Adaptive Collaboration Scripting with IMS LD

Part of the Studies in Computational Intelligence book series (SCI, volume 408)

Abstract

The IMS Learning Design specification is a widely known language that allows modelling of, amongst other learning designs, collaboration scripts in e-learning. Yet, it has been criticized for a number of shortcomings and specifically its lack of support for comprehensive adaptation features. We propose concrete extensions to the specification, which address a wide range of problems and omissions. The most important areas of modifications and amendments include: explicit representation of groups and corresponding collaboration contexts, as well as of artefacts as results of joint work; flexible integration of communication and collaboration services; a revamped script organization and sequencing model; a previously missing run-time model, with support for event- and exception- handling. The above are complemented by a wide range of adaptive interventions that can affect the script’s progress at run-time, tailor it to changing circumstances, and support learners. Last but not least, sophisticated scenarios are made possible through support for non-traditional collaboration script elements: the possibility to represent human involvement in adaptation decisions, ‘transactional’ action processing, loops and branches for controlling action execution, and the declaration of re-usable action sequences and complex expressions. Further to the proposed changes, examples are provided that highlight the novel possibilities afforded by these changes for advanced collaboration scripts.

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References

  1. 1.
    Roschelle, J., Teasley, S.D.: The construction of shared knowledge in collaborative problem solving. In: O’Malley, C. (ed.) Computer-Supported Collaborative Learning, pp. 69–97. Springer, Heidelberg (1995)CrossRefGoogle Scholar
  2. 2.
    Dillenbourg, P.: What do you mean by collaborative learning? In: Dillenbourg, P. (ed.) Collaborative-Learning: Cognitive and Computational Approaches, pp. 1–19. Elsevier, Oxford (1999)Google Scholar
  3. 3.
    Paramythis, A., Mühlbacher, J.R.: Towards New Approaches in Adaptive Support for Collaborative e-Learning. In: Proceedings of the 11th IASTED International Conference on Computers and Advanced Technology in Education (CATE 2008), pp. 95–100. ACTA Press, Crete (2008)Google Scholar
  4. 4.
    Zumbach, J., Schönemann, J., Reimann, P.: Analyzing and supporting collaboration in cooperative computer-mediated communication. In: Proceedings of the 2005 Conference on Computer Support for Collaborative Learning – Learning 2005: The Next 10 Years!, pp. 758–767. International Society of the Learning Sciences, Taipei (2005)CrossRefGoogle Scholar
  5. 5.
    Dillenbourg, P.: Over-scripting CSCL: The risks of blending collaborative learning with instructional design (2002), http://hal.archives-ouvertes.fr/hal-00190230/en/
  6. 6.
    Miao, Y., Hoeksema, K., Hoppe, H.U., Harrer, A.: CSCL Scripts: Modelling Features and Potential Use. In: Proceedings of the 2005 Conference on Computer Support for Collaborative Learning – Learning 2005: The Next 10 Years!, pp. 423–432. International Society of the Learning Sciences, Taipei (2005)CrossRefGoogle Scholar
  7. 7.
    O’Donnell, A.M., Dansereau, D.F.: Scripted Cooperation in Student Dyada: A Method for Analyzing and Enhancing Academic Learning and Performance. In: Hertz-Lazarowitz, R., Miller, N. (eds.) Interaction in Cooperative Groups: The Theoretical Anatomy of Group Learning, pp. 120–141. Cambridge University Press, London (1992)Google Scholar
  8. 8.
    IMS Global Learning Consortium, Inc.: Learning Design Specification (Version 1.0 Final Specification) (2003), http://www.imsglobal.org/learningdesign/
  9. 9.
    Pea, R.D.: The social and technological dimensions of scaffolding and related theoretical concepts for learning, education, and human activity. The Journal of the Learning Sciences 13, 423–451 (2004)CrossRefGoogle Scholar
  10. 10.
