Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-22T07:04:49.783Z Has data issue: false hasContentIssue false
  • English
  • Français

Agent-based systems for human learners

Published online by Cambridge University Press:  01 June 2010

Elizabeth Sklar  and
Debbie Richards
Elizabeth Sklar*
Affiliation:
Department of Computer and Information Science, Brooklyn College, and Department of Computer Science, The Graduate Center, City University of New York, Brooklyn, NY 11210, USA
Debbie Richards*
Affiliation:
Department of Computing, Division of Information and Communication Sciences, Macquarie University, Sydney NSW 2109, Australia
*
e-mail: [email protected], [email protected]
e-mail: [email protected], [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Applying intelligent agent technologies to support human learning activities has been the subject of recent work that reaches across computer science and education disciplines. This article discusses agent-based approaches that have been designed to address a range of pedagogical and/or curricular tasks. Three types of agents are identified in the literature: pedagogical agents, peer-learning agents, and demonstrating agents. Features of each type are considered, as well as the systems in which these agents are incorporated, examining common and divergent goals, system and agent architectures, and evaluation methodologies. Open issues are highlighted, and future directions for this burgeoning interdisciplinary field are suggested.

Type
Articles
Information
The Knowledge Engineering Review , Volume 25 , Issue 2 , June 2010 , pp. 111 - 135
Copyright
Copyright © Cambridge University Press 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Adobbati, R., Marshall, A. N., Scholer, A., Tejada, S., Kaminka, G. A., Schaffer, S., Sollitto, C. 2001. Gamebots: a 3d virtual world test-bed for multi-agent research. In Proceedings of the Second International Workshop on Infrastructure for Agents, MAS, and Scalable MAS, Wagner, T. & Rana, O. F. (eds). Montreal, Canada.Google Scholar
Albus, J. S., McCain, H., Lumia, R. 1987. Nasa/nbs Standard Reference Model for Telerobot Control System Architecture (nasrem). Technical report, Robot Systems Division, National Bureau of Standards, Gaithersburg, MD, USA.Google Scholar
Aldrich, C. 2003. Simulations and the Future of Learning: An Innovative (and Perhaps Revolutionary) Approach to E-Learning. Pfeiffer.Google Scholar
Anderson, J. R. 1982. Acquisition of cognitive skill. Psychology Review 89(4), 369–406.CrossRefGoogle Scholar
Anderson, T. 2005. Distance learning—social software’s killer app. In Proceedings of 17th Biennial Conference of the Open and Distance Learning Association of Australia, ODLAA: Adelaida.Google Scholar
Arkin, R. 1995. Reactive robotic systems. In Handbook of Brain Theory and Neural Networks. MIT Press.Google Scholar
Arkin, R. 1998. Behavior-based Robotics. MIT Press.Google Scholar
Arkin, R. C. 1989. Towards the unification of navigational planning and reactive control. In Proceedings of the AAAI Spring Symposium on Robot Navigation, AAAI Press, 1–5.Google Scholar
Azhar, M. Q., Goldman, R., Sklar, E. 2006. An agent-oriented behavior-based interface for educational robotics. In Proceedings of the Agent-based Systems for Human Learning (ABSHL) Workshop at AAMAS-2006, 41–46.Google Scholar
Bai, X., Black, J. 2006. Real: an agent-based learning environment. In Proceedings of the Agent-based Systems for Human Learning (ABSHL) Workshop at AAMAS-2006, 13–17.Google Scholar
Bai, X., Black, J. B., Vitale, J. 2007. Learning with the assistance of a reflective agent. In Proceedings of the Agent-based Systems for Human Learning Workshop (ABSHL) at Autonomous Agents and Multiagent Systems (AAMAS), 22–29.Google Scholar
