Difference between revisions of "Interactive Communication"

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== The PSLC Interactive Communication cluster ==
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= The PSLC Interactive Communication cluster =
  
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=== Abstract ===
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== Abstract ==
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The studies in the Interactive Communication deal primarily with learning environments where there are two agents, one of which is the student.  The other agent is typically a second student, a human tutor or a tutoring system. Both agents are capable of doing the instructional activity, albeit with varying degrees of success.  They communicate, either in a natural language or a formal language, such as mathematical expression or menus.  The main variables are:
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The studies in the Interactive Communication deal primarily with learning environments where there are two interacting, communicating agents, one of which is the student.  The other [[agent]] is typically a second student, a human tutor or a tutoring system.  They communicate, either in a natural language or a formal language, such as mathematical expression or menus.  We are trying to find out why such instructional, dyadic, interactive communication is sometimes highly effective and sometimes less effective.  Sometimes we study highly constrained forms of communication in order to vary isolated aspects, and sometimes we compare whole forms of communciation.  Our hypothesis is simply that interactive communication is effective if it guides students to attend to the right [[knowledge components]].
  
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*What part of the work is done by which agent?  On one extreme, the student does all the work while the other agent watches. On the other extreme, the student watches while the other agent does all the work.  In the middle, the two agents collaborate somehow.
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<br><center>[[Image:Ic.JPG]]</center>
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*Who makes the choice about which work is done by which agent?  The student, the other agent or a fixed policy of some kind?
 
  
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Our hypothesis is that learning by doing is the best, except that as the student takes on more work or more challenging work, the error frequency or the time to recover from errors may begin to interfere with learning.  Communication also can interfere when learning, in that it takes time and cognitive resources, and that it is never perfect.  Thus, learning can be optimized by somehow balancing the work done by the student, the work done by the agent and the work done by both in communicating.
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== Background and Significance ==
 +
Although instructional dialogue has been studied in classrooms (e.g., Lave & Wenger, 1991; Leinhardt, 1990) and workplaces (e.g., Hutchins, 1995; Nunes, Schliemann & Carraher, 1993), we are focusing on more tractable albeit still complex situations: ''dyadic'' instructional dialogues, namely dialogues between: (a) a human tutor and a human student, (b) two human students, or (c) A computer tutor and a human student. Moreover, the dialogue are task-oriented (Grosz & Sidner, 1986) in that the participants are working together on a task rather than simply conversing with no shared goals or with opposing goals.
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Early studies focused on the structure of dyadic instructional dialogue (e.g., Fox, 1993; Graesser, Person & Magliano, 1995; MacArthur, Stasz, & Zmuidzinas, 1990).  When later studies compared the learning that occurred during dialogue vs.  less interactive instruction (e.g., VanLehn, Graesser et al., 2007; Katz, Connelly & Allbritton, 2003; Evens & Michael, 2006; Cohen, Kulik & Kulik, 1982), they found surprisingly mixed results.  Only 60% of the studies showed that interactive communication caused larger learning gains than less interactive instruction.  
  
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=== Background and Significance ===
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The interactive communication cluster is undertaking the next step in this important line of research by investigating when different types of interactive communication are effective and why. Sometimes we compare highly constrained forms of communication in order to vary isolated aspects, and sometimes we compare constrained interactive communication to passive communication (e.g., reading).
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Educational dialogue has mostly been studied in classrooms (e.g., Lave & Wenger, 1991; Leinhardt, 1990) and workplaces (e.g., Hutchins, 1995; Nunes, Schliemann & Carraher, 1993). In order to investigate more tractable albeit still complex situations, most of our research focuses on dyadic dialogues, namely dialogues between: (a) a human tutor and a human student, (b) two human students, or (c) A computer tutor and a human student.
 
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Some studies of naturally occurring dyadic dialogues (e.g., Fox, 1993; Graesser, Bowers, Hacker, & Person, 1997; MacArthur, Stasz, & Zmuidzinas, 1990) sought their underlying structure.  They found that the dialogue structure was strongly determined by the task that the participants were working on.  For instance, if the task was solving a problem, then both dyads and students working alone tended to follow paths in the problem space.
 
