User Modeling and User-Adapted Interaction

, Volume 16, Issue 3–4, pp 175–209 | Cite as

Creating cognitive tutors for collaborative learning: steps toward realization

  • Andreas HarrerEmail author
  • Bruce M. McLaren
  • Erin Walker
  • Lars Bollen
  • Jonathan Sewall
Original Paper


Our long-term research goal is to provide cognitive tutoring of collaboration within a collaborative software environment. This is a challenging goal, as intelligent tutors have traditionally focused on cognitive skills, rather than on the skills necessary to collaborate successfully. In this paper, we describe progress we have made toward this goal. Our first step was to devise a process known as bootstrapping novice data (BND), in which student problem-solving actions are collected and used to begin the development of a tutor. Next, we implemented BND by integrating a collaborative software tool, Cool Modes, with software designed to develop cognitive tutors (i.e., the cognitive tutor authoring tools). Our initial implementation of BND provides a means to directly capture data as a foundation for a collaboration tutor but does not yet fully support tutoring. Our next step was to perform two exploratory studies in which dyads of students used our integrated BND software to collaborate in solving modeling tasks. The data collected from these studies led us to identify five dimensions of collaborative and problem-solving behavior that point to the need for abstraction of student actions to better recognize, analyze, and provide feedback on collaboration. We also interviewed a domain expert who provided evidence for the advantage of bootstrapping over manual creation of a collaboration tutor. We discuss plans to use these analyses to inform and extend our tools so that we can eventually reach our goal of tutoring collaboration.


Intelligent tutoring systems Collaborative learning Collaboration modeling Action-based analysis 