Balabanovic, M. 1998. Learning to Surf: Multi-agent Systems for Adaptive Web Page Recomendation. PhD thesis, Stanford University.Google Scholar
Barles, J., Dras, M., Kavakli, M., Richards, D., Tychsen, A. 2005. An overview of training simulation research and systems. In Proceedings of the Agent-based Systems for Human Learning (ABSHL) Workshop at AAMAS-2005, 3–10.Google Scholar
Bartles, R. 2003. Designing Virtual Worlds. New Riders.Google Scholar
Beck, J., Stern, M., Haugsjaa, E. 1996. Applications of AI in education. Crossroads: Special Issue on Artificial Intelligence 3(1), 11–15.CrossRefGoogle Scholar
Beck, J. E. 1998. Learning to teach with a reinforcement learning agent. In Proceedings of Fifteenth National Conference on Artificial Intelligence, AAAI Press, Menlo Park, California.Google Scholar
Berners-Lee, T., Fischetti, M. 1999. Weaving the Web. Harper.Google Scholar
Blake, M. B., Butcher-Green, J. D., Doswell, J. T. 2007. Agent-mediated customized training for human learning performance enhancement. In Proceedings of the Agent-based Systems for Human Learning Workshop (ABSHL) at Autonomous Agents and Multiagent Systems (AAMAS), 80–85.Google Scholar
Blank, D. S., Kumar, D., Meeden, L., Yanco, H. 2005. Pyro: a python-based versatile programming environment for teaching robotics. Journal on Educational Resources in Computing (JERIC), Special Issue on Robotics in Undergraduate Education, Part I 3(4), 1–15.Google Scholar
Blikstein, P., Wilensky, U. 2005. Less is more: agent-based simulation as a powerful learning tool in materials science. In Proceedings of the Agent-based Systems for Human Learning (ABSHL) Workshop at AAMAS-2005, 11–18.Google Scholar
Bratman, M. E. 1987. Intentions, Plans and Practical Reason. Harvard University Press.Google Scholar
Brisson, A., Dias, J., Paiva, A. 2007. From Chinese Shadows to Interactive Shadows: building a storytelling application with autonomous shadows. In Proceedings of the Agent-based Systems for Human Learning Workshop (ABSHL) at Autonomous Agents and Multiagent Systems (AAMAS), 15–21.Google Scholar
Brooks, F. P. 1975. The Mythical Man-Month: Essays on Software Engineering. Addison-Wesley.CrossRefGoogle Scholar
Brooks, R. 1984. A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation 2(1), 14–23.CrossRefGoogle Scholar
Brown, J. S., Burton, R. B. 1978. Diagnostic models for procedural bugs in basic mathematical skills. Cognitive Science 2(2), 155–192.Google Scholar
Brunner, C., Bennett, D., Honey, M. 1998. Girls’ games and technological desire. In From Barbie to Mortal Kombat: Gender and Computer Games, Cassell, J. & Jenkins, H. (eds). MIT Press, 72–88.Google Scholar
Chu, K.-H., Goldman, R., Sklar, E. 2005. Roboxap: an agent-based educational robotics simulator. In Proceedings of the Agent-based Systems for Human Learning (ABSHL) Workshop at AAMAS-2005, 19–26.Google Scholar
Clancey, W. J. 1986. Intelligent Tutoring Systems: A Tutorial Survey. Technical Report STAN-CS-87-1174, Stanford University.Google Scholar
Conole, G. 2002. The evolving landscape of learning technology. Association for Learning Technology Journal 10, 4–18.CrossRefGoogle Scholar
Cypher, A. 1991. Eager: programming repetitive tasks by example. In Proceedings of Computer-Human Interaction (CHI), New Orleans, April 28–May 2, ACM, New York, 33–39.Google Scholar
Epstein, J. M., Axtell, R. 1996. Growing Artificial Societies: Social Science from the Bottom Up. Technical report, The Brookings Institution, Washington, DC, USA.CrossRefGoogle Scholar
Erwin, B., Cyr, M., Rogers, C. B. 2000. Lego engineer and robolab: teaching engineering with labview from kindergarten to graduate school. International Journal of Engineering Education 16(3), 181–192.Google Scholar
Fassbender, E., Richards, D. 2006. Agent-driven knowledge exchange in a 3d learning environment. In Proceedings of the Agent-based Systems for Human Learning (ABSHL) Workshop at AAMAS-2006, 59–64.Google Scholar
