A Framework System for Intelligent Support in Open Distributed Learning Environments—a Look Back from 16 Years Later



The 1998 paper by Martin Mühlenbrock, Frank Tewissen, and myself introduced a multi-agent architecture and a component engineering approach for building open distributed learning environments to support group learning in different types of classroom settings. It took up prior work on “multiple student modeling” as a method to configure and inform group learning situations based on individually assessed learner models. Additionally, methods for detecting collaboration patterns in group action logs were introduced. The approach was exemplified with several applications in the areas of mathematics and general problems solving. The commentary traces a line of development from this work to current mobile and web-based learning architectures and approaches to action logging for interaction analysis. “Lessons learned” are discussed and briefly illustrated with examples from recent work on intelligently enhanced learning environments.


Open distributed learning environments Interaction analysis Collaboration patterns 


  1. Breuker, J. (1997). Presentation on ontologies for AIEd systems. Panel discussion. Eighth International Conference on Artificial Intelligence in Education, August 1997. Kobe, Japan.Google Scholar
  2. Bull, S., & Kay, J. (2007). Student models that invite the learner in: The SMILI:() open learner modelling framework. International Journal of Artificial Intelligence in Education, 17(2), 89–120.Google Scholar
  3. de Jong, T., van Joolingen, W. R., Giemza, A., Girault, I., Hoppe, H. U., Kindermann, J., & van der Zanden, M. (2010). Learning by creating and exchanging objects: the SCY experience. British Journal of Educational Technology, 41(6), 909–921.CrossRefGoogle Scholar
  4. Dimitrova, V., Self, J., & Brna, P. (1999). The interactive maintenance of open learner models. In S. P. Lajoie & M. Vivet (Eds.), Artificial Intelligence in Education - Proceedings of AIED’99 (pp. 405–412). Le Mans: Ios Press.Google Scholar
  5. Fidas, C., Komis, V., & Avouris, N. M. (2001). Design of collaboration-support tools for group problem solving. Proceedings of PC HCI (Patras, Greece, December 2001), pp. 263–268.Google Scholar
  6. Gelernter, D. (1985). Generative communication in Linda. ACM Transactions on Programming Languages and Systems, 7(1), 80–112.CrossRefMATHGoogle Scholar
  7. Giemza, A., Weinbrenner, S., Engler, J., & Hoppe, H. U. (2007). Tuple Spaces as a flexible integration platform for distributed learning environments. In T. Hirashima, H. U. Hoppe, & S.-C. Young (Eds.), Supporting learning flow through integrative technologies—proceedings of ICCE 2007 (pp. 313–320). Amsterdam (Netherlands): Ios Press.Google Scholar
  8. 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 Modeling and User-Adapted Interaction, 15(1–2), 85–134.CrossRefGoogle Scholar
  9. Greer, J., McCalla, G., Cooke, J., Collins, J., Kumar, V., Bishop, A., Vassileva, J., et al. (1998). The intelligent helpdesk: Supporting peer-help in a university course. In B. P. Goettl (Ed.), Intelligent tutoring systems - proceedings of ITS 1998 (pp. 494–503). Berlin-Heidelberg: Springer LNCS 1452.Google Scholar
  10. Harrer, A., Martínez-Monés, A., & Dimitracopoulou, A. (2009). Users’ data: Collaborative and social analysis. In N. Balacheff, S. Ludvigsen, T. de Jong, A. Lazonder, & S. Barnes (Eds.), Technology-enhanced learning. Principles and products (pp. 175–193). Netherlands: Springer.CrossRefGoogle Scholar
  11. Hoppe, H. U. (1994). Deductive error diagnosis and inductive error generalization for Intelligent Tutoring Systems. Journal of Artificial Intelligence in Education, 5(1), 27–49.Google Scholar
  12. Hoppe, H.U. (1995). Use of multiple student modeling to parametrize group learning. In J. Greer (ed.), Artificial intelligence in education - proceedings of AIED ‘95 (234–249). August 1995, Washington, DC (USA).Google Scholar
  13. Hoppe, H. U., & Plötzner, R. (1999). Can analytic models support learning in groups? In P. Dillenbourg (Ed.), Collaborative-learning: Cognitive and computational approaches (pp. 147–168). Amsterdam: Elsevier.Google Scholar
  14. Hoppe, H. U., Lingnau, A., Machado, I., Paiva, A., Prada, R., & Tewissen, F. (2000a). Supporting collaborative activities in computer integrated classrooms - the NIMIS approach. In Proceedings of the Sixth International Workshop on Groupware - CRIWG 2000 (pp. 94–101). Los Alamos: IEEE Press.CrossRefGoogle Scholar