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  1. Aleven, V., McLaren, B.M., Sewall, J., Koedinger, K.R. The Cognitive Tutor Authoring Tools (CTAT): Versatile and increasingly rapid creation of tutors. Accepted for presentation at the 8th international conference on intelligent tutoring systems, Jhongli, Taiwan, 26–30 June 2006.Google Scholar
  2. Aleven, V., Sewall, J., McLaren, B.M., Koedinger, K.R. Rapid authoring of intelligent tutors for real-world and experimental use. Submitted to the 6th IEEE international conference on advanced learning technologies (ICALT 2006), Kerkrade, The Netherlands, 5–7 July 2006.Google Scholar
  3. Alfonseca, E., Carro, R.M., Martin, E., Ortigosa, A., Paredes, P. The Impact of Learning Styles on Student Grouping for Collaborative Learning: A Case Study, in this issue (2006)Google Scholar
  4. Anderson J.R., Corbett A.T., Koedinger K., Pelletier R. (1995) Cognitive tutors: lessons learned. J. Learning Sci. 4, 167–207CrossRefGoogle Scholar
  5. Aronson E., Blaney N., Stephan C., Sikes J., Snapp M. (1978) The Jigsaw Classroom. Sage Publishing Company. Beverly Hills, CAGoogle Scholar
  6. Bollen, L., Harrer, A., Hoppe, H.U. An integrated approach for analysis-based report generation. In: Kinshuk, Chee-Kit Looi, Erkki Sutinen (eds.) Proceedings of the 4th IEEE International Conference on Advanced Learning Technologies (ICALT 2004), pp. 1094–1095. Joensuu, FinlandGoogle Scholar
  7. Bransford J.D., Brown A.L., Cocking R.R. ed. (2000) How People Learn: Brain, Mind, Experience, and School. National Academy Press, Washington, DCGoogle Scholar
  8. Clark H.H., Brennan S.E. (1991). Grounding in Communication. In: Resnik L.B., Levine J.M., Teasley S.D. (eds). Perspectives on Socially Shared Cognition. American Psychological Association, Washington DC, pp. 17–149Google Scholar
  9. Corbett A., McLaughlin M., Scarpinatto K.C. (2000) Modelling student knowledge: cognitive tutors in high school and college. User Model User-Adapted Interaction 10, 81–108CrossRefGoogle Scholar
  10. Constantino-González M.A., Suthers D.D., Escamilla de los Santos J.G. (2003) Coaching web-based collaborative learning based on problem solution differences and participation. Int. J. Artificial Intelligence Education 13, 263–299Google Scholar
  11. Constantino-González, M.A., Suthers, D.D. Coaching collaboration in a computer-mediated learning environment. In: Proceedings of the Conference on Computer Supported Collaborative Learning (CSCL-02) (2002)Google Scholar
  12. Gasevic, D., Devedzic, V. Software support for teaching Petri Nets: P3. In: Proceedings of the 3rd IEEE International Conference on Advanced Learning Technologies, pp. 300–301. Athens, Greece, (2003)Google Scholar
  13. Goodman B.A., Linton F.N., Gaimari R.D., Hitzeman J.M., Ross H.J., Zarrella G. (2005). Using Dialogue Features to Predict Trouble During Collaborative Learning. User Modelling and User-Adapted Interaction, vol. 15, Springer, Berlin, pp. 85–134Google Scholar
  14. Harrer, A., Bollen, L. Klassifizierung und Analyze von Aktionen in Modellierungswerkzeugen zur Lernerunterstützung. In: Workshop-Proceedings Modellierung 2004, Marburg, 2004Google Scholar
  15. Harrer, A., McLaren, B.M., Walker, E., Bollen, L., Sewall, J. (2005). Collaboration and cognitive tutoring: integration, empirical results, and future directions. In: Proceedings of the 12th International Conference on Artificial Intelligence and Education (AIED-05), Amsterdam, the Netherlands, July 2005Google Scholar
  16. Heiner, C., Beck, J.E., Mostow, J. Lessons on using ITS data to answer educational research questions. In: Proceedings of the ITS2004 Workshop on Analyzing Student-Tutor Interaction Logs to Improve Educational Outcomes, pp. 1–9 (2004)Google Scholar
  17. Hoppe H.U., Gassner K., Mühlenbrock M., Tewissen F. (2000) Distributed visual language environments for cooperation and learning - applications and intelligent support. Group Decision Negotiation 9(3): 205–220CrossRefGoogle Scholar
  18. Introne, J., Alterman, R. Using Shared Representations to Improve Coordination and Intent Inference, this issue (2006)Google Scholar
  19. Jansen, M. Matchmaker - a framework to support collaborative java applications. In: Proceedings of the 11th International Conference on Artificial Intelligence in Education (AIED-03), IOS Press, Amsterdam (2003)Google Scholar