Feurzeig, W., Papert, S., Bloom, M., Grant, R., Solomon, C. 1970. Programming-languages as a conceptual framework for teaching mathematics. ACM SIGCUE Outlook 4(2), 13–17.CrossRefGoogle Scholar
Foner, L. 1997. Yenta: A multi-agent referral based matchmaking system. In Proceedings of the First International Conference on Autonomous Agents. ACM.Google Scholar
Galarneau, L. 2004. The elearning edge: leveraging interactive technologies in the design of engaging, effective learning experiences. In Proceedings of e-Fest 2004. Udas, K. (ed.). Wellington, New Zealand, ITP, 1–10.Google Scholar
Gamma, E., Helm, R., Johnson, R., Vlissides, J. 1995. Design Patterns: Elements of Reusable Object Oriented Software. Addison-Wesley.Google Scholar
Goldberg, D., Nichols, D., Oki, B. M., Terry, D. 1992. Using collaborative filtering to weave and information tapestry. Communications of the ACM 35(12), 61–70.CrossRefGoogle Scholar
Goldman, R. 2005. From robolab to aibo: Capturing Agent Behavior. Master’s thesis, Computer Science Department, Columbia University, New York, NY, USA.Google Scholar
Goldman, R., Eguchi, A., Sklar, E. 2004. Using educational robotics to engage inner-city students with technology. In Proceedings of the Sixth International Conference of the Learning Sciences (ICLS).Google Scholar
Hartshorn, R., Boren, S. 1990. Experiential learning of mathematics: using manipulatives. ERIC Clearinghouse on Rural Education and Small Schools ED321967, 1–7.Google Scholar
Hayden, S. C., Carrick, C., Yang, Q. 1999. Architectural design patterns for multi-agent coordination. In Proceedings of the International Conference on Agent Systems (Agents’99), ACM Press.Google Scholar
Holz, T., Dragone, M., O’Hare, G., Martin, A., Duffy, B. 2006. Mixed reality agents as museum guides. In Proceedings of the Agent-based Systems for Human Learning (ABSHL) Workshop at AAMAS-2006, 33–40.Google Scholar
ID Software 2009. http://www.idsoftware.com/business/history/Google Scholar
Inkpen, K. 1994. Gender differences in an electronic games environment. In Proceedings of ED-MEDIA 94 World Conference on Educational Multimedia and Hypermedia, 25–30 June 1994, Ottman, T. & Tomek, I. (eds). AACE.Google Scholar
Jarrold, W. L. 2007. Treating Autism with the help of artificial intelligence: a value proposition. In Proceedings of the Agent-based Systems for Human Learning Workshop (ABSHL) at Autonomous Agents and Multiagent Systems (AAMAS), 30–37.Google Scholar
Jars, I., Kabachi, N., Lamure, M. 2004. Social learning in multi-agents system: an additional step toward intelligence, lass. In Systems, Man and Cybernetics, 2004 IEEE International Conference, 6, 5542–5547. Claude Bernard Lyon I University.Google Scholar
Johnson, R. B., Onwuegbuzie, A. J. 2004. Mixed methods research: a research paradigm whose time has come. Educational Researcher 33(7), 5.CrossRefGoogle Scholar
Johnson, W. L. 1995. Pedagogical agents for virtual learning environments. In Proceedings of the International Conference on Computers in Education, Singapore, 41–48.Google Scholar
Johnson, W. L. 2001. Pedagogical agent research at carte. AI Magazine 22(4).Google Scholar
Johnson, W. L., Beal, C., Fowles-Winkler, A., Narayanan, S., Papachristou, D., Marsella, S., Vilhj, H. 2004. Training system: an interim report. In Proceedings of the International Conference on Intelligent Tutoring Sys, Springer Verlag: Berlin, 336–345.Google Scholar
Kearsley, G. 2004. Explorations in Learning and Instruction: the Theory into Practice Database. http://tip.psychology.org/index.htmlGoogle Scholar
Khandaker, N., Soh, L.-K. 2007. Formation and scaffolding human coalitions in I-MINDS – a computer-supportive collaborative learning environment. In Proceedings of the Agent-based Systems for Human Learning Workshop (ABSHL) at Autonomous Agents and Multiagent Systems (AAMAS), 69–79.Google Scholar