    Rummel, N., Spada, H., Hauser, S.: Learning to collaborate while being scripted or by observing a model. International Journal of Computer-Supported Collaborative Learning 4, 69–92 (2009)CrossRefGoogle Scholar
  11. 11.
    Rummel, N., Weinberger, A., Wecker, C., Fischer, F., Meier, A., Voyiatzaki, E., Kahrimanis, G., Spada, H., Avouris, N., Walker, E., Koedinger, K.R., Rosé, C.P., Kumar, R., Gweon, G., Wang, Y.-C., Joshi, M.: New challenges in CSCL: Towards adaptive script support. In: Proceedings of the 8th International Conference of the Learning Sciences, vol. 3, pp. 338–345. International Society of the Learning Sciences, Utrecht (2008)Google Scholar
  12. 12.
    Demetriadis, S., Karakostas, A.: Adaptive Collaboration Scripting: A Conceptual Framework and a Design Case Study. In: International Conference on Complex, Intelligent and Software Intensive Systems (CISIS 2008), pp. 487–492. IEEE Computer Society, Los Alamitos (2008)CrossRefGoogle Scholar
  13. 13.
    Paramythis, A.: Adaptive Support for Collaborative Learning with IMS Learning Design: Are We There Yet? In: Proceedings of the Adaptive Collaboration Support Workshop, held in Conjunction with the 5th International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems (AH 2008), pp. 17–29. L3S Research Center, Hannover (2008) Google Scholar
  14. 14.
    Caeiro, M., Anido, L., Llamas, M.: A Critical Analysis of IMS Learning Design. In: Proceedings of CSCL 2003, pp. 363–367. Kluwer Academic Publishers, Bergen (2003)Google Scholar
  15. 15.
    Torres, J., Dodero, J.M.: Analysis of Educational Metadata Supporting Complex Learning Processes. In: Sartori, F., Sicilia, M.Á., Manouselis, N. (eds.) MTSR 2009. CCIS, vol. 46, pp. 71–82. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  16. 16.
    Hagen, K., Hibbert, D., Kinshuk, P.: Developing a Learning Management System Based on the IMS Learning Design Specification. In: IEEE International Conference on Advanced Learning Technologies (ICALT 2006), pp. 420–424. IEEE Computer Society, Los Alamitos (2006)CrossRefGoogle Scholar
  17. 17.
    König, F., Paramythis, A.: Towards Improved Support for Adaptive Collaboration Scripting in IMS LD. In: Wolpers, M., Kirschner, P.A., Scheffel, M., Lindstaedt, S., Dimitrova, V. (eds.) EC-TEL 2010. LNCS, vol. 6383, pp. 197–212. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  18. 18.
    König, F., Paramythis, A.: Collaboration Contexts, Services, Events and Actions: Four Steps Closer to Adaptive Collaboration Support in IMS LD. In: International Conference on Intelligent Networking and Collaborative Systems (INCoS 2010), pp. 145–152. IEEE Computer Society, Los Alamitos (2010)CrossRefGoogle Scholar
  19. 19.
    König, F., Paramythis, A.: Closing the Circle: IMS LD Extensions for Advanced Adaptive Collaboration Support. In: International Conference on Intelligent Networking and Collaborative Systems, pp. 421–426. IEEE Computer Society, Los Alamitos (2010)CrossRefGoogle Scholar
  20. 20.
    Laurillard, D.: The pedagogical challenges to collaborative technologies. International Journal of Computer-Supported Collaborative Learning 4, 5–20 (2009)CrossRefGoogle Scholar
  21. 21.
    Soller, A., Lesgold, A.: Modeling the Process of Collaborative Learning. In: Proceedings of the International Workshop on New Technologies in Collaborative Learning (NTCL 2000), Awaji-Yumebutai, Japan (2000)Google Scholar
  22. 22.