  20. Johnson D.W., Johnson R.T. (1990). Cooperative learning and achievement. In: Sharan S. (eds). Cooperative Learning: Theory and Research. Praeger, New York, pp. 23–37Google Scholar
  21. Koedinger, K.R., Aleven, V., Heffernan, N., McLaren, B.M., Hockenberry, M. Opening the door to non-programmers: authoring Intelligent Tutor Behavior by Demonstration. In: Proceedings of the 7th International Conference on Intelligent Tutoring Systems (ITS-2004), Maceio, Brazil (2004)Google Scholar
  22. Koedinger K.R., Anderson J.R., Hadley W.H., Mark M.A. (1997) Intelligent tutoring goes to school in the big city. Int. J. Artificial Int. Educ. 8, 30–43Google Scholar
  23. Koedinger, K.R., Junker, B. Learning factors analysis: mining student-tutor interactions to optimize instruction. Presented at Social Science Data Infrastructure Conference. New York University. 12–13, November, 1999Google Scholar
  24. Koedinger, K.R., Terao, A. A cognitive task analysis of using pictures to support pre-algebraic reasoning. In: Schunn, C.D., Gray, W. (eds.) In: Proceedings of the 24th Annual Conference of the Cognitive Science Society, pp. 542–547 (2002)Google Scholar
  25. Lesgold A., Katz S., Greenberg L., Hughes E., Eggan G. (1992). Extensions of intelligent tutoring paradigms to support collaborative learning. In: Dijkstra S., Krammer H., van Merrienboer J. (eds). Instructional Models in Computer-Based Learning Environments. Springer-Verlag, Berlin, pp. 291–311Google Scholar
  26. Lesgold, A.M., Lajoie, S.P., Bunzo, M., Eggan, G. SHERLOCK: A coached practice environment for an electronics troubleshooting job. In: Larkin, J., Chabay, R. (eds.) Computer Assisted Instruction and Intelligent Tutoring Systems. LEA, Hillsdale, NJ (1993)Google Scholar
  27. Lieberman, H. (ed.): Your Wish is My Command: Programming by Example. Morgan-Kauffman Publishers (2001)Google Scholar
  28. Mark, M. Analysis of Protocol Files: PACT Center User’s Manual. Carnegie Mellon University (1998)Google Scholar
  29. Matsuda, N., Cohen, W.W., Koedinger, K.R. Building Cognitive Tutors with Programming by Demonstration. In: Kramer, S., Pfahringer, B. (eds.) Technical report: TUM-I0510, Proceedings of the International Conference on Inductive Logic Programming, pp. 41–46. Institut fur Informatik, Technische Universitat Munchen (2005)Google Scholar
  30. McArthur D., Lewis M.W., Bishay M. (1996) ESSCOTS for learning: transforming commercial software into powerful educational tools. J. Artificial Int. Educ. 6(1): 3–33Google Scholar
  31. McLaren, B.M., Bollen, L., Walker, E., Harrer, A., Sewall, J. Cognitive tutoring of collaboration: developmental and empirical steps toward realization. In: Proceedings of the Conference on Computer Supported Collaborative Learning (CSCL-05), Taipei, Taiwan in May/June 2005.Google Scholar
  32. McLaren, B.M., Koedinger, K.R., Schneider, M., Harrer, A., Bollen, L. Bootstrapping novice data: semi-automated tutor authoring using student log files. In: Proceedings of the ITS2004 Workshop on Analyzing Student-Tutor Interaction Logs to Improve Educational Outcomes (2004a)Google Scholar
  33. McLaren B.M., Koedinger K.R., Schneider M., Harrer A., Bollen L. (2004b). Toward cognitive tutoring in a collaborative, web-based environment. In: Matera M., Comai S. (eds). Engineering Advanced Web Applications. Rinton Press, Princeton, NJ, pp. 167–179Google Scholar
  34. McManus M., Aiken R. (1995) Monitoring computer-based problem solving. J. Artif. Int. Educ. 6(4): 307–336Google Scholar
  35. Merceron, A., Yacef, K. TADA-Ed for educational data mining. Interactive Multimedia Electronic Journal of Computer-Enhanced Learning, 7(1) (2005), Scholar
  36. Mühlenbrock, M., Hoppe, H.U. A collaboration monitor for shared workspaces. In: Proceedings of the International Conference on Artificial Intelligence in Education (AIED-2001) (2001)Google Scholar
  37. Murray, T., Ainsworth, S., Blessing, S. (eds.): Authoring Tools for Advanced Technology Learning Environments: Toward Cost-Effective, Adaptive, Interactive, and Intelligent Educational Software. Kluwer Academic Publishers, Printed in the Netherlands (2003)Google Scholar
  38. Murray T. (1999) Authoring intelligent tutoring systems: an analysis of the state of the art. Int. J. Artif. Int. Educ. 10, 98–129zbMATHGoogle Scholar
  39. Nathan, M., Koedinger, K., Alibali, M. Expert blind spot: when content knowledge eclipses pedagogical content knowledge. Paper presented at the Annual Meeting of the American Educational Research Association. Seattle (2001)Google Scholar
