the purpose of some learning or test episode. Mastery manipulations usually stress that the work will be challenging, but that it can help one learn the material. Performance manipulations usually stress the evaluative nature of the task (i.e. "it will really show me what kids can do;" Elliott & Dweck, 1988) A meta-analysis (Utman, 1997) synthesized the results on experimentally-induced mastery and performance goals. It showed an advantage for mastery goals but mainly on complicated tasks, in older children, and for those working in groups. It should be noted that not every study found this advantage; performance goals were better than mastery in some of the studies included in the meta-analysis. <br />
<br />
==Links to Other Theories==<br />
Achievement goals have been linked to other theories as well. The strongest connection has been between achievement goals and implicit theories of intelligence (i.e. Blackwell, Trzesniewski, & Dweck, 2007). Implicit theories of intelligence are the beliefs people intuitively have about intelligence. An entity theory of intelligence holds that intelligence is set; a person has a certain "amount" of intelligence, and there is nothing else one can do about it. An incremental theory of intelligence holds that intelligence is malleable; a person's intelligence is a measure of his skill and effort, both of which can change. People who maintain an entity theory of intelligence are more likely to develop performance goals, as they would be more focused on demonstrations of existing ability, while those who hold incremental theories are more likely to develop mastery goals, since they are more focused on changing their skill levels, which are considered malleable. <br />
<br />
[[Self-efficacy]] is another theory of motivation which could play a role in achievement goals. [[Self-efficacy]] is the belief a person has about whether or not she can complete a given task. There is a role for this construct in achievement goal theory because achievement goals are fundamentally concerned with a person's competencies; if a person believes she can do something or not will influence a person's reactions to the environment. For example, two performance-approach oriented students may behave very similarly when they are both high in [[self-efficacy]], but very differently if one is low in [[self-efficacy]]. Self-efficacy has an influence on competence evaluations, which directly affects achievement goals. <br />
<br />
==Open Questions==<br />
Although achievement goals have been a major area of research over the past 30 years, much of that time has dealt with reconciling opposing viewpoints and findings. Today, a general consensus seems to exist in terms of the number of achievement goals (3 or 4, depending on the inclusion of mastery-avoidance), and some of their outcomes. However, there are still some open questions, some of which are particularly relevant to the PSLC:<br />
<br />
*Are some motivations more beneficial in certain situations? It seems like there could be a strong link between the type of learning outcomes sought (and the style of assessment used) and achievement goals. If a teacher is particularly interested in developing fluency, such as learning one's multiplication tables, or memorizing all of the state capitals, perhaps fostering performance-approach goals would be beneficial, as they seem to be linked to effort and surface strategies such as rehearsal, which are good for such tasks. However, if the goal is to develop a conceptual understanding that allows one to make good inferences about a complex topic, then mastery goals would seem to be more beneficial. This potential discrepancy between learning outcomes sought and achievement goals introduced could be a fruitful area of study, as well provide real value for optimizing learning environments.<br />
*Laboratory experiments have shown a benefit for mastery orientations (see Utman, 1997, for a review), but classroom studies have been less clear about those benefits, specifically in terms of achievement. This may also be due to a mismatch between the type of learning that occurs with mastery orientation and the type of assessments used. Could assessments of [[robust learning]] account for this? <br />
<br />
There are other open questions that may be less particularly relevant to the PSLC:<br />
<br />
*Many studies look at achievement goal orientations in exclusive terms, but students may in fact be adopting a variety of them. What would it mean for a student to be high in both mastery-approach and performance-approach? Or for someone to be very performance-approach oriented but particularly not mastery-avoidance oriented? Are the effects that have been reported in the extant literature additive? Or do they interact to create unique profiles?<br />
*Just how flexible are these orientations? Achievement goals were originally conceived of as a response to motivation theories that relied heavily on dispositional constructs, and were more heavily focused on “a more specific, contextual level of analysis” (Elliot, 2005). However, much of the more recent research has used a more dispositional assessment level of achievement goals. It is unclear exactly how predictive a dispositional assessment at the beginning of a semester is on how an individual will respond in any given situation. How much of the response will come from the disposition, and how much from the situation-specific aspects of the environment? <br />
*Do achievement goals produce fundamentally different outcomes in different age groups? For example, do performance-oriented college students have a different pattern of cognitions, strategies, and affect than performance-oriented middle-school students?<br />
<br />
<br />
==References==<br />
*Blackwell, L.S., Trzesniewski, K. H., & Dweck, C.S. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. ''Child Development, 78,'' 246-263.<br />
*Dweck, C.S., & Leggett, E.L. (1988). A social-cognitive approach to motivation and personality. ''Psychological Review, 95,'' 256-273. <br />
*Elliot, A.J. (1999). Approach and avoidance motivation and achievement goals. ''Educational Psychologist, 34,'' 149-169. <br />
*Elliot, A.J. (2005). A conceptual history of the achievement goal construct. In A.J. Elliot & Dweck C. S. (Eds.), ''Handbook of Competence and Motivation,'' (52-73). New York: Guilford Press.<br />
*Elliot, A.J., & McGregor, H. A. (2001). A 2 X 2 achievement goal framework. ''Journal of Personailty and Social Psychology, 80,'' 501-519.<br />
*Elliott, E.S., & Dweck, C.S. (1988). Goals: An approach to motivation and achievement. ''Journal of Personality and Social Psychology, 54,'' 5-12. <br />
*Kaplan, A., & Maehr, M.L. (2007). The contributions and prospects of goal orientation theory. ''Educational Psychology Review, 19,'' 141-184. <br />
*Harackiewicz, J. M., Barron, K. E., Pintrich, P. R., Elliot, A. J., & Thrash, T. M. (2002). Revision of achievement goal theory: Necessary and illuminating. ''Journal of Educational Psychology, 94,'' 638–645.<br />
*Midgley, C., Kaplan, A., & Middleton, M. (2001). Performance-approach goals; Good for what, for whom, under what circumstances, and at what cost? ''Journal of Educational Psychology, 93,'' 77-86. <br />
*Utman, C.H. (1997). Performance effects of motivational state: A meta-analysis. ''Personality and Social Psychology Review, 1,'' 170-182.<br />
<br />
==Appendix==<br />
Here is the 12-item measure used by Elliot & McGregor (2001). The first three items measure performance-approach(P.Ap), the next three mastery-avoidance(M.Av), then mastery-approach (M.Ap), and then performance-avoidance(P.Av).<br />
#It is important for me to do better than other students(P.Ap).<br />
#It is important for me to do well compared to others in this class(P.Ap).<br />
#My goal in in this class is to get a better grade than most of the other students(P.Ap).<br />
#I worry that I may not learn all that I possibly could in this class(M.Av).<br />
#Sometimes I'm afraid that I may not understand the content of this class as thoroughly as I'd like(M.Av).<br />
#I am often concerned that I may not learn all that there is to learn in this class(M.Av).<br />
#I want to learn as much as possible from this class(M.Ap).<br />
#It is important for me to understand the content of this course as thoroughly as possible(M.Ap).<br />
#I desire to completely master the material presented in this class(M.Ap).<br />
#I just want to avoid doing poorly in this class(P.Av).<br />
#My goal in this class is to avoid performing poorly(P.Av).<br />
#My fear of performing poorly in this class is often what motivates(P.Av).</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Achievement_Goals&diff=8875Achievement Goals2009-03-24T02:45:26Z<p>Dmbelenk: /* References */</p>
<hr />
<div>Achievement goals are the orientations for how and why people engage in achievement situations. They refer to the underlying aims a person has while engaging in an achievement setting, whether they are academic (such as in-class assignments or test preparation) or not (such as sports, work settings, etc.). These orientations guide interpretation of events in the achievement environment, and produce characteristic patterns of cognition, emotion and behaviors (Kaplan & Maehr, 2007). <br />