Kim, Y. 2005. Agent learning companions: learners expectations of the desirable characteristics. In Proceedings of the Agent-based Systems for Human Learning (ABSHL) Workshop at AAMAS-2005, 27–34.Google Scholar
Klassner, F., Anderson, S. 2003. Lego mindstorms: not just for k-12 anymore. IEEE Robotics and Automation 10(2), 12–18.CrossRefGoogle Scholar
Kolodner, J. L. 1983. Maintaining organization in a dynamic long-term memory. Cognitive Science 7(4), 243–280.Google Scholar
Kuokka, D., Harada, L. 1997. Matchmaking for information agents. In Readings in Agents. Morgan Kaufman.Google Scholar
Lang, K. 1995. Newsweeder: Learning to filter news. In Proceedings of the Twelth International Conference on Machine Learning (ICML), Morgan Kaufmann Publishers Inc., 331–339.Google Scholar
Lashkari, Y., Metral, M., Maes, P. 1994. Collaborative interface agents. In Proceedings of the Twelth National Conference on Artificial Intelligence (AAAI), Menlo Park, CA, 444–449.Google Scholar
Lave, J., Wenger, E. 1991. Situated Learning: Legitimate Peripheral Participation. Cambridge University Press.CrossRefGoogle Scholar
Lazzari, L., Mari, M., Negri, A., Poggi, A. 2005. Support remote software development in an open distributed community. In Proceedings of the Agent-based Systems for Human Learning (ABSHL) Workshop at AAMAS-2005, 68–73.Google Scholar
Lieberman, H. 1995. Letizia: an agent that assists web browsing. In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence (IJCAI), Mellish, C.S. (ed.). San mateo, CA, Kaufmann Publishers, 924–929.Google Scholar
Lin, F., Leung, S., Wen, D., Zhang, F., Kinshuk, , McGreal, R. 2007. e-Advisor: a Multi-agent system for academic advising. In Proceedings of the Agent-based Systems for Human Learning Workshop (ABSHL) at Autonomous Agents and Multiagent Systems (AAMAS), 86–94.Google Scholar
Lin, F., Zhang, F., Wen, D. 2006. Developing mas for academic advising. In Proceedings of the Agent-based Systems for Human Learning (ABSHL) Workshop at AAMAS-2006, 53–58.Google Scholar
Littman, D., Soloway, E. 1988. Evaluating itss: the cognitive science perspective. In Foundations of Intelligent Tutoring Systems. Lawrence Erlbaum Associates.Google Scholar
Logan, B., Fraser, M., Fielding, D., Benford, S., Greenhalgh, C., Herrero, P. 2002. Keeping in touch: agents reporting from collaborative virtual environments. In Artificial intelligence and interactive entertainment, papers presented at the American Association for Artificial Intelligence Symposium, Technical report SS-02-01, AAAI Press, Menlo Park, CA, USA.Google Scholar
Lucas, J. P., Wilges, B., Silveira, R. A. 2005. Inserting animated pedagogical agents inside distributed learning environments by means of fipa specifications. In Proceedings of the Agent-based Systems for Human Learning (ABSHL) Workshop at AAMAS-2005, 74–77.Google Scholar
Maes, P. 1994a. Modeling adaptive autonomous agents. Artificial Life Journal 1(1–2), 135–162.CrossRefGoogle Scholar
Maes, P. 1994b. Modeling adaptive autonomous agents. Artificial Life: An Overview.Google Scholar
Mahmood, A. K., Ferneley, E. 2006. The use of animated agents in e-learning environments: an exploratory interpretive case study alt-j. Research in Learning Technology 14(2), 153–168.CrossRefGoogle Scholar
Malone, T. 1981a. Toward a theory of intrinsically motivating instruction. Cognitive Science 5(4), 333–369.Google Scholar
Malone, T. 1981b. What makes computer games fun? Byte Magazine 6, 258–277.Google Scholar
Mark, M. A., Greer, J. E. 1993. Evaluation methodologies for intelligent tutoring systems. Journal of Artificial Intelligence and Education 4, 1–30.Google Scholar
Marsella, S., Johnson, W. L., LaBore, K. 2000. Interactive pedagogical drama. In Proceedings of the Fourth International Conference on Autonomous Agents. ACM Press: New York.Google Scholar