  
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Other studies compared the learning gains of dyadic dialogue-based instruction to non-interactive instruction from text, video, etc. (e.g., VanLehn, Graesser et al., in press; Katz, Connelly & Allbritton, 2003; Cohen, Kulik & Kulik, 1982). These studies found surprisingly mixed results.  Although most studies showed that interactive communication was more effective than less interactive instruction, it was not always better than non-interactive instruction.
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== Glossary ==
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See [[:Category:Interactive Communication|Interactive Communication Glossary]]
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Having preliminary answers to the research questions of what dialogue is and whether it is effective, the next step in this important line of research is to determine when different types of interactive communication are effective and why.
 
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The studies in the Interactive Communication cluster tend 
 
  
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=== Glossary ===
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== Research question ==
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To be developed, but will probably include:
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What properties of interactive communication promote robust learning?
  
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* ''Agent'':  Something that can perform the instructional activity.  Typically a student, a tutor, a tutoring system or a simulated student.  In the extreme case, an agent can be a passive medium, such as text or a video, that presents a performance of the activity.  For instance, if the instructional activity is solving physics problems, then a worked example, such as the ones shown in a textbook, is an agent.
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== Independent variables ==
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The independent variables (also called Treatment Variables) of the IC cluster appear as column headers in the matrix above.  They are listed here with links to their glossary entries.
  
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* ''Communication''.
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* [[Collaboration]]
  
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* ''Initiative''.  This measures the ratio of the work initiated by the two agents.  A dialogue with lots of student initiative is one where the student spontaneously initiates work on the activity.  A dialogue with lots of tutor initiative is one where the tutor either does the work or requests (in the speech act sense of “request”) the student to do the work.  The “initiative” term comes from linguistics, whereas a synonymous distinction, learn control vs. teacher control, comes from education.
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* [[Vicarious learning]]
  
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* ''Zone of proximal development''.  When instruction is laid out on a scale of difficulty from easy to hard, there is a region where the instruction is too hard for the student to learn effectively from it without help, but still just easy enough that the student can learn if given help, typically from a second agent.  This region is called the zone of proximal development (ZPD), a term from developmental psychology.
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* [[Collaboration scripts]]
  
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=== Research question ===
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* [[Deep/Reflection questions]]
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How can instructional activities that involve two agents, the student and another agent, increase robust learning?
 
  
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=== Independent ===
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* [[Instructional explanation]]
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* The type of second agent (peer, tutor, computer program, passive media) and how it communicates with the student,
 
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* the allocation of work between the two agents,
 
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* how that schedule is controlled,
 
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* and the difficulty of the instruction.
 
  
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=== Dependent variables ===
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* [[Prompted Self-explanation]]
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Measures of normal and robust learning.
 
  
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=== Hypothesis ===
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* [[Tutoring feedback]]
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When student engage in collaborative learning with another agent where the collaboration somehow appropriately balances the work done by the agents and their communication, then learning will be more robust than it would if the learning environment had just the student and not the second agent.
 
  
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=== Explanation ===
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* [[Error correction support]]
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Assuming a control condition where the student works alone or with only limited interaction with the second agent, there are 3 cases:
 
  
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#If the instruction is in the students’ zone of proximal development (ZPD), then a second agent’s help can increase learning compared to a control condition.
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== Dependent variables ==
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#If the instruction above (more difficult than) the ZPD, then the student makes too many errors and/or requires too much communication with the second agent, which thwarts learning.  Thus, learning is equally ineffective in the two conditions.
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Measures of normal and robust learning.
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#If the instruction is below (more easy than) the ZPD, then the student can learn just as much working alone as when working with the second agent.  That is, learning is equally effective in the two conditions.
 
  
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This idea can be rephrased in terms of the PSLC’s [[Root_node|general hypothesis]].  Robust learning should occur under two conditions.  First, the instruction should be designed to have the right paths, which means that there is a target path that involves the student doing almost all the intellectual work (learning by doing) and many alternative paths where in the second agent does most of the work.  Second, the student should choose the paths so that they take the learning-by-doing path by default, and take the other paths when the learning-by-doing path is too difficult for this particular student at this time.  Moreover, the choice of taking an alternative to the learning-by-doing path should take into account the overhead and reliability of communication, which is generally higher on the alternative paths.
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== Hypothesis ==
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Our central hypothesis is just a special case of the [[Knowledge component hypothesis]]: interactive communication is effective if it guides students to attend to the right [[knowledge components]].  The key words here are “guide” and “attend” because they may oppose each other.  A dialogue that strongly guides the student may also cause the student to disengage and thus not attend to the knowledge component even if the student’s dialogue partner mentions them.  On the other hand, an unguided dialogue may increase the student’s engagement but may skirt around the right knowledge components.  That is, the [[assistance dilemma]] surfaces as the degree of ''learner control'' (a term from the older educational literature) or ''student initiativ''e (a nearly synonymous term from the natural language dialogue literature).
  