Early theory and research on achievement goals led to the proposal of two broad classes of goals, mastery and performance (i.e. Dweck & Leggett, 1988). Subsequent work contributed a differentiation between approach and avoidance orientations in addition to the mastery/performance split, creating a 2X2 framework (i.e. Elliot & McGregor, 2001). These four goals (mastery-approach, mastery-avoidance, performance-approach, and performance-avoidance) have been empirically tested and found to predict different patterns of outcomes, in terms of achievement, learning, cognitions, emotions, and behaviors, both in classroom and laboratory settings. <br />
<br />
==Achievement Goals==<br />
<br />
===Mastery Goals===<br />
Mastery goals (alternatively called learning goals, or task-focused goals) are concerned with the development of skill or competence. A mastery-oriented student is one whose primary goal is to improve her ability. Adoption of mastery goals has been found to be correlated with better self-regulation, deeper processing strategies, more positive affect, and increased topic interest (Harackiewicz et al., 2002; Kaplan & Maehr, 2007). However, mastery goals are less well correlated to measures of actual achievement, such as grades (Harackiewicz et al., 2002). <br />
<br />
===Performance Goals===<br />
Performance goals (alternatively called normative goals, or ego-focused goals) are concerned with demonstrations of skill. A performance-oriented student is one whose primary goal is to ensure an acceptable demonstration of her ability. Adoption of performance goals has been linked with a variety of effects, some positive and some negative. Performance goals are generally correlated with surface processing strategies, and negative affect and off-task behaviors following failures (Kaplan & Maehr, 2007; Dweck & Leggett, 1988). However, performance goals have also resulted in less clear links with achievement scores (such as grades), topic interest, and affect in general. Performance goals sometimes have a positive correlation with these outcomes, and sometimes have a negative correlation (see Midgley et al., 2001; and Harackiewicz et al., 2002, for a discussion on the consistency of findings).<br />
<br />
===Approach/Avoidance Distinction===<br />
To address the mixed findings regarding performance goals, Andrew Elliot and colleagues proposed incorporating a distinction between approach goals and avoidance goals (e.g. Elliot, 1999; Elliot & McGregor, 2001). This idea was inspired by earlier research on motivational drives, which included such a distinction. Approach in this case refers to an orientation towards seeking positive outcomes, while avoidance refers to preventing negative outcomes. These dimensions were originally only added to performance goals to help make sense of the conflicting findings, leading to a trichotomous framework of mastery, performance-approach, and performance-avoidance goals. Subsequent studies have used factor analysis and extended this distinction into a full 2 X 2 framework (Elliot & McGregor, 2001; see Appendix for the questionnaire). The four goals in this framework are:<br />
<br />
*Mastery-approach: This goal refers to wanting to develop skill or competence.<br />
*Mastery-avoidance: This goal refers to not wanting to lose competence or miss an opportunity to improve skill.<br />
*Performance-approach: This goal refers to wanting to demonstrate skill or competence.<br />
*Performance-avoidance: This goal refers to not wanting to demonstrate a lack of skill or competence. <br />
<br />
It is important to note that all of these goals are frameworks to understand the purposes a person has in engaging in achievement situations. They do not refer to the activities a person may engage in in service of these goals. For example, a performance-avoidance motivated student may still expend a lot of energy studying for a test. The important distinction is that this student's goal of not looking bad will lead him to engage, behave, think, and feel very differently than a student who studies with the goal of looking good, or one who is concerned with making sure he has mastered the material. <br />
<br />
Performance-avoidance goals generally lead to negative outcomes, while performance-approach seem to lead to positive outcomes in terms of achievement (Harackiewicz et al., 2002). Elliot (1999) was able to re-examine existing research to show that the prior mixed results for performance goals was due to this conflating of performance-approach and performance-avoidance goals. Most prior research had looked at mastery in exclusively approach terms, so the research that had shown a benefit for deeper processing, improved interest and affective response, and only small correlations with achievement generally applies to mastery-approach goals. Less is known about the effect of mastery-avoidance goals on cognition, emotion and behavior. <br />
<br />
==Experimental Manipulations==<br />
A fair amount of research on the effect of achievement goals has been correlational, administering questionnaires at the beginning of a semester and then observing the outcomes (i.e. via subsequent questionnaires and achievement measures, like final grades). However, experimental work has been done as well. These are usually instantiated by giving a set of instructions that explain the purpose of some learning or test episode. Mastery manipulations usually stress that the work will be challenging, but that it can help one learn the material. Performance manipulations usually stress the evaluative nature of the task (i.e. "it will really show me what kids can do;" Elliott & Dweck, 1988) A meta-analysis (Utman, 1997) synthesized the results on experimentally-induced mastery and performance goals. It showed an advantage for mastery goals but mainly on complicated tasks, in older children, and for those working in groups. It should be noted that not every study found this advantage; performance goals were better than mastery in some of the studies included in the meta-analysis. <br />
<br />
==Links to Other Theories==<br />
Achievement goals have been linked to other theories as well. The strongest connection has been between achievement goals and implicit theories of intelligence (i.e. Blackwell, Trzesniewski, & Dweck, 2007). Implicit theories of intelligence are the beliefs people intuitively have about intelligence. An entity theory of intelligence holds that intelligence is set; a person has a certain "amount" of intelligence, and there is nothing else one can do about it. An incremental theory of intelligence holds that intelligence is malleable; a person's intelligence is a measure of his skill and effort, both of which can change. People who maintain an entity theory of intelligence are more likely to develop performance goals, as they would be more focused on demonstrations of existing ability, while those who hold incremental theories are more likely to develop mastery goals, since they are more focused on changing their skill levels, which are considered malleable. <br />
<br />
[[Self-efficacy]] is another theory of motivation which could play a role in achievement goals. [[Self-efficacy]] is the belief a person has about whether or not she can complete a given task. There is a role for this construct in achievement goal theory because achievement goals are fundamentally concerned with a person's competencies; if a person believes she can do something or not will influence a person's reactions to the environment. For example, two performance-approach oriented students may behave very similarly when they are both high in [[self-efficacy]], but very differently if one is low in [[self-efficacy]]. Self-efficacy has an influence on competence evaluations, which directly affects achievement goals. <br />
<br />
==Open Questions==<br />
Although achievement goals have been a major area of research over the past 30 years, much of that time has dealt with reconciling opposing viewpoints and findings. Today, a general consensus seems to exist in terms of the number of achievement goals (3 or 4, depending on the inclusion of mastery-avoidance), and some of their outcomes. However, there are still some open questions, some of which are particularly relevant to the PSLC:<br />
<br />
*Are some motivations more beneficial in certain situations? It seems like there could be a strong link between the type of learning outcomes sought (and the style of assessment used) and achievement goals. If a teacher is particularly interested in developing fluency, such as learning one's multiplication tables, or memorizing all of the state capitals, perhaps fostering performance-approach goals would be beneficial, as they seem to be linked to effort and surface strategies such as rehearsal, which are good for such tasks. However, if the goal is to develop a conceptual understanding that allows one to make good inferences about a complex topic, then mastery goals would seem to be more beneficial. This potential discrepancy between learning outcomes sought and achievement goals introduced could be a fruitful area of study, as well provide real value for optimizing learning environments.<br />
*Laboratory experiments have shown a benefit for mastery orientations (see Utman, 1997, for a review), but classroom studies have been less clear about those benefits, specifically in terms of achievement. This may also be due to a mismatch between the type of learning that occurs with mastery orientation and the type of assessments used. Could assessments of [[robust learning]] account for this? <br />
<br />
There are other open questions that may be less particularly relevant to the PSLC:<br />
