1. The Effect of Generation and Interaction on Robust Learning Robert G.M. Hausmann Kurt VanLehn Pittsburgh Science of Learning Center Learning Research and Development Center University of Pittsburgh

2. Explaining Examples u Prompting –Paraphrase –Self-explain u Example Type –Complete –Incomplete Experiment 1 u Interaction –Individual (solo) –Collaborative (dyad) u Prompting –Natural –Explain Experiment 2 u The Generation Hypothesis u The Coverage Hypothesis u The Interaction Hypothesis u The Coverage Hypothesis

3. The Interaction Hypothesis u The interaction itself increases learning gains, even if the set of learning events covered by dyads and solos is exactly the same. u Potential Explanations of the hypothesis (Rogoff, 1998) –Process of negotiating meaning with a peer –Appropriating part of the peers’ perspective –Building and maintaining common ground –Articulating their knowledge –Clarifying it when the peer misunderstands

4. The Coverage Hypothesis u Learning should be equivalent for peers and solo learners, provided : –Both forms of instruction must cover the same information. –The student must attend to that information. u Similar proposals –Transfer performance depends on mastery, not path (i.e., direct instruction vs. discovery learning) (Klahr & Nigam, 2004) –Different types of instruction lead to different knowledge structures but similar performance (Nokes & Ohlsson, 2005) –If within ZPD, then dialog = monolog (VanLehn et al., in press)

5. Studies of Dyad vs. Solo u Chi & Roy (in press) example study + problem solving –Dyad > solo when both solving and watching a video of a tutor/tutee pair solving the same problem. u Many: problem solving –Self- vs. interactive explanations (Ploetzner, Dillenbourg, Praier, & Traum, 1999) –Newtonian Physics (Kneser & Ploetzner, 2001) –Conceptual Engineering (Hausmann, 2006) –Hundreds more… u None: example studying

6. Method u Participants –Physics LearnLab –United States Naval Academy (N=100) u Materials –Andes homework system –Domain: electrodynamics (electric & magnetic fields) u Robust Learning Measures –Duration: immediate (experiment), short delay (chapter exam), long delay (final exam) –Transfer: chapter & final exam isomorphic problems –Preparation for learning: magnetism homework

7. Design u Natural Solo: prompts to keep working, but no processing advice (control for Hawthorn effects). u Explain Solo: prompts to self-explain u Natural Dyads: prompts to keep working together, but no collaborative processing advice. u Explain Dyads: prompts to generate joint explanations Interaction SolosDyads Natural n=25 Explain n=25 Prompting

8. Procedure Problem4: Immediate Posttest Solo Explain Solo Natural Dyad Explain Dyad Natural Example1Example2 Solo Explain Solo Natural Dyad Explain Dyad Natural Example3 Solo Explain Solo Natural Dyad Explain Dyad Natural Problem3: Intermed. Posttest Problem2: Intermed. Posttest Problem1: Warm-up Problem

9. Data Sources u Andes log files: Homework (before & after) u Andes log files: Experiment u On-screen activities: Experiment u Coded interactions (McGregor & Chi, 2002): –Novel or Repeated knowledge component –Individual or jointly generated –If individual, record speaker/listener (Hausmann, Chi, & Roy, 2004)

10. Predicted Results The Interaction Hypothesis The Coverage Hypothesis

11. Learning event space Process Line Dyad Prompted Natural Prompted Explain Little Learning A Explains; B Listens Neither Explain Learning Jointly Explain B ComprehendsB ~Comprehend Solo Prompted Natural Prompted Explain Little Learning Explain~Explain Learning

12. How should prompting to explain affect path choice? u Read line (Solo) 1.Explain  Exit, with learning 2.Not explain  Exit, without learning u Read line (Dyad) 1.Neither explains  Exit, with little learning 2.A (B) explains 1.B (A) comprehends  Exit, both learn 2.B (A) fails to comprehend  Exit, A (B) learns 3.A & B co-construct an explanation  Exit, both learning Increase?

13. How should interaction affect path choice? u Read line (Dyad) 1.Neither explains  Exit, with little learning 2.A (B) explains 1.B (A) comprehends  Exit, both learn 2.B (A) fails to comprehend  Exit, A (B) learns 3.A & B co-construct an explanation  Exit, both learning Accountability, so this decreases Probability of having the right knowledge

14. How should interaction affect path effects? u Read line (Dyad) 1.Neither explains  Exit, with little learning 2.A (B) explains 1.B (A) comprehends  Exit, both learn 2.B (A) fails to comprehend  Exit, A (B) learns 3.A & B co-construct an explanation  Exit, both learning Less feature validity Partner not present at post-test,  moderate learning gains?

15. Questions/Feedback

16. Why might dyads choose the right paths more frequently than solos? u Collaborators may be more engaged than the solos: – accountable? Responsible? u The union of the collaborators’ knowledge has fewer gaps, so they more often finds explanations –Heterogeneous groups outperform homogeneous groups (Howe, Tolmie, & Rodgers, 1992) –Diverse knowledge increases probability of taking good paths.

17. Learning-event Space: Solo u Read line 1.Explain: Exit, with learning 2.Not explain: Exit, without learning

18. Learning-event Space: Dyad u Read line 1.Neither explains: Exit, with little learning 2.A (B) explains 1.B (A) comprehends: Exit, both learn 2.B (A) fails to comprehend: Exit, A (B) learns 3.A & B co-construct an explanation: Exit, both learning