    Gweon, G., Rose, C., Carey, R., Zaiss, Z.: Providing support for adaptive scripting in an on-line collaborative learning environment. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 251–260. ACM, Montréal (2006)CrossRefGoogle Scholar
  23. 23.
    Constantino-González, M.A., Suthers, D.D.: An approach for coaching collaboration based on difference recognition and participation tracking. In: The Role of Technology in CSCL: Studies in Technology Enhanced Collaborative Learning, pp. 87–113. Springer, Heidelberg (2007)Google Scholar
  24. 24.
    Lipponen, L.: Exploring foundations for computer-supported collaborative learning. In: Proceedings of the Conference on Computer Support for Collaborative Learning: Foundations for a CSCL Community, pp. 72–81. International Society of the Learning Sciences, Boulder (2002)CrossRefGoogle Scholar
  25. 25.
    Suthers, D.D.: Technology affordances for intersubjective learning: a thematic agenda for CSCL. In: Proceedings of the 2005 Conference on Computer Support for Collaborative Learning – Learning 2005: The Next 10 Years!, pp. 662–671. International Society of the Learning Sciences (2005)Google Scholar
  26. 26.
    Haake, J.M., Pfister, H.-R.: Flexible Scripting in Net-Based Learning Groups. In: Fischer, F., Kollar, I., Mandl, H., Haake, J.M. (eds.) Scripting Computer-Supported Collaborative Learning, pp. 155–175. Springer US, Boston (2007)CrossRefGoogle Scholar
  27. 27.
    King, A.: Scripting Collaborative Learning Processes: A Cognitive Perspective. In: Fischer, F., Kollar, I., Mandl, H., Haake, J.M. (eds.) Scripting Computer-Supported Collaborative Learning, pp. 13–37. Springer US, Boston (2007)CrossRefGoogle Scholar
  28. 28.
    Kobbe, L., Weinberger, A., Dillenbourg, P., Harrer, A., Hämäläinen, R., Häkkinen, P., Fischer, F.: Specifying computer-supported collaboration scripts. International Journal of Computer-Supported Collaborative Learning 2, 211–224 (2007)CrossRefGoogle Scholar
  29. 29.
    Dillenbourg, P., Jermann, P.: Designing Integrative Scripts. In: Fischer, F., Kollar, I., Mandl, H., Haake, J.M. (eds.) Scripting Computer-Supported Collaborative Learning, pp. 275–301. Springer US, Boston (2007)CrossRefGoogle Scholar
  30. 30.
    Häkkinen, P., Mäkitalo-Siegl, K.: Educational Perspectives on Scripting CSCL. In: Fischer, F., Kollar, I., Mandl, H., Haake, J.M. (eds.) Scripting Computer-Supported Collaborative Learning, pp. 263–271. Springer US, Boston (2007)CrossRefGoogle Scholar
  31. 31.
    Suthers, D.D.: Roles of Computational Scripts. In: Fischer, F., Kollar, I., Mandl, H., Haake, J.M. (eds.) Scripting Computer-Supported Collaborative Learning, pp. 177–187. Springer US, Boston (2007)CrossRefGoogle Scholar
  32. 32.
    Wecker, C., Fischer, F.: Fading scripts in computer-supported collaborative learning: the role of distributed monitoring. In: Proceedings of the 8th International Conference on Computer Supported Collaborative Learning, pp. 764–772. International Society of the Learning Sciences, New Brunswick (2007)CrossRefGoogle Scholar
  33. 33.
    Walker, E., Rummel, N., Koedinger, K.: CTRL: A research framework for providing adaptive collaborative learning support. User Modeling and User-Adapted Interaction 19, 387–431 (2009)CrossRefGoogle Scholar
  34. 34.
    Dillenbourg, P., Baker, M., Blaye, A., O’Malley, C.: The evolution of research on collaborative learning. In: Learning in Humans and Machine: Towards an Interdisciplinary Learning Science, pp. 189–211. Elsevier, Oxford (1996)Google Scholar
  35. 35.