<br />
*Many studies look at achievement goal orientations in exclusive terms, but students may in fact be adopting a variety of them. What would it mean for a student to be high in both mastery-approach and performance-approach? Or for someone to be very performance-approach oriented but particularly not mastery-avoidance oriented? Are the effects that have been reported in the extant literature additive? Or do they interact to create unique profiles?<br />
*Just how flexible are these orientations? Achievement goals were originally conceived of as a response to motivation theories that relied heavily on dispositional constructs, and were more heavily focused on “a more specific, contextual level of analysis” (Elliot, 2005). However, much of the more recent research has used a more dispositional assessment level of achievement goals. It is unclear exactly how predictive a dispositional assessment at the beginning of a semester is on how an individual will respond in any given situation. How much of the response will come from the disposition, and how much from the situation-specific aspects of the environment? <br />
*Do achievement goals produce fundamentally different outcomes in different age groups? For example, do performance-oriented college students have a different pattern of cognitions, strategies, and affect than performance-oriented middle-school students?<br />
<br />
<br />
==References==<br />
*Blackwell, L.S., Trzesniewski, K. H., & Dweck, C.S. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. ''Child Development, 78,'' 246-263.<br />
*Dweck, C.S., & Leggett, E.L. (1988). A social-cognitive approach to motivation and personality. ''Psychological Review, 95,'' 256-273. <br />
*Elliot, A.J. (1999). Approach and avoidance motivation and achievement goals. ''Educational Psychologist, 34,'' 149-169. <br />
*Elliot, A.J. (2005). A conceptual history of the achievement goal construct. In A.J. Elliot & Dweck C. S. (Eds.), ''Handbook of Competence and Motivation,'' (52-73). New York: Guilford Press.<br />
*Elliot, A.J., & McGregor, H. A. (2001). A 2 X 2 achievement goal framework. ''Journal of Personailty and Social Psychology, 80,'' 501-519.<br />
*Elliott, E.S., & Dweck, C.S. (1988). Goals: An approach to motivation and achievement. ''Journal of Personality and Social Psychology, 54,'' 5-12. <br />
*Kaplan, A., & Maehr, M.L. (2007). The contributions and prospects of goal orientation theory. ''Educational Psychology Review, 19,'' 141-184. <br />
*Harackiewicz, J. M., Barron, K. E., Pintrich, P. R., Elliot, A. J., & Thrash, T. M. (2002). Revision of achievement goal theory: Necessary and illuminating. ''Journal of Educational Psychology, 94,'' 638–645.<br />
*Midgley, C., Kaplan, A., & Middleton, M. (2001). Performance-approach goals; Good for what, for whom, under what circumstances, and at what cost? ''Journal of Educational Psychology, 93,'' 77-86. <br />
*Utman, C.H. (1997). Performance effects of motivational state: A meta-analysis. ''Personality and Social Psychology Review, 1,'' 170-182.<br />
<br />
==Appendix==<br />
Here is the 12-item measure used by Elliot & McGregor (2001). The first three items measure performance-approach(P.Ap), the next three mastery-avoidance(M.Av), then mastery-approach (M.Ap), and then performance-avoidance(P.Av).<br />
#It is important for me to do better than other students(P.Ap).<br />
#It is important for me to do well compared to others in this class(P.Ap).<br />
#My goal in in this class is to get a better grade than most of the other students(P.Ap).<br />
#I worry that I may not learn all that I possibly could in this class(M.Av).<br />
#Sometimes I'm afraid that I may not understand the content of this class as thoroughly as I'd like(M.Av).<br />
#I am often concerned that I may not learn all that there is to learn in this class(M.Av).<br />
#I want to learn as much as possible from this class(M.Ap).<br />
#It is important for me to understand the content of this course as thoroughly as possible(M.Ap).<br />
#I desire to completely master the material presented in this class(M.Ap).<br />
#I just want to avoid doing poorly in this class(P.Av).<br />
#My goal in this class is to avoid performing poorly(P.Av).<br />
#My fear of performing poorly in this class is often what motivates(P.Av).</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Achievement_Goals&diff=8874Achievement Goals2009-03-24T02:43:08Z<p>Dmbelenk: </p>
<hr />
<div>Achievement goals are the orientations for how and why people engage in achievement situations. They refer to the underlying aims a person has while engaging in an achievement setting, whether they are academic (such as in-class assignments or test preparation) or not (such as sports, work settings, etc.). These orientations guide interpretation of events in the achievement environment, and produce characteristic patterns of cognition, emotion and behaviors (Kaplan & Maehr, 2007). <br />
Early theory and research on achievement goals led to the proposal of two broad classes of goals, mastery and performance (i.e. Dweck & Leggett, 1988). Subsequent work contributed a differentiation between approach and avoidance orientations in addition to the mastery/performance split, creating a 2X2 framework (i.e. Elliot & McGregor, 2001). These four goals (mastery-approach, mastery-avoidance, performance-approach, and performance-avoidance) have been empirically tested and found to predict different patterns of outcomes, in terms of achievement, learning, cognitions, emotions, and behaviors, both in classroom and laboratory settings. <br />
<br />
==Achievement Goals==<br />
<br />
===Mastery Goals===<br />
Mastery goals (alternatively called learning goals, or task-focused goals) are concerned with the development of skill or competence. A mastery-oriented student is one whose primary goal is to improve her ability. Adoption of mastery goals has been found to be correlated with better self-regulation, deeper processing strategies, more positive affect, and increased topic interest (Harackiewicz et al., 2002; Kaplan & Maehr, 2007). However, mastery goals are less well correlated to measures of actual achievement, such as grades (Harackiewicz et al., 2002). <br />
<br />
===Performance Goals===<br />
Performance goals (alternatively called normative goals, or ego-focused goals) are concerned with demonstrations of skill. A performance-oriented student is one whose primary goal is to ensure an acceptable demonstration of her ability. Adoption of performance goals has been linked with a variety of effects, some positive and some negative. Performance goals are generally correlated with surface processing strategies, and negative affect and off-task behaviors following failures (Kaplan & Maehr, 2007; Dweck & Leggett, 1988). However, performance goals have also resulted in less clear links with achievement scores (such as grades), topic interest, and affect in general. Performance goals sometimes have a positive correlation with these outcomes, and sometimes have a negative correlation (see Midgley et al., 2001; and Harackiewicz et al., 2002, for a discussion on the consistency of findings).<br />
<br />
===Approach/Avoidance Distinction===<br />
To address the mixed findings regarding performance goals, Andrew Elliot and colleagues proposed incorporating a distinction between approach goals and avoidance goals (e.g. Elliot, 1999; Elliot & McGregor, 2001). This idea was inspired by earlier research on motivational drives, which included such a distinction. Approach in this case refers to an orientation towards seeking positive outcomes, while avoidance refers to preventing negative outcomes. These dimensions were originally only added to performance goals to help make sense of the conflicting findings, leading to a trichotomous framework of mastery, performance-approach, and performance-avoidance goals. Subsequent studies have used factor analysis and extended this distinction into a full 2 X 2 framework (Elliot & McGregor, 2001; see Appendix for the questionnaire). The four goals in this framework are:<br />
<br />
*Mastery-approach: This goal refers to wanting to develop skill or competence.<br />
*Mastery-avoidance: This goal refers to not wanting to lose competence or miss an opportunity to improve skill.<br />
*Performance-approach: This goal refers to wanting to demonstrate skill or competence.<br />
*Performance-avoidance: This goal refers to not wanting to demonstrate a lack of skill or competence. <br />
<br />
It is important to note that all of these goals are frameworks to understand the purposes a person has in engaging in achievement situations. They do not refer to the activities a person may engage in in service of these goals. For example, a performance-avoidance motivated student may still expend a lot of energy studying for a test. The important distinction is that this student's goal of not looking bad will lead him to engage, behave, think, and feel very differently than a student who studies with the goal of looking good, or one who is concerned with making sure he has mastered the material. <br />
<br />