Martin, F. 1994. Circuits to Control: Learning Engineering by Designing LEGO Robots. PhD thesis, Massachusetts Institute of Technology, Cambridge, MA, USA.Google Scholar
Mataric, M. J. 1998. Behavior-based robotics as a tool for synthesis of artificial behavior and analysis of natural behavior. Trends in Cognitive Science 2(3), 82–87.CrossRefGoogle ScholarPubMed
McCalla, G. I., Greer, J. E. 1994. Granularity-based reasoning and belief revision in student models. In Student Models: The Key to Individualized Educational Systems, 39–62. Springer Verlag.Google Scholar
Mott, B., McQuiggan, S., Lee, S. 2006. Narrative-centered environment for guided exploratory learning. In Proceedings of the Agent-based Systems for Human Learning (ABSHL) Workshop at AAMAS-2006, 26–32.Google Scholar
Mowlds, F., Roche, B.-J., Mangina, E. 2006. Use of agents in e-learning to enrich students learning experiences. In Proceedings of the Agent-based Systems for Human Learning (ABSHL) Workshop at AAMAS-2006, 5–12.Google Scholar
Nilsson, N. J. 1969. A mobile automaton. In Proceedings of the 1st International Joint Conference on Artificial Intelligence (IJCAI), Walker, D. E. & Norton, L. M. (eds), May 1969, Washington, DC, William Kaufmann.Google Scholar
Nilsson, N. J. 1984. Shakey the Robot. Technical report, Artificial Intelligence Center, SRI International, Menlo Park, CA, USA.Google Scholar
North, M. J., Collier, N. T., Vos, J. R. 2006. Experiences creating three implementations of the repast agent modeling toolkit. ACM Transactions on Modeling and Computer Simulation 16(1), 1–25.CrossRefGoogle Scholar
Pacuit, E. 2007. Some comments on history based structures. The Journal of Applied Logic, 613–624.CrossRefGoogle Scholar
Papert, S. 1991. Situating constructionism. In Constructionism. Ablex Publishing.Google Scholar
Preece, J., Rogers, Y., Sharp, H., Benyon, D., Holland, S., Carey, T. 1994. Human-Computer Interaction. Addison-Wesley.Google Scholar
Pynadath, D. V., Marsella, S. C. 2005. Psychsim: modeling theory of mind with decision-theoretic agents. In Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence (IJCAI), July 30–August 5, 2005, Edinburgh, Scotland, UK, 1181–1186.Google Scholar
Repenning, A., Citrin, W. 1993. Agentsheets: applying grid-based spatial reasoning to human-computer interaction. In Proceedings of the IEEE Workshop on Visual Languages, August 24–27, 1993, Bergen, Norway.Google Scholar
Resnick, M. 1997. Turtles, Termites and Traffic Jams: Explorations in Massively Parallel Microworlds. The MIT Press.Google Scholar
Richards, D., Barles, J., Szilas, N., Kavakli, M., Dras, M. 2006. Human and software agents learning together. In Proceedings of the Agent-based Systems for Human Learning (ABSHL) Workshop at AAMAS-2006, 18–25.Google Scholar
Richards, D., Kavakli, M., Dras, M. 2005. Training for high risk situations. In Proceedings of the Agent-based Systems for Human Learning (ABSHL) Workshop at AAMAS-2005, 35–41.Google Scholar
Richards, D., Kavakli, M., Dras, M. 2007. Impacts of visualisation, interaction and immersion on learning using an agent-based training simulation. In Proceedings of the Agent-based Systems for Human Learning Workshop (ABSHL) at Autonomous Agents and Multiagent Systems (AAMAS), 57–68.Google Scholar
Rickel, J., Johnson, W. L. 1998. STEVE: a pedagogical agent for virtual reality. In Proceedings of the Second International Conference on Autonomous Agents, St. Paul, Minnepolis, USA, May 9–13, Sycara, K. P., Wooldridge, M. (eds). New York, ACM Press.Google Scholar
Roberts, D. L., Isbell, C. L. 2007. Desiderata for managers of interactive experiences: a survey of recent advances in drama management. In Proceedings of the Agent-based Systems for Human Learning Workshop (ABSHL) at Autonomous Agents and Multiagent Systems (AAMAS), 5–14.Google Scholar