    Karakostas, A., Demetriadis, S.: Adaptation patterns in systems for scripted collaboration. In: Proceedings of the 9th International Conference on Computer Supported Collaborative Learning, vol. 1, pp. 477–481. International Society of the Learning Sciences, Rhodes (2009)CrossRefGoogle Scholar
  36. 36.
    Masthoff, J.: An Exploration of Adaptive Collaboration Support. In: Paramythis, A., Weibelzahl, S. (eds.) Proceedings of the Adaptive Collaboration Support Workshop, held in Conjunction with the 5th International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems (AH 2008), pp. 5–7. L3S Research Center, Hannover (2008)Google Scholar
  37. 37.
    Dillenbourg, P., Baker, M.: Negotiation Spaces in Human-Computer Collaborative Learning. In: Proceedings of the International Conference on Cooperative Systems (COOP 1996), Juan-Les-Pins, France, pp. 187–206 (1996)Google Scholar
  38. 38.
    Miao, Y., Hoppe, U.: Adapting Process-Oriented Learning Design to Group Characteristics. In: Proceeding of the 2005 Conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology, pp. 475–482. IOS Press, Amsterdam (2005)Google Scholar
  39. 39.
    Hernández-Leo, D., Asensio-Pérez, J.I., Dimitriadis, Y.A.: Computational Representation of Collaborative Learning Flow Patterns using IMS Learning Design. Educational Technology & Society 8, 75–89 (2005)Google Scholar
  40. 40.
    Miao, Y., Burgos, D., Griffiths, D., Koper, R.: Representation of Coordination Mechanisms in IMS Learning Design to Support Group-based Learning. In: Lockyer, L., Bennett, S., Agostinho, S., Harper, B. (eds.) Handbook of Research on Learning Design and Learning Objects: Issues, Applications and Technologies, pp. 330–351. IDEA Group, Hershey (2008)CrossRefGoogle Scholar
  41. 41.
    de la Fuente Valentin, L., Miao, Y., Pardo, A., Delgado Kloos, C.: A Supporting Architecture for Generic Service Integration in IMS Learning Design. In: Times of Convergence. Technologies Across Learning Contexts. pp. 467–473 (2008)Google Scholar
  42. 42.
    Dalziel, J.: From Re-usable E-learning Content to Re-usable Learning Designs: Lessons from LAMS (2005), http://www.lamsinternational.com/CD/html/resources.html
  43. 43.
    Towle, B., Halm, M.: Designing Adaptive Learning Environments with Learning Design. In: Koper, R., Tattersall, C. (eds.) Learning Design. A Handbook on Modelling and Delivering Networked Education and Training, pp. 215–226. Springer, Heidelberg (2005)Google Scholar
  44. 44.
    Berlanga, A.J., Garcia, F.J.: A Proposal to Define Adaptive Learning Designs. In: Proceedings of the International Workshop on Applications of Semantic Web Technologies for Educational Adaptive Hypermedia (SW-EL 2004), pp. 354–358. Technische Universiteit Eindhoven, Eindhoven (2004)Google Scholar
  45. 45.
    Zarraonandia, T., Dodero, J.M., Fernández, C.: Crosscutting Runtime Adaptations of LD Execution. Educational Technology & Society 9, 123–137 (2006)Google Scholar
  46. 46.
    Paramythis, A., Cristea, A.: Towards Adaptation Languages for Adaptive Collaborative Learning Support. In: Proceedings of the First International Workshop on Individual and Group Adaptation in Collaborative Learning Environments (IGACLE 2008) held in Conjunction with the 3rd European Conference on Technology Enhanced Learning (EC-TEL 2008). CEUR Worhshop Proceedings, Maastricht, The Netherlands (2008), ISSN 1613–1673, CEUR-WS.org/Vol-384/FULLPAPER-p6.pdf
  47. 47.