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=== Descendents ===
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== Explanation ==
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If we view a short episode of interactive communication as a [[learning event space]], there could be three reasons why one treatment might be more effective than another: 
  
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*[[Craig_questions|Deep-level questions during example studying (Craig & Chi)]]
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(1) The learning event spaces might have different paths with different content.  For instance, if one person contributes critical information that the other person lacks, then their joint learning event space has paths that are absent in the learning event space of the second person if that person were working solo.  That is, the ''topology'' of one space might be better than the topology of the other.
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(2) If the learning event spaces in the two conditions are the same, then the interactive communication treatment might cause the students to traverse different paths than the control students.  That is, the ''path choices'' of one treatment might be better than the path choices of the other.
  
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*[[Craig_observing|Learning from Problem Solving while Observing Worked Examples (Craig Gadgil, & Chi)]]
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(3) If the learning event spaces are the same and the students take the same paths, they still might learn more in one condition than another because of the way that they traversed the path.  For instance, having a partner observe the student as the student traverse a path might cause the student to be more attentive to details and to remember more.  That is, the ''path effects'' might differ in the treatment vs. the control.
  
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*[[Hausmann_Study|Does it matter who generates the explanations? (Hausmann & VanLehn)]]
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== Descendents ==
  
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*[[Hausmann_Study2|The effects of interaction on robust learning (Hausmann & VanLehn)]]
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=== Collaboration ===
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When and how does collaboration between peers can increase robust learning? Problem solving, example studying and many other activities can be done alone, in pairs, or in pairs with various kinds of assistance, such as collaboration scripts. From the standpoint of an individual learner, having a partner offers more [[assistance]] than working alone, and having a partner plus other scaffolding offer even more assistance.  Thus, the [[Assistance Hypothesis]] predicts an interaction between various forms of peer collaboration and students' prior competence.
  
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*[[Hausmann_Diss|The effects of elaborative dialog on problem solving and learning (Hausmann & Chi)]]
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*[[Craig_observing|Learning from Problem Solving while Observing Worked Examples (Craig Gadgil, VanLehn & Chi)]]
  
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*[[Reflective Dialogues (Katz)]]
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*[[Hausmann_Diss|The effects of elaborative dialog on problem solving and learning (Hausmann & Chi, 2005)]]
  
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*[[Post-practice reflection (Katz)]]  
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*[[Hausmann_Study2|The effects of interaction on robust learning (Hausmann & VanLehn, 2007)]]
  
 
*[[Rummel_Scripted_Collaborative_Problem_Solving|Collaborative Extensions to the Cognitive Tutor Algebra: Scripted Collaborative Problem Solving (Rummel, Diziol, McLaren, & Spada)]]
 
*[[Rummel_Scripted_Collaborative_Problem_Solving|Collaborative Extensions to the Cognitive Tutor Algebra: Scripted Collaborative Problem Solving (Rummel, Diziol, McLaren, & Spada)]]
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*[[Walker_A_Peer_Tutoring_Addition|Collaborative Extensions to the Cognitive Tutor Algebra: A Peer Tutoring Addition (Walker, McLaren, Koedinger, & Rummel)]]
 
*[[Walker_A_Peer_Tutoring_Addition|Collaborative Extensions to the Cognitive Tutor Algebra: A Peer Tutoring Addition (Walker, McLaren, Koedinger, & Rummel)]]
  