Russell, S., Norvig, P. 2002. Artificial Intelligence: A Modern Approach, 2nd edn, Prentice Hall.Google Scholar
Schank, R. C. 1981. Failure-driven memory. Cognition and Brain Theory 4(1), 41–60.Google Scholar
Scott, J. 1991. Social Network Analysis: a handbook. SAGE Publications.Google Scholar
Sehaba, K., Estraillier, P. 2005. A multi-agent system for rehabilitation of children with autism. In Proceedings of the Agent-based Systems for Human Learning (ABSHL) Workshop at AAMAS-2005, 84–89.Google Scholar
Sengupta, P., Wilensky, U. 2005. Niels: an emergent multi-agent based modeling environment for learning physics. In Proceedings of the Agent-based Systems for Human Learning (ABSHL) Workshop at AAMAS-2005, 42–47.Google Scholar
Shaw, M. 1996. Some patterns for software architectures. In Proceedings of the Second Workshop on Pattern Languages for Programming. Addison Wesley.Google Scholar
Shiri, M., Aïmeur, E., Frasson, C. 1998. Student modelling by cased based reasoning. In Fourth International Conference on Intelligent Tutoring Systems (ITS-98), San Antonio, Texas, USA, August 16–19, Goettl, B. P., Half, H. M., Redfield, C. L., Shute, V. J. (eds). Lecture Notes in Computer Science 1452, 394–403. Springer.Google Scholar
Si, M., Marsella, S. C., Pynadath, D. V. 2005a. Thespian: using multi-agent fitting to craft interactive drama. In Proceedings of the 4th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), July 25–29, 2005, Utrecht, The Netherlands. Dignam, F., Dignum, V., Koenig, S., Kraus, S., Singh, M. P. & Wooldridge, M. (eds). ACM.Google Scholar
Si, M., Marsella, S. C., Pynadath, D. V. 2005b. Thespian: an architecture for interactive pedagogical drama. In Proceedings of the 2005 International Conference on Artificial Intelligence in Education (AIED): Supporting Learning through Intelligent and Socially Informed Technology. Looi, C., MeCalla, G., Bredeweg, B. & Breuker, J. (eds). Frontiers in Artificial Intelligence and Applications, 125, 592–602, Amsterdam, The Netherlands, IOS Press.Google Scholar
Sklar, E. 2000. CEL: A Framework for Enabling an Internet Learning Community. PhD thesis, Department of Computer Science, Brandeis University, Waltham, MA, USA.Google Scholar
Sklar, E. 2003. Agents for education: when too much intelligence is a bad thing. In Proceedings of the Second International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 1118–1119, ACM Press.CrossRefGoogle Scholar
Sklar, E. 2007. Software review: Netlogo, a multiagent simulation environment. Journal of Artificial Life 13(2), 303–311.CrossRefGoogle ScholarPubMed
Sklar, E., Davies, M., Co, M. S. T. 2004. SimEd: simulating education as a multiAgent system. In Proceedings of the Third International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), 998–1005. ACM Press.Google Scholar
Sklar, E., Parsons, S. 2002. RoboCupJunior: a vehicle for enhancing technical literacy. In Proceedings of the AAAI-02 Mobile Robot Workshop. AAAI Press.Google Scholar
Sklar, E., Parsons, S., Stone, P. 2005. Using robocup in university-level computer science education. Journal on Educational Resources in Computing (JERIC), Special Issue on robotics in undergraduate education, part I 4(2), 1–21.Google Scholar
Sklar, E., Richards, D. 2006. The use of agents in human learning systems. In Fifth International Conference on Autonomous Agents and Multi Agent Systems (AAMAS), Nakashima, H., Wellman, M. P., Weiss, G. & Stone, P. (eds). May 8–12, 2006, ACM, 767–774Google Scholar
Soloway, E. M., Woolf, B., Rubin, E., Barth, P. 1981. Meno-ii: an intelligent tutoring system for novice programmers. In Proceedings of the Seventh International Joint Conference on Artificial Intelligence (IJCAI), Hayes, P. J. (ed.). Vancouver, BC, Canada, Willam Kaufmann.Google Scholar