Performance-avoidance goals generally lead to negative outcomes, while performance-approach seem to lead to positive outcomes in terms of achievement (Harackiewicz et al., 2002). Elliot (1999) was able to re-examine existing research to show that the prior mixed results for performance goals was due to this conflating of performance-approach and performance-avoidance goals. Most prior research had looked at mastery in exclusively approach terms, so the research that had shown a benefit for deeper processing, improved interest and affective response, and only small correlations with achievement generally applies to mastery-approach goals. Less is known about the effect of mastery-avoidance goals on cognition, emotion and behavior. <br />
<br />
==Experimental Manipulations==<br />
A fair amount of research on the effect of achievement goals has been correlational, administering questionnaires at the beginning of a semester and then observing the outcomes (i.e. via subsequent questionnaires and achievement measures, like final grades). However, experimental work has been done as well. These are usually instantiated by giving a set of instructions that explain the purpose of some learning or test episode. Mastery manipulations usually stress that the work will be challenging, but that it can help one learn the material. Performance manipulations usually stress the evaluative nature of the task (i.e. "it will really show me what kids can do;" Elliott & Dweck, 1988) A meta-analysis (Utman, 1997) synthesized the results on experimentally-induced mastery and performance goals. It showed an advantage for mastery goals but mainly on complicated tasks, in older children, and for those working in groups. It should be noted that not every study found this advantage; performance goals were better than mastery in some of the studies included in the meta-analysis. <br />
<br />
==Links to Other Theories==<br />
Achievement goals have been linked to other theories as well. The strongest connection has been between achievement goals and implicit theories of intelligence (i.e. Blackwell, Trzesniewski, & Dweck, 2007). Implicit theories of intelligence are the beliefs people intuitively have about intelligence. An entity theory of intelligence holds that intelligence is set; a person has a certain "amount" of intelligence, and there is nothing else one can do about it. An incremental theory of intelligence holds that intelligence is malleable; a person's intelligence is a measure of his skill and effort, both of which can change. People who maintain an entity theory of intelligence are more likely to develop performance goals, as they would be more focused on demonstrations of existing ability, while those who hold incremental theories are more likely to develop mastery goals, since they are more focused on changing their skill levels, which are considered malleable. <br />
<br />
[[Self-efficacy]] is another theory of motivation which could play a role in achievement goals. [[Self-efficacy]] is the belief a person has about whether or not she can complete a given task. There is a role for this construct in achievement goal theory because achievement goals are fundamentally concerned with a person's competencies; if a person believes she can do something or not will influence a person's reactions to the environment. For example, two performance-approach oriented students may behave very similarly when they are both high in [[self-efficacy]], but very differently if one is low in [[self-efficacy]]. Self-efficacy has an influence on competence evaluations, which directly affects achievement goals. <br />
<br />
==Open Questions==<br />
Although achievement goals have been a major area of research over the past 30 years, much of that time has dealt with reconciling opposing viewpoints and findings. Today, a general consensus seems to exist in terms of the number of achievement goals (3 or 4, depending on the inclusion of mastery-avoidance), and some of their outcomes. However, there are still some open questions, some of which are particularly relevant to the PSLC:<br />
<br />
*Are some motivations more beneficial in certain situations? It seems like there could be a strong link between the type of learning outcomes sought (and the style of assessment used) and achievement goals. If a teacher is particularly interested in developing fluency, such as learning one's multiplication tables, or memorizing all of the state capitals, perhaps fostering performance-approach goals would be beneficial, as they seem to be linked to effort and surface strategies such as rehearsal, which are good for such tasks. However, if the goal is to develop a conceptual understanding that allows one to make good inferences about a complex topic, then mastery goals would seem to be more beneficial. This potential discrepancy between learning outcomes sought and achievement goals introduced could be a fruitful area of study, as well provide real value for optimizing learning environments.<br />
*Laboratory experiments have shown a benefit for mastery orientations (see Utman, 1997, for a review), but classroom studies have been less clear about those benefits, specifically in terms of achievement. This may also be due to a mismatch between the type of learning that occurs with mastery orientation and the type of assessments used. Could assessments of [[robust learning]] account for this? <br />
<br />
There are other open questions that may be less particularly relevant to the PSLC:<br />
<br />
*Many studies look at achievement goal orientations in exclusive terms, but students may in fact be adopting a variety of them. What would it mean for a student to be high in both mastery-approach and performance-approach? Or for someone to be very performance-approach oriented but particularly not mastery-avoidance oriented? Are the effects that have been reported in the extant literature additive? Or do they interact to create unique profiles?<br />
*Just how flexible are these orientations? Achievement goals were originally conceived of as a response to motivation theories that relied heavily on dispositional constructs, and were more heavily focused on “a more specific, contextual level of analysis” (Elliot, 2005). However, much of the more recent research has used a more dispositional assessment level of achievement goals. It is unclear exactly how predictive a dispositional assessment at the beginning of a semester is on how an individual will respond in any given situation. How much of the response will come from the disposition, and how much from the situation-specific aspects of the environment? <br />
*Do achievement goals produce fundamentally different outcomes in different age groups? For example, do performance-oriented college students have a different pattern of cognitions, strategies, and affect than performance-oriented middle-school students?<br />
<br />
<br />
==References==<br />
*Blackwell, L.S., Trzesniewski, K. H., & Dweck, C.S. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. Child Development, 78, 246-263.<br />
*Dweck, C.S., & Leggett, E.L. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95, 256-273. <br />
*Elliot, A.J. (1999). Approach and avoidance motivation and achievement goals. Educational Psychologist, 34, 149-169. <br />
*Elliot, A.J. (2005). A conceptual history of the achievement goal construct. In A.J. Elliot & Dweck C. S. (Eds.), Handbook of Competence and Motivation, (52-73). New York: Guilford Press.<br />
*Elliot, A.J., & McGregor, H. A. (2001). A 2 X 2 achievement goal framework. Journal of Personailty and Social Psychology, 80, 501-519.<br />
*Elliott, E.S., & Dweck, C.S. (1988). Goals: An approach to motivation and achievement. Journal of Personality and Social Psychology, 54, 5-12. <br />
*Kaplan, A., & Maehr, M.L. (2007). The contributions and prospects of goal orientation theory. Educational Psychology Review, 19, 141-184. <br />
*Harackiewicz, J. M., Barron, K. E., Pintrich, P. R., Elliot, A. J., & Thrash, T. M. (2002). Revision of achievement goal theory: Necessary and illuminating. Journal of Educational Psychology, 94, 638–645.<br />
*Midgley, C., Kaplan, A., & Middleton, M. (2001). Performance-approach goals; Good for what, for whom, under what circumstances, and at what cost? Journal of Educational Psychology, 93, 77-86. <br />
*Utman, C.H. (1997). Performance effects of motivational state: A meta-analysis. Personality and Social Psychology Review, 1, 170-182.<br />
<br />
==Appendix==<br />
Here is the 12-item measure used by Elliot & McGregor (2001). The first three items measure performance-approach(P.Ap), the next three mastery-avoidance(M.Av), then mastery-approach (M.Ap), and then performance-avoidance(P.Av).<br />
#It is important for me to do better than other students(P.Ap).<br />
#It is important for me to do well compared to others in this class(P.Ap).<br />
#My goal in in this class is to get a better grade than most of the other students(P.Ap).<br />
#I worry that I may not learn all that I possibly could in this class(M.Av).<br />
#Sometimes I'm afraid that I may not understand the content of this class as thoroughly as I'd like(M.Av).<br />
#I am often concerned that I may not learn all that there is to learn in this class(M.Av).<br />
#I want to learn as much as possible from this class(M.Ap).<br />
#It is important for me to understand the content of this course as thoroughly as possible(M.Ap).<br />
#I desire to completely master the material presented in this class(M.Ap).<br />
#I just want to avoid doing poorly in this class(P.Av).<br />
#My goal in this class is to avoid performing poorly(P.Av).<br />
#My fear of performing poorly in this class is often what motivates(P.Av).</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Achievement_Goals&diff=8872Achievement Goals2009-03-23T23:40:04Z<p>Dmbelenk: </p>