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*[[The_Help_Tutor__Roll_Aleven_McLaren|Tutoring a meta-cognitive skill: Help-seeking (Roll, Aleven & McLaren)]] [Moved to Refinement and Fluency, Was in Coordinative Learning]
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*[[Adaptive Assistance for Peer Tutoring (Walker, Rummer, Koedinger)]]
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*[[McLaren_et_al_-_Conceptual_Learning_in_Chemistry|Supporting Conceptual Learning in Chemistry through Collaboration Scripts and Adaptive, Online Support (McLaren, Rummel, Harrer, Spada, & Pinkwart)]]
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=== Questioning ===
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When and how can asking the student questions increase the student's robust learning?  What kinds of questions are best? 
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*[[Craig_questions|Deep-level questions during example studying (Craig & Chi)]]
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*[[Post-practice reflection (Katz)|Post-practice reflection (Katz & Connelly, 2005)]]
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*[[Reflective Dialogues (Katz)|Reflective Dialogues (Katz, Connelly, & Treacy, 2006)]]
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*[[Extending Reflective Dialogue Support (Katz & Connelly)|Extending Reflective Dialogue Support (Katz & Connelly, 2007)]]
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*[[Self-explanation: Meta-cognitive vs. justification prompts|Self-explanation: Meta-cognitive vs. justification prompts (Hausmann, van de Sande, Gershman, & VanLehn, 2008]])
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*[[FrenchCulture|Understanding culture from film (Ogan, Aleven & Jones)]] [Also relevant to Refinement & Fluency, Explicit instruction and manipulations of attention & discrimination]
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=== Tell vs. elicit ===
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When a tutor knows that something needs to be said, she or he must decide whether to ''tell'' it to the tutee, try to ''elicit'' it from the tutee via a question or prompt, or just ''wait'' and hope that the tutee says it.  Similarly, if a tutor knows that something needs to be done, the tutor can do it, elicit the action from the student or just wait.  An instructional designer faces the same choices.  For each thing that needs to be said or done in the instructional dialogue, should the tutor or the student be made responsible for it?  For instance, should the tutoring system point out errors to the students or should the students detect their errors?  In general, assistance is higher when the tutor does a portion of the instructional activity than when the student does it.
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*[[Student_Uncertainty|Does Treating Student Uncertainty as a Learning Impasse Improve Learning in Spoken Dialogue Tutoring? (Forbes-Riley & Litman)]]  
  
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*[[FrenchCulture|Understanding culture from film (Ogan, Aleven & Jones)]]
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*[[The self-correction of speech errors (McCormick, O’Neill & Siskin)]]
  
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*Does learning from examples improved tutored problem solving? (Renkl, Aleven & Salden) [Was in Coordinative Learning]
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*[[Hausmann_Study|Does it matter who generates the explanations? (Hausmann & VanLehn, 2006)]]
  
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*[[Visual-Verbal Learning (Aleven & Butcher Project) | Visual-Verbal Learning (Aleven & Butcher)]] -- ''Elaborated Explanation condition is the relevant manipulation''
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*[[Using Elaborated Explanations to Support Geometry Learning (Aleven & Butcher)]]
  
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*The self-correction of speech errors (McCormick, O’Neill & Siskin) [Was in Fluency and in Coordinative Learning]
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*[[The_Help_Tutor__Roll_Aleven_McLaren|Tutoring a meta-cognitive skill: Help-seeking (Roll, Aleven & McLaren)]] [Also in the Refinement & Fluency cluster, and relevant to Knowledge Component analysis]
  
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=== Annotated bibliography ===
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*[[Plateau_study|What is the optimal level of interaction during learning from problem solving? (Hausmann, van de Sande, & VanLehn, 2008)]]
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Forthcoming
 
  
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*[[Ringenberg_Ill-Defined_Physics|Eliciting missing information for solving ill-defined physics problems. (Ringenberg & VanLehn, 2008)]]
 
[[Category:Cluster]]
 
[[Category:Cluster]]

Latest revision as of 12:48, 8 September 2011

The PSLC Interactive Communication cluster

Abstract

The studies in the Interactive Communication deal primarily with learning environments where there are two interacting, communicating agents, one of which is the student. The other agent is typically a second student, a human tutor or a tutoring system. They communicate, either in a natural language or a formal language, such as mathematical expression or menus. We are trying to find out why such instructional, dyadic, interactive communication is sometimes highly effective and sometimes less effective. Sometimes we study highly constrained forms of communication in order to vary isolated aspects, and sometimes we compare whole forms of communciation. Our hypothesis is simply that interactive communication is effective if it guides students to attend to the right knowledge components.