  15. Hoppe, H. U., Gaßner, K., & Tewissen, F. (2000b). Distributed visual language environments for cooperation and learning: Applications and intelligent support. Group Decision and Negotiation, 9(3), 205–220.CrossRefGoogle Scholar
  16. Lesgold, A., Katz, S., Greenberg, L., Hughes, E., & Eggan, G. (1992). Extensions of intelligent tutoring paradigms to support collaborative learning. In S. Dijkstra, H. Krammer, & J. van Merrienboer (Eds.), Instructional Models in Computer-Based Learning Environments (pp. 291–311). Berlin: Springer.Google Scholar
  17. Manske, S., Hecking, T., Bollen, L., Göhnert, T., Ramos, A., & Hoppe, H.U. (2014). A flexible framework for the authoring of reusable and portable learning analytics gadgets. In Proceedings of the 14th IEEE International Conference on Advanced Learning Technologies (254–258). Athens (Greece).Google Scholar
  18. McCalla, G. (2000). The fragmentation of culture, learning, teaching, and technology: implications for the artificial intelligence in education research agenda in 2010. International Journal of Artificial Intelligence in Education, 11, 177–196.Google Scholar
  19. Mühlenbrock, M. (2001). Action Based Collaboration Analysis for Group Learning. Amsterdam: Ios Press.MATHGoogle Scholar
  20. Mühlenbrock, M., & Hoppe, H. U. (1999). Computer supported interaction analysis of group problem solving. In C. Hoadley & J. Roschelle (Eds.), Proceedings of the Conference on Computer Supported Collaborative Learning - CSCL ‘99 (pp. 398–405). Palo Alto: Erbaum.Google Scholar
  21. Mühlenbrock, M., Tewissen, F., & Hoppe, H. U. (1998). A framework system for intelligent support in open distributed learning environments. International Journal of Artificial Intelligence in Education, 9, 256–274.Google Scholar
  22. Pinkwart, N., Hoppe, H. U., Bollen, L., & Fuhlrott, E. (2002). Group-oriented modelling tools with heterogeneous semantics. In S. A. Cerri, G. Gouardéres, & F. Paraguacu (Eds.), Intelligent Tutoring Systems - Proceedings of ITS 2002 (pp. 21–30). Berlin-Heidelberg: Springer LNCS 2363.Google Scholar
  23. Pinkwart, N., Hoppe, H. U., Milrad, M., & Perez, J. (2003). Educational scenarios for cooperative use of Personal Digital Assistants. Journal of Computer Assisted Learning, 19(3), 383–391.CrossRefGoogle Scholar
  24. Ritter, S., & Koedinger, K. R. (1996). An architecture for plug-in tutor agents. International Journal of Artificial Intelligence in Education, 7(3/4), 315–347.Google Scholar
  25. Soller, A., Martínez, A., Jermann, P., & Mühlenbrock, M. (2005). From mirroring to guiding: a review of state of the art technology for supporting collaborative learning. International Journal of Artificial Intelligence in Education, 15(4), 261–290.Google Scholar
  26. Tewissen, F., Lingnau, A., & Hoppe, H. U. (2000). “Today’s Talking Typewriter” - supporting early literacy in a classroom environment. In G. Gauthier, C. Frasson, & K. VanLehn (Eds.), Intelligent Tutoring Systems - Proceedings of ITS 2000 (pp. 252–261). Berlin-Heidelberg: Springer LNCS 1839.Google Scholar
  27. Vassileva, J. (1998). Goal-based autonomous social agents supporting adaptation and teaching in a distributed environment. Proceedings of the Third International Conference on Intelligent Tutoring Systems, San Antonio, Texas. pp. 564–573.Google Scholar
  28. Wasson, B. (1998). Identifying coordination agents for collaborative telelearning. International Journal of Artificial Intelligence in Education, 9, 275–299.Google Scholar
  29. Weinbrenner, S., Engler, J., Wichmann, A., Hoppe, U., et al. (2010). Monitoring and analysing students’ systematic behaviour - The SCY pedagogical agent framework. In M. Wolpers (Ed.), Sustaining TEL: From Innovation to Learning and Practice - Proceedings of EC-TEL 2010 (pp. 602–607). Barcelona: Springer LNCS.CrossRefGoogle Scholar
  30. Wyckoff, P., McLaughry, S. W., Lehman, T. J., & Ford, D. A. (1998). T Spaces. IBM Systems Journal, 37(3), 454–474.CrossRefGoogle Scholar

Copyright information

© International Artificial Intelligence in Education Society 2015

Authors and Affiliations

  1. 1.COLLIDE Research Group - Department of Computer Science and Applied Cognitive ScienceUniversity of Duisburg-EssenEssenGermany

Personalised recommendations