<hr />
<div>Achievement goals are the orientations for how and why people engage in achievement situations. They refer to the underlying aims a person has while engaging in an achievement setting, whether they are academic (such as in-class assignments or test preparation) or not (such as sports, work settings, etc.). These orientations guide interpretation of events in the achievement environment, and produce characteristic patterns of cognition, emotion and behaviors (Kaplan & Maehr, 2007). <br />
Early theory and research on achievement goals led to the proposal of two broad classes of goals, mastery and performance (i.e. Dweck & Leggett, 1988). Subsequent work contributed a differentiation between approach and avoidance orientations in addition to the mastery/performance split, creating a 2X2 framework (i.e. Elliot & McGregor, 2001). These four goals (mastery-approach, mastery-avoidance, performance-approach, and performance-avoidance) have been empirically tested and found to predict different patterns of outcomes, in terms of achievement, learning, cognitions, emotions, and behaviors, both in classroom and laboratory settings. <br />
<br />
==Achievement Goals==<br />
<br />
===Mastery Goals===<br />
Mastery goals (alternatively called learning goals, or task-focused goals) are concerned with the development of skill or competence. A mastery-oriented student is one whose primary goal is to improve her ability. Adoption of mastery goals has been found to be correlated with better self-regulation, deeper processing strategies, more positive affect, and increased topic interest (Harackiewicz et al., 2002; Kaplan & Maehr, 2007). However, mastery goals are less well correlated to measures of actual achievement, such as grades (Harackiewicz et al., 2002). <br />
<br />
===Performance Goals===<br />
Performance goals (alternatively called normative goals, or ego-focused goals) are concerned with demonstrations of skill. A performance-oriented student is one whose primary goal is to ensure an acceptable demonstration of her ability. Adoption of performance goals has been linked with a variety of effects, some positive and some negative. Performance goals are generally correlated with surface processing strategies, and negative affect and off-task behaviors following failures (Kaplan & Maehr, 2007; Dweck & Leggett, 1988). However, performance goals have also resulted in less clear links with achievement scores (such as grades), topic interest, and affect in general. Performance goals sometimes have a positive correlation with these outcomes, and sometimes have a negative correlation (see Midgley et al., 2001; and Harackiewicz et al., 2002, for a discussion on the consistency of findings).<br />
<br />
===Approach/Avoidance Distinction===<br />
To address the mixed findings regarding performance goals, Andrew Elliot and colleagues proposed incorporating a distinction between approach goals and avoidance goals (e.g. Elliot, 1999; Elliot & McGregor, 2001). This idea was inspired by earlier research on motivational drives, which included such a distinction. Approach in this case refers to an orientation towards seeking positive outcomes, while avoidance refers to preventing negative outcomes. These dimensions were originally only added to performance goals to help make sense of the conflicting findings, leading to a trichotomous framework of mastery, performance-approach, and performance-avoidance goals. Subsequent studies have used factor analysis and extended this distinction into a full 2 X 2 framework (Elliot & McGregor, 2001). The four goals in this framework are:<br />
<br />
*Mastery-approach: This goal refers to wanting to develop skill or competence.<br />
*Mastery-avoidance: This goal refers to not wanting to lose competence or miss an opportunity to improve skill.<br />
*Performance-approach: This goal refers to wanting to demonstrate skill or competence.<br />
*Performance-avoidance: This goal refers to not wanting to demonstrate a lack of skill or competence. <br />
<br />
It is important to note that all of these goals are frameworks to understand the purposes a person has in engaging in achievement situations. They do not refer to the activities a person may engage in in service of these goals. For example, a performance-avoidance motivated student may still expend a lot of energy studying for a test. The important distinction is that this student's goal of not looking bad will lead him to engage, behave, think, and feel very differently than a student who studies with the goal of looking good, or one who is concerned with making sure he has mastered the material. <br />
<br />
Performance-avoidance goals generally lead to negative outcomes, while performance-approach seem to lead to positive outcomes in terms of achievement (Harackiewicz et al., 2002). Elliot was able to re-examine existing research to show that the prior mixed results for performance goals was due to this conflating of performance-approach and performance-avoidance goals(Elliot, 1999). Most prior research had looked at mastery in exclusively approach terms, so the research that had shown a benefit for deeper processing, improved interest and affective response, and only small correlations with achievement generally applies to mastery-approach goals. Less is known about the effect of mastery-avoidance goals on cognition, emotion and behavior. <br />
<br />
==Experimental Manipulations==<br />
A fair amount of research on the effect of achievement goals has been correlational, administering questionnaires at the beginning of a semester and then observing the outcomes (i.e. via subsequent questionnaires and achievement measures, like final grades). However, experimental work has been done as well. A meta-analysis (Utman, 1997) synthesized the results on experimentally-induced mastery and performance goals. It showed an advantage for mastery goals but mainly on complicated tasks, in older children, and for those working in groups. It should be noted that not every study found this advantage; performance goals were better than mastery in some of the studies included in the meta-analysis. <br />
<br />
==Links to Other Theories==<br />
Achievement goals have been linked to other theories as well. The strongest connection has been between achievement goals and implicit theories of intelligence (i.e. Blackwell, Trzesniewski, & Dweck, 2007). Implicit theories of intelligence are the beliefs people intuitively have about intelligence. An entity theory of intelligence holds that intelligence is set; a person has a certain "amount" of intelligence, and there is nothing else one can do about it. An incremental theory of intelligence holds that intelligence is malleable; a person's intelligence is a measure of his skill and effort, both of which can change. People who maintain an entity theory of intelligence are more likely to develop performance goals, as they would be more focused on demonstrations of existing ability, while those who hold incremental theories are more likely to develop mastery goals, since they are more focused on changing their skill levels, which are considered malleable. <br />
<br />
[[Self-efficacy]] is another theory of motivation which could play a role in achievement goals. [[Self-efficacy]] is the belief a person has about whether or not she can complete a given task. There is a role for this construct in achievement goal theory because achievement goals are fundamentally concerned with a person's competencies; if a person believes she can do something or not will influence a person's reactions to the environment. For example, two performance-approach oriented students may behave very similarly when they are both high in [[self-efficacy]], but very differently if one is low in [[self-efficacy]]. Self-efficacy has an influence on competence evaluations, which directly affects achievement goals. <br />
<br />
==Open Questions==<br />
Although achievement goals have been a major area of research over the past 30 years, much of that time has dealt with reconciling opposing viewpoints and findings. Today, a general consensus seems to exist in terms of the number of achievement goals (3 or 4, depending on the inclusion of mastery-avoidance), and some of their outcomes. However, there are still some open questions, some of which are particularly relevant to the PSLC:<br />
<br />
*Are some motivations more beneficial in certain situations? It seems like there could be a strong link between the type of learning outcomes sought (and the style of assessment used) and achievement goals. If a teacher is particularly interested in developing fluency, such as learning one's multiplication tables, or memorizing all of the state capitals, perhaps fostering performance-approach goals would be beneficial, as they seem to be linked to effort and surface strategies such as rehearsal, which are good for such tasks. However, if the goal is to develop a conceptual understanding that allows one to make good inferences about a complex topic, then mastery goals would seem to be more beneficial. This potential discrepancy between learning outcomes sought and achievement goals introduced could be a fruitful area of study, as well provide real value for optimizing learning environments.<br />
