Designing learning by teaching agents: The betty’s brain system

International Journal of Artificial Intelligence in Education

Volumn 18, Issue 3, 2008, Pages 181-208

  Leelawong, Krittaya ^a   Biswas, Gautam ^a  

^a VANDERBILT UNIVERSITY   (United States)

Author keywords

Learning by teaching; Metacognitive strategies; Self regulated learning; Teachable agents

Indexed keywords

EID: 85013605746     PISSN: 15604292     EISSN: 15604306     Source Type: Journal    
DOI: None     Document Type: Article

References (44)

1. Ames, C., & Archer, J. (1988). Achievement Goals in the Classroom: Students’ Learning Strategies and Motivation Processes. Journal of Educational Psychology, 80(3), 260-267.
2. Artzt, A. F., & Armour-Thomas, E. (1999). Cognitive Model for Examining Teachers’ Instructional Practice in Mathematics: A Guide for Facilitating Teacher Reflection. Educational Studies in Mathematics, 40(3), 211-235.
3. Bargh, J. A., & Schul, Y. (1980). On the cognitive benefits of teaching. Journal of Educational Psychology, 72(5), 593-604.
4. Biswas, G., Schwartz, D. L., Bransford, J. D., & TAG-V. (2001). Technology support for complex problem solving: From SAD Environments to AI. In K. Forbus & P. Feltovich (Eds.) Smart machines in education (pp. 71-98). Menlo Park, CA: AAAI/MIT Press.
5. Biswas, G., Schwartz, D. L., Leelawong, K., Vye, N., & TAG-V. (2005). Learning by teaching: A new paradigm for educational software. Applied Artificial Intelligence, 19(3), 363-392.
6. Biswas, G., Leelawong, K., Belynne, K., Viswanath, K., Vye, N., Schwartz, D., & Davis, J. (2004). Incorporating Self Regulated Learning Techniques into Learning by Teaching Environments. In K. Forbus, D. Gentner & T. Regier (Eds.) Proceedings of the Twenty Sixth Annual Meeting of the Cognitive Science Society (pp. 120-125). Mahwah, NJ: Lawrence Erlbaum Associates.
7. Bransford, J. D., Brown, A. L., & Cocking, R.R. (Eds.). (2000). How People Learn. Washington, D.C., National Academy Press.
8. Brophy, S., Biswas, G., Katzlberger, T., Bransford, J., & Schwartz, D. (1999). Teachable Agents: Combining Insights from Learning Theory and Computer Science. In S.P. Lajoie & M. Vivet (Eds.) Artificial Intelligence in Education Open Learning Environments: New Computational Technologies to Support Learning (pp. 21-28). Amsterdam: IOS Press.
9. Brown, A.L. (1987). Metacognition, Executive Control, Self-Regulation and other more Mysterious Mechanisms. In F.E. Weinert & R.H. Kluwe (Eds.) Metacognition, Motivation, and Understanding (pp. 65-116). Hillsdale, NJ: Lawrence Erlbaum Associates.
10. Butler, D. L., & Winne, P. H. (1995). Feedback and Self-Regulated Learning: A Theoretical Synthesis. Review of Educational Research, 65(3), 245-281.
11. Chan, T.-W., & Chou, C.-Y. (1997). Exploring the Design of Computer Supports for Reciprocal Tutoring. International Journal of Artificial Intelligence in Education, 8 1-29.
12. Chi, M. T. H., De Leeuw, N., Chiu, M.-H., & Lavancher, C. (1994). Eliciting self-explanations. Cognitive Science, 18 439-477.
13. Chi, M. T. H., Siler, S. A., Jeong, H., Yamauchi, T., & Hausmann, R. G. (2001). Learning from Human Tutoring. Cognitive Science, 25(4), 471-533.
14. Clarebout, G., Elen, J., Johnson, W. L., & Shaw, E. (2002). Animated Pedagogical Agents: An Opportunity to be Grasped? Journal of Educational Multimedia and Hypermedia, 11, 267-286.
15. Colton, A. B., & Sparks-Langer, G. M. (1993). A Conceptual Framework to Guide the Development of Teacher Reflection and Decision Making. Journal of Teacher Education, 44(1), 45-54.
16. Davis, J., Leelawong, K., Belynne, K., Bodenheimer, B., Biswas, G., Vye, N., & Bransford, J. (2003). In W. In L. Johnson, E. Andre & J. Domingue (Eds.) IUI '03: Proceedings of the 8th International Conference on Intelligent User Interfaces (pp. 26-33). New York: The Association for Computing Machinery.
17. Forbus, K. (1984). Qualitative Process Theory. Artificial Intelligence, 24 85-168.
18. Goos, M., Galbraith, P., & Renshaw, P. (2002). Socially Mediated Metacognition: Creating Collaborative Zones of Proximal Development in Small Group Problem Solving. Educational Studies in Mathematics, 49 193-223.
19. Graesser, A. C., Person, N., & Magliano, J. (1995). Collaborative dialog patterns in naturalistic one on one tutoring. Applied Cognitive Psychologist, 9 495-522
20. Leelawong, K. (2005). Using the Learning-by-Teaching Paradigm to Design Learning Environments. Unpublished PhD. Department of EECS, Vanderbilt University, Nashville, USA.
21. Leelawong, K., Wang, Y., Biswas, G., Vye, N., & Bransford, J. (2001). Qualitative reasoning techniques to support learning by teaching: The Teachable Agents project. Fifteenth International Workshop on Qualitative Reasoning (pp. 73-80). San Antonio, Texas. AAAI Press
