The Effect of Generation and Interaction on Robust Learning

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

3. The Interaction Hypothesis • The interaction itself increases learning gains, even if the set of learning events covered by dyads and solos is exactly the same. • 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 • 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. • 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 • 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. • Many: problem solving • Self- vs. interactive explanations (Ploetzner, Dillenbourg, Praier, & Traum, 1999) • Newtonian Physics (Kneser & Ploetzner, 2001) • Conceptual Engineering (Hausmann, 2006) • Hundreds more… • None: example studying

6. Method • Participants • Physics LearnLab • United States Naval Academy (N=100) • Materials • Andes homework system • Domain: electrodynamics (electric & magnetic fields) • 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 • Natural Solo: prompts to keep working, but no processing advice (control for Hawthorn effects). • Explain Solo: prompts to self-explain • Natural Dyads: prompts to keep working together, but no collaborative processing advice. • Explain Dyads: prompts to generate joint explanations Prompting

8. Example1 Example2 Example3 Solo Explain Solo Explain Solo Explain Solo Natural Solo Natural Solo Natural Dyad Explain Dyad Explain Dyad Explain Dyad Natural Dyad Natural Dyad Natural Procedure Problem1: Warm-up Problem Problem2: Intermed. Posttest Problem3: Intermed. Posttest Problem4: Immediate Posttest

9. Data Sources • Andes log files: Homework (before & after) • Andes log files: Experiment • On-screen activities: Experiment • 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. Solo Dyad Prompted Natural Prompted Explain PromptedNatural PromptedExplain ~Explain Explain Neither Explain A Explains; B Listens Jointly Explain B ~Comprehend B Comprehends Little Learning Little Learning Learning Learning Learning event space Process Line

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

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

14. How should interaction affect path effects? • Read line (Dyad) • Neither explains  Exit, with little learning • A (B) explains • B (A) comprehends  Exit, both learn • B (A) fails to comprehend  Exit, A (B) learns • 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? • Collaborators may be more engaged than the solos: • <social psych?> accountable? Responsible? • 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 • Read line • Explain: Exit, with learning • Not explain: Exit, without learning

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