*Laboratory experiments have shown a benefit for mastery orientations (see Utman, 1997, for a review), but classroom studies have been less clear about those benefits, specifically in terms of achievement. This may also be due to a mismatch between the type of learning that occurs with mastery orientation and the type of assessments used. Could assessments of [[robust learning]] account for this? <br />
<br />
There are other open questions that may be less particularly relevant to the PSLC:<br />
<br />
*Many studies look at achievement goal orientations in exclusive terms, but students may in fact be adopting a variety of them. What would it mean for a student to be high in both mastery-approach and performance-approach? Or for someone to be very performance-approach oriented but particularly not mastery-avoidance oriented? Are the effects that have been reported in the extant literature additive? Or do they interact to create unique profiles?<br />
*Just how flexible are these orientations? Achievement goals were originally conceived of as a response to motivation theories that relied heavily on dispositional constructs, and were more heavily focused on “a more specific, contextual level of analysis” (Elliot, 2005). However, much of the more recent research has used a more dispositional assessment level of achievement goals. It is unclear exactly how predictive a dispositional assessment at the beginning of a semester is on how an individual will respond in any given situation. How much of the response will come from the disposition, and how much from the situation-specific aspects of the environment? <br />
*Do achievement goals produce fundamentally different outcomes in different age groups? For example, do performance-oriented college students have a different pattern of cognitions, strategies, and affect than performance-oriented middle-school students?<br />
<br />
<br />
==References==<br />
*Blackwell, L.S., Trzesniewski, K. H., & Dweck, C.S. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. Child Development, 78, 246-263.<br />
*Dweck, C.S., & Leggett, E.L. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95, 256-273. <br />
*Elliot, A.J. (1999). Approach and avoidance motivation and achievement goals. Educational Psychologist, 34, 149-169. <br />
*Elliot, A.J. (2005). A conceptual history of the achievement goal construct. In A.J. Elliot & Dweck C. S. (Eds.), Handbook of Competence and Motivation, (52-73). New York: Guilford Press.<br />
*Elliot, A.J., & McGregor, H. A. (2001). A 2 X 2 achievement goal framework. Journal of Personailty and Social Psychology, 80, 501-519. <br />
*Kaplan, A., & Maehr, M.L. (2007). The contributions and prospects of goal orientation theory. Educational Psychology Review, 19, 141-184. <br />
*Harackiewicz, J. M., Barron, K. E., Pintrich, P. R., Elliot, A. J., & Thrash, T. M. (2002). Revision of achievement goal theory: Necessary and illuminating. Journal of Educational Psychology, 94, 638–645.<br />
*Midgley, C., Kaplan, A., & Middleton, M. (2001). Performance-approach goals; Good for what, for whom, under what circumstances, and at what cost? Journal of Educational Psychology, 93, 77-86. <br />
*Utman, C.H. (1997). Performance effects of motivational state: A meta-analysis. Personality and Social Psychology Review, 1, 170-182.</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Achievement_Goals&diff=8871Achievement Goals2009-03-23T23:34:41Z<p>Dmbelenk: </p>
<hr />
<div>Achievement goals are the orientations for how and why people engage in achievement situations. They refer to the underlying aims a person has while engaging in an achievement setting, whether they are academic (such as in-class assignments or test preparation) or not (such as sports, work settings, etc.). These orientations guide interpretation of events in the achievement environment, and produce characteristic patterns of cognition, emotion and behaviors (Kaplan & Maehr, 2007). <br />
Early theory and research on achievement goals led to the proposal of two broad classes of goals, mastery and performance (i.e. Dweck & Leggett, 1988). Subsequent work contributed a differentiation between approach and avoidance orientations in addition to the mastery/performance split, creating a 2X2 framework (i.e. Elliot & McGregor, 2001). These four goals (mastery-approach, mastery-avoidance, performance-approach, and performance-avoidance) have been empirically tested and found to predict different patterns of outcomes, in terms of achievement, learning, cognitions, emotions, and behaviors, both in classroom and laboratory settings. <br />
<br />
==Achievement Goals==<br />
<br />
===Mastery Goals===<br />
Mastery goals (alternatively called learning goals, or task-focused goals) are concerned with the development of skill or competence. A mastery-oriented student is one whose primary goal is to improve her ability. Adoption of mastery goals has been found to be correlated with better self-regulation, deeper processing strategies, more positive affect, and increased topic interest (Harackiewicz et al., 2002; Kaplan & Maehr, 2007). However, mastery goals are less well correlated to measures of actual achievement, such as grades (Harackiewicz et al., 2002). <br />
<br />
===Performance Goals===<br />
Performance goals (alternatively called normative goals, or ego-focused goals) are concerned with demonstrations of skill. A performance-oriented student is one whose primary goal is to ensure an acceptable demonstration of her ability. Adoption of performance goals has been linked with a variety of effects, some positive and some negative. Performance goals are generally correlated with surface processing strategies, and negative affect and off-task behaviors following failures (Kaplan & Maehr, 2007; Dweck & Leggett, 1988). However, performance goals have also resulted in less clear links with achievement scores (such as grades), topic interest, and affect in general. Performance goals sometimes have a positive correlation with these outcomes, and sometimes have a negative correlation (see Midgley et al., 2001; and Harackiewicz et al., 2002, for a discussion on the consistency of findings).<br />
<br />
===Approach/Avoidance Distinction===<br />
To address the mixed findings regarding performance goals, Andrew Elliot and colleagues proposed incorporating a distinction between approach goals and avoidance goals (e.g. Elliot, 1999; Elliot & McGregor, 2001). This idea was inspired by earlier research on motivational drives, which included such a distinction. Approach in this case refers to an orientation towards seeking positive outcomes, while avoidance refers to preventing negative outcomes. These dimensions were originally only added to performance goals to help make sense of the conflicting findings, leading to a trichotomous framework of mastery, performance-approach, and performance-avoidance goals. Subsequent studies have used factor analysis and extended this distinction into a full 2 X 2 framework (Elliot & McGregor, 2001). The four goals in this framework are:<br />
<br />
*Mastery-approach: This goal refers to wanting to develop skill or competence.<br />
*Mastery-avoidance: This goal refers to not wanting to lose competence or miss an opportunity to improve skill.<br />
*Performance-approach: This goal refers to wanting to demonstrate skill or competence.<br />
*Performance-avoidance: This goal refers to not wanting to demonstrate a lack of skill or competence. <br />
<br />
It is important to note that all of these goals are frameworks to understand the purposes a person has in engaging in achievement situations. They do not refer to the activities a person may engage in in service of these goals. For example, a performance-avoidance motivated student may still expend a lot of energy studying for a test. The important distinction is that this student's goal of not looking bad will lead him to engage, behave, think, and feel very differently than a student who studies with the goal of looking good, or one who is concerned with making sure he has mastered the material. <br />
<br />
Performance-avoidance goals generally lead to negative outcomes, while performance-approach seem to lead to positive outcomes in terms of achievement (Harackiewicz et al., 2002). Elliot was able to re-examine existing research to show that the prior mixed results for performance goals was due to this conflating of performance-approach and performance-avoidance goals(Elliot, 1999). Most prior research had looked at mastery in exclusively approach terms, so the research that had shown a benefit for deeper processing, improved interest and affective response, and only small correlations with achievement generally applies to mastery-approach goals. Less is known about the effect of mastery-avoidance goals on cognition, emotion and behavior. <br />
<br />
==Experimental Manipulations==<br />
A fair amount of research on the effect of achievement goals has been correlational, administering questionnaires at the beginning of a semester and then observing the outcomes (i.e. via subsequent questionnaires and achievement measures, like final grades). However, experimental work has been done as well. A meta-analysis (Utman, 1997) synthesized the results on experimentally-induced mastery and performance goals. It showed an advantage for mastery goals but mainly on complicated tasks, in older children, and for those working in groups. It should be noted that not every study found this advantage; performance goals were better than mastery in some of the studies included in the meta-analysis. <br />