Ic.JPG

Background and Significance

Although instructional dialogue has been studied in classrooms (e.g., Lave & Wenger, 1991; Leinhardt, 1990) and workplaces (e.g., Hutchins, 1995; Nunes, Schliemann & Carraher, 1993), we are focusing on more tractable albeit still complex situations: dyadic instructional dialogues, namely dialogues between: (a) a human tutor and a human student, (b) two human students, or (c) A computer tutor and a human student. Moreover, the dialogue are task-oriented (Grosz & Sidner, 1986) in that the participants are working together on a task rather than simply conversing with no shared goals or with opposing goals.

Early studies focused on the structure of dyadic instructional dialogue (e.g., Fox, 1993; Graesser, Person & Magliano, 1995; MacArthur, Stasz, & Zmuidzinas, 1990). When later studies compared the learning that occurred during dialogue vs. less interactive instruction (e.g., VanLehn, Graesser et al., 2007; Katz, Connelly & Allbritton, 2003; Evens & Michael, 2006; Cohen, Kulik & Kulik, 1982), they found surprisingly mixed results. Only 60% of the studies showed that interactive communication caused larger learning gains than less interactive instruction.

The interactive communication cluster is undertaking the next step in this important line of research by investigating when different types of interactive communication are effective and why. Sometimes we compare highly constrained forms of communication in order to vary isolated aspects, and sometimes we compare constrained interactive communication to passive communication (e.g., reading).

Glossary

See Interactive Communication Glossary

Research question

What properties of interactive communication promote robust learning?

Independent variables

The independent variables (also called Treatment Variables) of the IC cluster appear as column headers in the matrix above. They are listed here with links to their glossary entries.

Dependent variables

Measures of normal and robust learning.

Hypothesis

Our central hypothesis is just a special case of the Knowledge component hypothesis: interactive communication is effective if it guides students to attend to the right knowledge components. The key words here are “guide” and “attend” because they may oppose each other. A dialogue that strongly guides the student may also cause the student to disengage and thus not attend to the knowledge component even if the student’s dialogue partner mentions them. On the other hand, an unguided dialogue may increase the student’s engagement but may skirt around the right knowledge components. That is, the assistance dilemma surfaces as the degree of learner control (a term from the older educational literature) or student initiative (a nearly synonymous term from the natural language dialogue literature).

Explanation

If we view a short episode of interactive communication as a learning event space, there could be three reasons why one treatment might be more effective than another:

(1) The learning event spaces might have different paths with different content. For instance, if one person contributes critical information that the other person lacks, then their joint learning event space has paths that are absent in the learning event space of the second person if that person were working solo. That is, the topology of one space might be better than the topology of the other.

(2) If the learning event spaces in the two conditions are the same, then the interactive communication treatment might cause the students to traverse different paths than the control students. That is, the path choices of one treatment might be better than the path choices of the other.

(3) If the learning event spaces are the same and the students take the same paths, they still might learn more in one condition than another because of the way that they traversed the path. For instance, having a partner observe the student as the student traverse a path might cause the student to be more attentive to details and to remember more. That is, the path effects might differ in the treatment vs. the control.

Descendents

Collaboration

When and how does collaboration between peers can increase robust learning? Problem solving, example studying and many other activities can be done alone, in pairs, or in pairs with various kinds of assistance, such as collaboration scripts. From the standpoint of an individual learner, having a partner offers more assistance than working alone, and having a partner plus other scaffolding offer even more assistance. Thus, the Assistance Hypothesis predicts an interaction between various forms of peer collaboration and students' prior competence.

Questioning

When and how can asking the student questions increase the student's robust learning? What kinds of questions are best?

Tell vs. elicit

When a tutor knows that something needs to be said, she or he must decide whether to tell it to the tutee, try to elicit it from the tutee via a question or prompt, or just wait and hope that the tutee says it. Similarly, if a tutor knows that something needs to be done, the tutor can do it, elicit the action from the student or just wait. An instructional designer faces the same choices. For each thing that needs to be said or done in the instructional dialogue, should the tutor or the student be made responsible for it? For instance, should the tutoring system point out errors to the students or should the students detect their errors? In general, assistance is higher when the tutor does a portion of the instructional activity than when the student does it.

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