Sommerville, I. 1992. Software Engineering. Addison-Wesley.Google Scholar
Songa, K.-S., Hub, X., Olneyc, A., Graesserb, A. C. 2004. A framework of synthesizing tutoring conversation capability with web-based distance education courseware. Computers & Education 42, 375–388.CrossRefGoogle Scholar
Spoelstra, M., Sklar, E. 2007. Using simulation to model and understand group learning. In Proceedings of the Agent-based Systems for Human Learning Workshop (ABSHL) at Autonomous Agents and Multiagent Systems (AAMAS), 38–47.Google Scholar
Stone, P., Kuhlmann, G., Taylor, M. E., Liu, Y. 2005. Keepaway soccer: from machine learning testbed to benchmark. In Proceedings of RoboCup-2005: Robot Soccer World Cup IX. Springer Verlag.Google Scholar
Sun, S., Joy, M., Griffiths, N. 2005. An agent-based approach to dynamic adaptive learning. In Proceedings of the Agent-based Systems for Human Learning Workshop at AAMAS-2005, 48–58.Google Scholar
Suydam, M., Higgins, J. 1977. Activity-based learning in elementary school mathematics: Recommendations from research. ERIC Clearinghouse for Science, Mathematics, and Environmental Education ED144840, 203 pp.Google Scholar
Swartout, W., Hill, R., Gratch, J., Johnson, W. L., Kyriakakis, C., LaBore, C., Lindheim, R., Marsella, S., Miraglia, D., Moore, B., Morie, J., Rickel, J., Thiebaux, M., Tuch, L., Whitney, R., Douglas, J. 2001. Toward the holodeck: integrating graphics, sound, character and story. In Proceedings of the Fifth International Conference on Autonomous Agents, May 28–June 1, 2001, Montreal, Canada. ACM.Google Scholar
Tanaka, T., Katagami, D., Nitta, K. 2006. Advice agent for online mediator education. In Proceedings of the Agent-based Systems for Human Learning (ABSHL) Workshop at AAMAS-2006, 47–52.Google Scholar
van den Broek, E. 2005. Empathic agent technology (eat). In Proceedings of the Agent-based Systems for Human Learning (ABSHL) Workshop at AAMAS-2005, 59–67.Google Scholar
VanLehn, K. 1983. Human procedural skill acquisition: theory, model, and psychological validation. In Proceedings of the National Conference on AI, 420–423. Los Altos, CA, Morgan Kaufmann.Google Scholar
VanLehn, K., Niu, Z., Slier, S., Gertner, A. 1998. Student modeling from conventional test data: a bayesian approach without priors. In Proceedings of the 4th Intelligent Tutoring Systems Conference (ITS’98), 434–443. Springer-Verlag, Berlin, Heidelberg, GmbH & Co. K.CrossRefGoogle Scholar
Vygotsky, L. S. 1978. Mind in Society: The Development of Higher Psychological Processes. Harvard University Press.Google Scholar
Wagner, S. P. 1999. Robotics and children: science achievement and problem solving. Journal of Computing in Childhood Education 9(2), 149–192.Google Scholar
Walia, V., Byde, A., Cliff, D. 2003. Evolving Market Design in Zero-Intelligence Trader Markets. Technical report, Hewlett-Packard Research Laboratories, Bristol, England.Google Scholar
Wilensky, U. 2002. Modeling nature’s emergent patterns with multi-agent languages. In Proceedings of EuroLogo-2002, Futschek, G. (ed.). Austrian Computer Society.Google Scholar
Wilensky, U., Resnick, M. 1999. Thinking in levels: a dynamic systems perspective to making sense of the world. Journal of Science Education and Technology 8(1), 3–19.CrossRefGoogle Scholar
Wilkinson, D. 2002. The intersection of learning architecture and instructional design in e-learning. In e-Technologies in Engineering Education: Learning Outcomes Providing Future Possibilities. Lohmann, J. R. & Corradini, M. L. (eds). http://services.bepress.com/eci/etechnologies/33Google Scholar
Wooldridge, M. 2002. An Introduction to Multi-agent Systems. John Wiley and Sons.Google Scholar
Wooldridge, M., Jennings, N. R. 1995. Intelligent agents: theory and practice. Knowledge Engineering Review 10(2), 115–152.CrossRefGoogle Scholar