<br />
==Links to Other Theories==<br />
Achievement goals have been linked to other theories as well. The strongest connection has been between achievement goals and implicit theories of intelligence (i.e. Blackwell, Trzesniewski, & Dweck, 2007). Implicit theories of intelligence are the beliefs people intuitively have about intelligence. An entity theory of intelligence holds that intelligence is set; a person has a certain "amount" of intelligence, and there is nothing else one can do about it. An incremental theory of intelligence holds that intelligence is malleable; a person's intelligence is a measure of his skill and effort, both of which can change. People who maintain an entity theory of intelligence are more likely to develop performance goals, as they would be more focused on demonstrations of existing ability, while those who hold incremental theories are more likely to develop mastery goals, since they are more focused on changing their skill levels, which are considered malleable. <br />
<br />
Self-efficacy is another theory of motivation which could play a role in achievement goals. Self-efficacy is the belief a person has about whether or not she can complete a given task. There is a role for this construct in achievement goal theory because achievement goals are fundamentally concerned with a person's competencies; if a person believes she can do something or not will influence a person's reactions to the environment. For example, two performance-approach oriented students may behave very similarly when they are both high in self-efficacy, but very differently if one is low in self-efficacy. Self-efficacy has an influence on competence evaluations, which directly affects achievement goals. <br />
<br />
==Open Questions==<br />
Although achievement goals have been a major area of research over the past 30 years, much of that time has dealt with reconciling opposing viewpoints and findings. Today, a general consensus seems to exist in terms of the number of achievement goals (3 or 4, depending on the inclusion of mastery-avoidance), and some of their outcomes. However, there are still some open questions, some of which are particularly relevant to the PSLC:<br />
<br />
*Are some motivations more beneficial in certain situations? It seems like there could be a strong link between the type of learning outcomes sought (and the style of assessment used) and achievement goals. If a teacher is particularly interested in developing fluency, such as learning one's multiplication tables, or memorizing all of the state capitals, perhaps fostering performance-approach goals would be beneficial, as they seem to be linked to effort and surface strategies such as rehearsal, which are good for such tasks. However, if the goal is to develop a conceptual understanding that allows one to make good inferences about a complex topic, then mastery goals would seem to be more beneficial. This potential discrepancy between learning outcomes sought and achievement goals introduced could be a fruitful area of study, as well provide real value for optimizing learning environments.<br />
*Laboratory experiments have shown a benefit for mastery orientations (see Utman, 1997, for a review), but classroom studies have been less clear about those benefits, specifically in terms of achievement. This may also be due to a mismatch between the type of learning that occurs with mastery orientation and the type of assessments used. Could assessments of [[robust learning]] account for this? <br />
<br />
There are other open questions that may be less particularly relevant to the PSLC:<br />
<br />
*Many studies look at achievement goal orientations in exclusive terms, but students may in fact be adopting a variety of them. What would it mean for a student to be high in both mastery-approach and performance-approach? Or for someone to be very performance-approach oriented but particularly not mastery-avoidance oriented? Are the effects that have been reported in the extant literature additive? Or do they interact to create unique profiles?<br />
*Just how flexible are these orientations? Achievement goals were originally conceived of as a response to motivation theories that relied heavily on dispositional constructs, and were more heavily focused on “a more specific, contextual level of analysis” (Elliot, 2005). However, much of the more recent research has used a more dispositional assessment level of achievement goals. It is unclear exactly how predictive a dispositional assessment at the beginning of a semester is on how an individual will respond in any given situation. How much of the response will come from the disposition, and how much from the situation-specific aspects of the environment? <br />
*Do achievement goals produce fundamentally different outcomes in different age groups? For example, do performance-oriented college students have a different pattern of cognitions, strategies, and affect than performance-oriented middle-school students?<br />
<br />
<br />
==References==<br />
*Blackwell, L.S., Trzesniewski, K. H., & Dweck, C.S. (2007). Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. Child Development, 78, 246-263.<br />
*Dweck, C.S., & Leggett, E.L. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95, 256-273. <br />
*Elliot, A.J. (1999). Approach and avoidance motivation and achievement goals. Educational Psychologist, 34, 149-169. <br />
*Elliot, A.J. (2005). A conceptual history of the achievement goal construct. In A.J. Elliot & Dweck C. S. (Eds.), Handbook of Competence and Motivation, (52-73). New York: Guilford Press.<br />
*Elliot, A.J., & McGregor, H. A. (2001). A 2 X 2 achievement goal framework. Journal of Personailty and Social Psychology, 80, 501-519. <br />
*Kaplan, A., & Maehr, M.L. (2007). The contributions and prospects of goal orientation theory. Educational Psychology Review, 19, 141-184. <br />
*Harackiewicz, J. M., Barron, K. E., Pintrich, P. R., Elliot, A. J., & Thrash, T. M. (2002). Revision of achievement goal theory: Necessary and illuminating. Journal of Educational Psychology, 94, 638–645.<br />
*Midgley, C., Kaplan, A., & Middleton, M. (2001). Performance-approach goals; Good for what, for whom, under what circumstances, and at what cost? Journal of Educational Psychology, 93, 77-86. <br />
*Utman, C.H. (1997). Performance effects of motivational state: A meta-analysis. Personality and Social Psychology Review, 1, 170-182.</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Achievement_Goals&diff=8866Achievement Goals2009-03-21T20:31:52Z<p>Dmbelenk: </p>
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<div>WORK IN PROGRESS -- THIS PAGE IS STILL BEING CREATED FOR A CLASS PROJECT. PLEASE DO NOT EDIT.<br />
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<br />
Achievement goals are the orientations for how and why people engage in achievement situations. They refer to the underlying purposes of engagement in the scenario. These orientations guide interpretation of events in an achievement environment, and produce characteristic patterns of cognition, emotion and behaviors (Kaplan & Maehr, 2007). <br />
<br />
<br />
==Mastery and Performance Goals==<br />
Early theory and research on achievement goals led to the proposal of two broad classes of goals, mastery-oriented and performance-oriented. <br />
<br />
===Mastery Goals===<br />
Mastery goals (alternatively called Learning goals, or task-focused goals) are concerned with the development of skill. A mastery-oriented student is one whose primary goal is to improve her ability. Adoption of mastery goals has been found to be correlated with better self-regulation, deeper processing strategies, more positive affect, and increased topic interest (WHAT CITATION TO COVER ALL?). However, mastery goals are less well correlated to measures of actual achievement, such as grades (Harackiewicz et al., 2002). <br />
<br />
===Performance Goals===<br />
Performance goals (alternatively called normative goals, or ego-focused goals) are concerned with demonstrations of skill. A performance-oriented student is one whose primary goal is to demonstrate her ability. Adoption of performance goals has been linked with a variety of effects, some positive and some negative. Performance goals are generally correlated with surface processing strategies, and negative affect and off-task behaviors following failures. However, performance goals have also resulted in less clear links with achievement scores (such as grades), topic interest, and affect in general. Performance goals sometimes have a positive correlation with these outcomes, and sometimes have a negative correlation.<br />
<br />
===Approach/Avoidance Distinction===<br />
To address the mixed findings regarding performance goals, Andrew Elliot and colleagues proposed incorporating a distinction between approach goals and avoidance goals (e.g. Elliot, 1999; Elliot & McGregor, 2001). This idea was inspired by earlier research on motivational drives, which included such a distinction. Approach in this case refers to an orientation towards seeking positive outcomes, while avoidance refers to preventing negative outcomes. These dimensions were originally only added to performance goals to help make sense of the conflicting findings, leading to a trichotomous framework of mastery, performance-approach, and performance-avoidance goals. Subsequent studies have used factor analysis and extended this distinction into a full 2 X 2 framework. The four goals in this framework are:<br />