  40. Paiva, A. Learner modelling for collaborative learning environments. In: Proceedings of the 8th International Conference on Artificial Intelligence in Education, pp. 215–222. Kobe (Japan), August (1997)Google Scholar
  41. Pinkwart, N. Collaborative modeling in graph based environments. Berlin, Germany: – Verlag im Internet (2005)Google Scholar
  42. Pinkwart, N. A Plug-In Architecture for graph based collaborative modelling systems. In: Hoppe, U., Verdejo, F., Kay, J. (eds.) Proceedings of the 11th International Conference on Artificial Intelligence in Education (AIED-03), pp. 535–536 (2003)Google Scholar
  43. Pinkwart, N., Hoppe, H.U., Bollen, L., Fuhlrott, E. Group-oriented modelling tools with heterogeneous semantics. In: Cerri, S., Gouarderes, G., Paraguacu, F. (eds.) Proceedings of the 7th International Conference on Intelligent Tutoring Systems (ITS-2004), pp. 21–30. Maceio, Brazil, Springer, Berlin (2002)Google Scholar
  44. Polson, M.C., Richardson, J.J. Foundations of Intelligent Tutoring Systems. Lawrence Erlbaum Associates Publishers (1988)Google Scholar
  45. Read, T., Barros, B., Barcena, E., Pancorbo, J. Coalescing individual and collaborative learning to model user linguistic competences, this issue (2006)Google Scholar
  46. Ritter S., Koedinger K.R. (1996) An Architecture For plug-in tutor agents. J. Artif. Int. Educ. 7(3/4): 315–347Google Scholar
  47. Searle J. Dialogue Acts An Essay in the Philosophy of Language. Cambridge University Press, LondonGoogle Scholar
  48. Slavin R.E. (1992). When and why does cooperative learning increase achievement? Theoretical and empirical perspectives. In: Hertz-Lazarowitz R., Miller N. (eds). Interaction in cooperative groups: The theoretical anatomy of group learning. Cambridge University Press, New York, pp. 145–173Google Scholar
  49. Soller, A., Lesgold, A. A computational approach to analyzing online knowledge sharing interaction. In: Proceedings of the 11th International Conference on Artificial Intelligence in Education (AIED-03), pp. 253–260. Sydney, Australia (2003)Google Scholar
  50. Spada, H., Meier, A., Rummel, N., Hauser, S. A new method to assess the quality of collaborative process in CSCL. In: Koschmann, T., Suthers, D., Chan, T.W. (eds.) Proceedings of the Conference on Computer Supported Collaborative Learning (CSCL-05), pp. 622–631. Taipei, Taiwan, Lawrence Erlbaum, Mahwah, NJ (2005)Google Scholar
  51. Stasser G., Titus W. (1985) Pooling of unshared information in group decision making: biased information sampling during discussion. J. Pers. Soc. Psychol. 48, 1467–1478CrossRefGoogle Scholar
  52. Stevens, R., Soller, A. Implementing a layered analytic approach for real-time modelling of students’ Scientific Understanding. In: Proceedings of the 12th International Conference on Artificial Intelligence and Education (AIED-05). Amsterdam, the Netherlands, July 2005 (2005)Google Scholar
  53. Suebnukarn, S., Haddawy, P. Modeling Individual and Collaborative Problem-Solving in Medical Problem-Based Learning, this issue. (2006)Google Scholar
  54. Vizcaino, A. A simulated student can improve collaborative learning. Int. J. Artif. Int. Educ. 15 (2005) 3–40, IOS Press, Amsterdan (2005)Google Scholar
  55. Walker, E., Koedinger, K.R., McLaren, B.M., Rummel, N. Cognitive tutors as research platforms: extending and established tutoring system for collaborative and metacognitive experimentation. Accepted for presentation at the 8th international conference on intelligent tutoring systems, Jhongli, Taiwan, 26–30 June 2006.Google Scholar
  56. Weinberger A., Fischer F. (2006) A framework to analyze argumentative knowledge construction in computer-supported collaborative learning. Comput. Education 46, 71–95CrossRefGoogle Scholar
  57. Wenger E. (1987) Artificial Intelligence and Tutoring Systems. Morgan Kaufmann Publishers Inc, OS Altos, CAGoogle Scholar
  58. Winograd T., Flores F. (1986) Understanding Computers and Cognition – A new Foundation for Design. Ablex Publishing Comp, New JerseyGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2006

Authors and Affiliations

  • Andreas Harrer
    • 1
    Email author
  • Bruce M. McLaren
    • 2
  • Erin Walker
    • 2
  • Lars Bollen
    • 1
  • Jonathan Sewall
    • 2
  1. 1.University Duisburg-EssenDuisburgGermany
  2. 2.Carnegie Mellon UniversityPittsburghUSA

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