Theory Wiki - User contributions [en]

Prompted Self-explanation

2011-07-06T15:19:53Z

Turadg: remove spam

Self-explaining is defined as a "content-relevant articulation uttered by the student after reading a line of text" (Chi, 2000; p. 165) or after studying a step in a worked-out example. A self-explanation may contain a meta-cognitive statement and/or a self-explanation inference.
* A meta-cognitive statement is an assessment, made by the student, of his or her own current understanding of the line of text or example step.
* A self-explanation inference is "an identified pieced of knowledge generated...that states something beyond what the sentence explicitly said" (Chi, 2000; p. 165).

Prompting is defined as an external cue that is intended to elicit the activity of self-explaining. Prompts are typically generated by a person, tutoring system, or a verbal reminder embedded in the learning material.

See also [[prompted self-explanation hypothesis]].

=== Examples ===

Here are the instructions to self-explain, taken from Chi et al. (1994):

"We would like you to read each sentence out loud and then explain what it means to you. That is, what 
new information does each line provide for you, how does it relate to what you've already read, does it give 
you a new insight into your understanding of how the circulatory system works, or does it raise a question 
in your mind. Tell us whatever is going through your mind–even if it seems unimportant." 

These prompts were reworded to be used in Hausmann & VanLehn (2007):

* What new information does each step provide for you?
* How does it relate to what you've already seen?
* Does it give you a new insight into your understanding of how to solve the problems?
* Does it raise a question in your mind?

These prompts were then included as text, just below a worked-out example. The example was presented as a video taken of the Andes interface, with a voice-over narration describing the user-interface actions (see Table below). In this example, the student is learning how to solve the following problem:

<Blockquote>A charged particle is in a region where there is an electric field E of magnitude 
14.3 V/m at an angle of 22 degrees above the positive x-axis. If the charge on the particle 
is -7.9 C, find the magnitude of the force on the particle P due to the electric field E.</Blockquote>

 

{| cellspacing="0" cellpadding="5" border="1"
|+ '''An example of prompting for self-explanining'''
|-
| style="border-bottom: 3px solid grey;" |
    Now that all the given information has been entered, we need to apply our knowledge of physics to solve the problem. 

    One way to start is to ask ourselves, “What quantity is the problem seeking?” In this case, the answer is the magnitude of the force on the particle due to the electric field. 

    We know that there is an electric field. If there is an electric field, and there is a charged particle located in that region, then we can infer that there is an electric force on the particle. The direction of the electric force is in the opposite direction as the electric field because the charge on the particle is negative.

    We use the Force tool from the vector tool bar to draw the electric force. This brings up a dialog box. The force is on the particle and it is due to some unspecified source. We do know, however, that the type of force is electric, so we choose “electric” from the pull-down menu. For the orientation, we need to add 180 degrees to 22 degrees to get a force that is in a direction that is opposite of the direction of the electric field. Therefore we put 202 degrees. Finally, we use “Fe” to designate this as an electric force.

<center>[ PROMPT ]</center>

    Now that the direction of the electric force has been indicated, we can work on finding the magnitude. We must choose a principle that relates the magnitude of the electric force to the strength of the electric field, and the charge on the particle. The definition of an electric field is only equation that relates these three variables. We write this equation, in the equation window.

<center>[ PROMPT ]</center>

|}
Note. PROMPT = "Please begin your self-explanation."

== References ==
Chi, M. T. H. (2000). Self-explaining: The dual processes of generating and repairing mental models. In R. Glaser (Ed.), ''Advances in Instructional Psychology'' (pp. 161-238). Mahwah, NJ: Erlbaum. [http://www.public.asu.edu/~mtchi/papers/advances.pdf]

Chi, M. T. H., DeLeeuw, N., Chiu, M.-H., & LaVancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18, 439-477. [http://www.pitt.edu/~chi/papers/ChiBassokLewisReimannGlaser.pdf]

Hausmann, R. G. M., & VanLehn, K. (2007). Explaining self-explaining: A contrast between content and generation. In R. Luckin, K. R. Koedinger & J. Greer (Eds.), Artificial intelligence in education: Building technology rich learning contexts that work (Vol. 158, pp. 417-424). Amsterdam: IOS Press. [http://learnlab.org/uploads/mypslc/publications/hausmannvanlehn2007_final.pdf]

[[Category:Glossary]]
[[Category:Independent Variables]]

PSLC GradStudents

2010-09-21T18:35:25Z

Turadg: added Turadg

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.

== Announcements==

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.

* 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!

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.

3) Ultimate Block Party in Central Park, NY.

* 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.)

* How to sign up: E-mail Michael Bett at mbett@cs.cmu.edu if you are interested.

4) PSLC Graduate Student Meetings are scheduled for the following days and will begin at noon.

* Monday, September 20 in 408 LRDC - topic: grad student wiki pages
* Monday, October 18 at CMU (location tba) - topic what is the PSLC and why should you care
* Monday, November 15 in 408 LRDC - topic ?
* Monday, December 6 at CMU topic ?

== Meeting Notes==

== FAQs==

'''1. What does it take to be a PSLC grad student?'''

Well, there are basically three ways you can be considered a PSLC grad student.

a. You work on a project that receives funding from the PSLC.

b. Your advisor or collaborator receives funding from the PSLC and asks you to be involved.

c. You want to be a PSLC grad student.

'''2. What types of opportunities does the PSLC have for a grad student like me?'''

There are a variety of different levels of involvement and types of activities that the PSLC offers.

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.

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.

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.

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.

'''3. What is expected of me as a PSLC grad student?'''