22. Leelawong, K., Davis, J., Vye, N., Biswas, G., Schwartz, D., Belynne, K., Katzlberger, T., & Bransford, J. (2002). The Effects of Feedback in Supporting Learning by Teaching in a Teachable Agent Environment. In P. Bell, R. Stevens & T. Satwicz (Eds.) Keeping Learning Complex: The Proceedings of the Fifth International Conference for the Learning Sciences (pp. 245-252). Mahwah, NJ: Lawrence Erlbaum Associates.
23. Lin, X. D., Schwartz, D. L., & Hatano, G. (2005). Towards teachers’ adaptive metacognition. Educational Psychologist, 40(4), 245-255.
24. McAlpine, L., Weston, C., Beauchamp, J., Wiseman, C., & Beauchamp, C. (1999). Building a Metacognitive Model of Reflection. Higher Education, 37(2), 105-131.
25. Michie, D., Paterson, A., & Hayes-Michie, J. E. (1989). Learning by Teaching. Second Scandinavian Conference on Artificial Intelligence (SCAI) (pp. 307-331). Amsterdam: IOS Press.
26. Nichols, D. M. (1993). Intelligent Student Systems: an application of viewpoints to intelligent learning environments. Unpublished PhD, Lancaster University, UK.
27. Nichols, D. M. (1994). Issues in Designing Learning by Teaching Systems. In Proceedings of the East-West International Conference on Computer Technologies in Education (EW-ED’94) (pp. 176-181). Crimea, Ukraine.
28. Novak, J. D. (1996). Concept Mapping as a tool for improving science teaching and learning. In D. F. Treagust, R. Duit & B. J. Fraser (Eds). Improving Teaching and Learning in Science and Mathematics (pp. 32-43). London, Teachers College Press.
29. Obayashi, F., Shimoda, H., & Yoshikawa, H. (2000). Construction and Evaluation of CAI System Based on Learning by Teaching to Virtual Student. World Multiconference on Systemics, Cybernetics and Informatics (pp. 94-99). Volume 3. Orlando, Florida.
30. Palincsar, A. S., & Brown, A. L.(1984). Reciprocal teaching of comprehension-fostering and comprehension-monitoring activities. Cognition and Instruction, 1, 117-175.
31. Palthepu, S., Greer, J. E., & McCalla, G. (1991). Learning by teaching. In L. Birnbaum (Ed.) Proceedings of the First International Conference on the Learning Sciences (pp. 357-363). Charlottesville, VA: American Association for Advancement of Computing in Education.
32. Papert, S. (1993). he Children’s Machine: Rethinking school in the age of the computer. New York, NY: Basic Books.
33. Pintrich, P. R., & DeGroot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82(1), 33-40.
34. Ramirez Uresti, J. A. (2000). Should I Teach My Computer Peer? Some Issues in Teaching a Learning Companion. In G. Gauthier, C. Frasson & K. VanLehn (Eds.) Proceedings of the 5th International Conference on Intelligent Tutoring Systems (pp. 103-112). Berlin: Springer-Verlag.
35. Ramirez Uresti, J.A., & du Boulay, B. (2004). Expertise, Motivation, and Teaching in Learning by Teaching Systems. International Journal of Artificial Intelligence in Education, 14 67-106.
36. Schwartz, D. L., Blair, K. P., Biswas, G., Leelawong, K., & Davis, J. P. (2008). Animations of Thought: Interactivity in the Teachable Agent Paradigm. In R. Lowe & W. Schnotz (Eds.) Learning with Animation: Research and Implications for Design. Cambridge University Press. (Available at AAALab.Stanford.Edu).
37. Shapiro, A. (1983). he Role of Structured Induction in Expert Systems. Machine Intelligence Unit. Edinburgh, UK: University of Edinburgh.
38. Tan, J., Biswas, G., & Schwartz, D. (2006). Feedback for Metacognitive Support in Learning by Teaching Environments. In R. Sun and N. Miyake (Eds.) Proceedings of the 28th Annual Meeting of the Cognitive Science Society (pp. 828-833). Vancouver, Canada.
39. Tan, J., Skirvin, N., Biswas, G., & Catley, K. (2007). Providing Guidance and Opportunities for Self-Assessment and Transfer in a Simulation Environment for Discovery Learning. In D. S. McNamara & G. Trafton (Eds.) Proceedings of the 29th Annual Meeting of the Cognitive Science Society (pp. 1539-1544). Nashville, TN.
40. Wagster, J., Tan, J., Wu, Y., Biswas, G., & Schwartz, D. (2007). Do Learning by Teaching Environments with Metacognitive Support Help Students Develop Better Learning Behaviors? In D. In S. McNamara & G. Trafton (Eds.) Proceedings of the 29th Annual Meeting of the Cognitive Science Society (pp. 695-700). Nashville, TN.
41. Weinert, F.E., & Kluwe, R. (1987). Metacognition, motivation, and understanding. Hillsdale, NJ: Lawrence Erlbaum Associates.
42. Wenger, E. (1987). Artificial intelligence and tutoring systems: computational and cognitive approaches to the communication of knowledge. San Mateo, CA: Morgan Kaufmann.
43. Zimmerman, B. J. (1986). Development of self-regulated learning: Which are the key subprocesses? Contemporary Educational Psychology, 16, 307-313.
44. Zimmerman, B. J. (1989). A Social Cognitive View of Self-Regulated Academic Learning. Journal of Educational Psychology, 81(3), 329-339.