    Russell, N., Arthur, van der Aalst, W., Mulyar, N.: Workflow Control-Flow Patterns: A Revised View. BPMcenter.org (2006)Google Scholar
  48. 48.
    Reinhard, W., Schweitzer, J., Völksen, G., Weber, M.: CSCW Tools: Concepts and Architectures. Computer 27, 28–36 (1994)CrossRefGoogle Scholar
  49. 49.
    Carroll, J.M., Neale, D.C., Isenhour, P.L., Rosson, M.B., McCrickard, D.S.: Notification and awareness: synchronizing task-oriented collaborative activity. International Journal of Human-Computer Studies 58, 605–632 (2003)CrossRefGoogle Scholar
  50. 50.
    Gutwin, C., Greenberg, S., Roseman, M.: Workspace Awareness in Real-Time Distributed Groupware: Framework, Widgets, and Evaluation. In: Sasse, A., Cunningham, R.J., Winder, R. (eds.) People and Computers XI (Proceedings of HCI 1996), pp. 281–298. Springer, London (1996)Google Scholar
  51. 51.
    Ellis, C.A., Gibbs, S.J., Rein, G.: Groupware: some issues and experiences. Communications of the ACM 34, 39–58 (1991)CrossRefGoogle Scholar
  52. 52.
    Ellis, C., Wainer, J.: A conceptual model of groupware. In: Proceedings of the 1994 ACM Conference on Computer Supported Cooperative Work, pp. 79–88. ACM, Chapel Hill (1994)CrossRefGoogle Scholar
  53. 53.
    Aronson, E., Blaney, N., Stephin, C., Sikes, J., Snapp, M.: The Jigsaw Classroom. Sage Publishing Company, Beverly Hills (1978)Google Scholar
  54. 54.
    Lochhead, J., Whimbey, A.: Teaching analytical reasoning through thinking aloud pair problem solving. New Directions for Teaching and Learning, 73–92 (1987)Google Scholar
  55. 55.
    Dillenbourg, P., Tchounikine, P.: Flexibility in macro-scripts for computer-supported collaborative learning. Journal of Computer Assisted Learning 23, 1–13 (2007)CrossRefGoogle Scholar
  56. 56.
    Constantino-Gonzalez, M.A., Suthers, D.D., de los Santos, J.G.E.: Coaching Web-based Collaborative Learning based on Problem Solution Differences and Participation. International Journal of Artificial Intelligence in Education 13, 263–299 (2003)Google Scholar
  57. 57.
    Totterdell, P., Rautenbach, P.: Adaptation as a problem of design. In: Browne, D., Totterdell, P., Norman, M. (eds.) Adaptive User Interfaces, pp. 59–84. Academic Press, London (1990)Google Scholar
  58. 58.
    Sakai: Sakai Project. Sakai Foundation, http://www.sakaiproject.org
  59. 59.
    Advanced Distributed Learning Initiative: Sharable Content Object Reference Model (SCORM 2004) 4th edn., Version 1.1 – Run-Time Environment (2009), http://www.adlnet.gov/Technologies/scorm/
  60. 60.
    Abel, F., Heckmann, D., Herder, E., Hidders, J., Krause, D., Leonardi, E., Van Der Slujis, K.: A Framework for Flexible User Profile Mashups. In: Proceedings of International Workshop on Adaptation and Personalization for Web 2.0 (AP-WEB 2.0 2009), CEUR Workshop Proceedings, Trento, Italy, pp. 1–10 (2009) ISSN 1613-0073. CEUR-WS.org/Vol-485/paper1.pdf
  61. 61.
    Caeiro-Rodríguez, M., Llamas-Nistal, M., Anido-Rifón, L.: Towards a Benchmark for the Evaluation of LD Expressiveness and Suitability. Journal of Interactive Media in Education, 1–14 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Institute for Information Processing and Microprocessor Technology (FIM)Johannes Kepler UniversityLinzAustria

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