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.

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.

'''How do I find out about upcoming talks/meetings/events?'''

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.

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.

4. '''I already consider myself a PSLC grad, and want to be included on this page! What do I have to do?'''

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!

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:

<pre>
|-
| Name || University || Advisor || e-mail address || Bio || Personal Webpage || Link to PSLC project page [Project page URL Project page title]
</pre>

and paste it into the appropriate place on the table. With your own information, of course.

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.

5. '''But that's such a pain! Isn't there an easier way?!'''

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.

== Who are the PSLC grads? ==

{| border=1 cellspacing="0" cellpadding="5" style="text-align: left;"
|-
! Grad Student Name
! University/Department
! Advisor
! E-mail
! Bio
! Personal Webpage
! PSLC Projects
|-
| 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]
|-
| 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]
|-
| 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]
|-
| 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]
|-
| 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] ||
|}

== Science of Learning Relevant Courses ==
The PIER program offers three courses -- see the [http://www.cmu.edu/pier PIER Web page]

See also the courses taught be any of the PSLC faculty.

(Please add the names of relevant courses and web pointers if possible!)

<pre>
05832 / 05432 Cognitive Modeling & Intelligent Tutoring Systems
3:00pm-4:20pm, Tuesdays and Thursdays, Fall 2010
Room 3002, Newell-Simon Hall, Carnegie Mellon University
9 units
Dr. Vincent Aleven, aleven@cs.cmu.edu
</pre>

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.

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.

Worked examples

2008-05-21T21:54:03Z

Turadg: added a few more citations

Worked examples are a kind of [[example]] involving step-by-step solutions to problems typically presented in textual, graphical, video, or face-to-face format. Worked examples sometimes provide explanations of each step and sometimes withhold them so as to encourage student [[self-explanation]].

A worked example is a problem plus the [[step]]s leading up to its solution. For instance, if the problem is "Solve 12+2*x=15 for x" then one worked example is:

In order to solve 12+2*x=15 for x, we write
2*x = 15-12
2*x = 3
x = 3/2
x = 1.5

There are 4 steps in this worked example solution.

A large body of literature, much due to John Sweller (see relevant references below) and his [[cognitive load]] theory, has investigated the benefits of interleaving worked examples with problem-solving practice. Such interleaving seems to provide a good balance of [[assistance]] between assistance-giving examples and assistance-withholding problems.

A worked example is sometimes called a "model", particularly when presented by expert in face-to-face or video format. Such a demonstration is the first step in the model-scaffold-face approach recommended by Collins et al. (1989).

For illustrative studies see the [[Does learning from worked-out examples improve tutored problem solving? | Renkl et al. study]] of faded worked-out examples in geometry and the [[McLaren_et_al_-_Studying_the_Learning_Effect_of_Personalization_and_Worked_Examples_in_the_Solving_of_Stoich_Problems | McLaren et al. study]] of interleaved worked examples in Chemistry. A number of other studies involving manipulations in the distribution of, presentation of, or supporting instruction around worked examples can be found in the [[Coordinative Learning]] and [[Interactive Communication]] clusters.

=== Sample References ===

* Collins, A., Brown, J. S., & Newman, S. E. (1989). Cognitive apprenticeship: Teaching the craft of reading, writing and mathematics. In L. B. Resnick (Ed.), ''Knowing, learning and instruction: Essays in honor of Robert Glaser'' (pp. 453-494). Hillsdale, NJ: Lawrence Erlbaum Associates.
* Hilbert, T., Schworm, S., & Renkl, A. (2004). Learning from worked-out examples: The transition from instructional explanations to self-explanation prompts. In P. Gerjets, J. Elen, R. Joiner, & P. Kirschner (Eds.), ''Instructional design for effective and enjoyable computer-supported learning'' (pp. 184-192). Tübingen: Knowledge Media Research Center.
* Schworm, S., & Renkl, A. (2006). Computer-supported example-based learning: When instructional explanations reduce self-explanations. ''Computers & Education, 46'', 426-445
* Schworm, S. & Renkl, A. (2002). Learning by solved example problems: Instructional explanations reduce self-explanation activity. In W. D. Gray & C. D. Schunn (Eds.), ''Proceeding of the 24th Annual Conference of the Cognitive Science Society'' (pp.816-821). Mahwah, NJ: Erlbaum
* Sweller, J. (1999). ''Instructional design in technical areas.'' Australian Council for Education Press.
* Sweller, J., & Cooper, G. A. (1985). The use of worked examples as a substitute for problem solving in learning algebra. ''Cognition and Instruction, 2'', 59–89.
* Trafton, J. G., & Reiser, B.J. (1993). The contributions of studying examples and solving problems to skill acquisition. In M. Polson (Ed.), ''Proceedings of the Fifteenth annual conference of the Cognitive Science Society'' (1017-1022). Hillsdale, N.J.: Erlbaum.
* Ward, M., & Sweller, J. (1990). Structuring effective worked examples. ''Cognition and Instruction, 7'', 1-39.
* Zhu, X., & Simon, H. A. (1987). Learning mathematics from examples and by doing. ''Cognition and Instruction, 4''(3), 137-166.

[[Category:Glossary]]
[[Category:Independent Variables]]
[[Category:Coordinative Learning]]
[[Category:Interactive Communication]]
[[Category:PSLC General]]

Worked Examples

2008-05-21T21:51:03Z

Turadg: linked to active page

Step-by-step solutions to problems, together with explanations of each step, presented in textual, graphical, or video format.

'''Nothing links to this page'''. See [[Worked examples]] (different capitalization).