<br />
*Mastery-approach: This goal refers to wanting to develop skill or competence.<br />
*Mastery-avoidance: This goal refers to not wanting to lose skill or miss an opportunity to improve skill.<br />
*Performance-approach: This goal refers to wanting to demonstrate skill or competence.<br />
*Performance-avoidance: This goal refers to not wanting to demonstrate a lack of skill or competence. <br />
<br />
It is important to note that all of these goals are framework to understand the purposes a person has in engaging in achievement situations. They do not refer to the activities a person may engage in in service of these goals. For example, a performance-avoidance motivated student may still expend a lot of energy studying for a test. The important dinstinction is that this student's goal of not looking bad may lead him to engage, behave, think, and feel very differently than a student who studies with the goal of looking good, or one who is concerned with making sure he has mastered the material. <br />
<br />
Performance-avoidance goals generally lead to negative outcomes, while performance-approach seem to lead to positive outcomes in terms of achievement. Most prior research had looked at mastery in exclusively approach terms, so the research that had shown a benefit for deeper processing, improved interest and affective response, and only small correlations with achievement generally applies to mastery-approach goals. Less is known about the effect of mastery-avoidance goals on cognition, emotion and behavior. <br />
<br />
==Experimental Manipulations==<br />
A fair amount of research on the effect of achievement goals has been correlational, administering questionnaires at the beginning of a semester and then observed the outcomes (i.e. via subsequent questionnaires and achievement measures, like final grades). However, experimental work has been done as well. A meta-analysis (Utman, 1997) synthesized the results on experimentally induced mastery and performance goals. It showed an advantage for mastery goals on complicated tasks, in older children, and for those working in groups. It should be noted that not every study found this advantage; performance goals were better than mastery in some of studies included in the meta-analysis. <br />
<br />
==Links to Other Theories==<br />
Achievement goals have been linked to other theories as well. The strongest connection has been between achievement goals and implicit theories of intelligence (i.e. Blackwell, Trzesniewski, & Dweck, 2007). Implicit theories of intelligence are the beliefs people intuitively have about intelligence. An entity theory of intelligence holds that intelligence is set; a person can have a certain "amount" of intelligence, and there is nothing else one can do about it. An incremental theory of intelligence holds that intelligence is malleable; a person's intelligence is a measure of his skill and effort, both of which can change. People who maintain an entity theory of intelligence are more likely to develop performance goals, while those who hold incremental theories are more likley to develop mastery goals. <br />
<br />
Self-efficacy is another theory of motivation which could play a role in achievement goals. Self-efficacy is the belief a person has about whether or not she can complete a given task. There is a role for this construct in achievement goal theory because achievement goals are fundamentally concerned with a person's competencies; if a person believes she can do something or not will influence a person's reactions to the environment. For example, two performance-approach oriented students may behave very similarly when they are both high in self-efficacy, but very differently if one is low in self-efficacy. <br />
<br />
==Open Questions==<br />
Although achievement goals have been a major area of research over the past 30 years, much of that time has dealt with reconciling opposing viewpoints and findings. Today, a general consensus seems to exist in terms of the number of achievement goals (3 or 4, depending on the inclusion of mastery-avoidance), and some of their outcomes. However, there are still some open questions, some of which are particularly relevant to the PSLC:<br />
<br />
*Are some motivations more beneficial in certain situations? It seems like there could be a strong link between the type of learning outcomes sought (and the style of assessment used) and achievement goals. If a teacher is particularly interested in developing fluency, such as learning one's multiplication tables, or memorizing all of the state capital's, perhaps fostering performance-approach goals would be beneficial, as they seem to be linked to effort and surface strategies such as rehearsal, which are good for such tasks. However, if the goal is to develop a conceptual understanding that allows one to make good inferences about a complex topic, then mastery goals would seem to be more beneficial. This potential discrepancy between learning outcomes sought and achievement goals introduced could be a fruitful area of study, as well provide real value for optimizing learning environments.<br />
*Laboratory experiments have shown a benefit for mastery orientations (see Utman, 1997, for a review), but classroom studies have been less clear about those benefits, specifically in terms of achievement. This may also be due to a mismatch between the type of learning that occurs with mastery orientation and the type of assessments used. Could assessments of robust learning account for this? <br />
<br />
There are other open questions that may be less particularly relevant to the PSLC:<br />
<br />
*Most of these studies look at achievement goal orientations in exclusive terms, but students may in fact be adopting a variety of them. What would it mean for a student to be high in both mastery-approach and performance-approach? Or for someone to be very performance-approach oriented but particularly not mastery-avoidance oriented? Are the effects that have been reported in the extant literature additive? Or do they interact to create unique profiles?<br />
*Just how flexible are these orientations? How much is state, and how much is more like trait? (EXPAND)<br />
*Do achievement goals produce fundamentally different outcomes in different age groups? For example, do performance-oriented college students have a different pattern of cognitions, strategies, and affect than performance-oriented middle schoolers?</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Achievement_Goals&diff=8865Achievement Goals2009-03-20T17:47:50Z<p>Dmbelenk: </p>
<hr />
<div>WORK IN PROGRESS -- THIS PAGE IS STILL BEING CREATED FOR A CLASS PROJECT. PLEASE DO NOT EDIT.<br />
<br />
----<br />
<br />
Achievement goals are the orientations for how and why people engage in achievement situations. They refer to the underlying purposes of engagement in the scenario. These orientations guide interpretation of events in an achievement environment, and produce characteristic patterns of cognition, emotion and behaviors (Kaplan & Maehr, 2007). <br />
<br />
<br />
==Mastery and Performance Goals==<br />
Early theory and research on achievement goals led to the proposal of two broad classes of goals, mastery-oriented and performance-oriented. <br />
<br />
===Mastery Goals===<br />
Mastery goals (alternatively called Learning goals, or task-focused goals) are concerned with the development of skill. A mastery-oriented student is one whose primary goal is to improve her ability. Adoption of mastery goals has been found to be correlated with better self-regulation, deeper processing strategies, more positive affect, and increased topic interest (What citation to cover all?). However, mastery goals are less well correlated to measures of actual achievement, such as grades (Harackiewicz et al., 2002). <br />
===Performance Goals===<br />
Performance goals (alternatively called normative goals, or ego-focused goals) are concerned with demonstrations of skill. A performance-oriented student is one whose primary goal is to demonstrate her ability. Adoption of performance goals has been linked with a variety of effects, some positive and some negative. Performance goals are generally correlated with surface processing, and negative affect and off-task behaviors following failures <br />
<br />
there has also been much variability across studies.<br />
<br />
==Approach/Avoidance Distinction==<br />
<br />
==Experimental Manipulations==<br />
<br />
==Links to Other Theories==<br />
<br />
==Open Questions==</div>Dmbelenkhttps://learnlab.org/wiki/index.php?title=Achievement_Goals&diff=8864Achievement Goals2009-03-19T23:41:01Z<p>Dmbelenk: New page: WORK IN PROGRESS -- THIS PAGE IS STILL BEING CREATED FOR A CLASS PROJECT. PLEASE DO NOT EDIT. ---- Achievement goals theory addresses the role that a student's purpose in an achievement ...</p>
<hr />
<div>WORK IN PROGRESS -- THIS PAGE IS STILL BEING CREATED FOR A CLASS PROJECT. PLEASE DO NOT EDIT.<br />
<br />
----<br />
<br />
Achievement goals theory addresses the role that a student's purpose in an achievement situation has on their cognition, affect, and behavior. <br />
<br />
==Mastery Goals==<br />
<br />
<br />
==Performance Goals==<br />
<br />
==Approach/Avoidance Distinction==<br />
<br />
==Experimental Manipulations==<br />
<br />
==Links to Other Theories==<br />
<br />
==Open Questions==</div>Dmbelenk