Conati, Cristina, and Xiaohong Zhao. "Building and evaluating an intelligent pedagogical agent to improve the effectiveness of an educational game." In Proceedings of the 9th international conference on Intelligent user interfaces, pp. 6-13. ACM, 2004.
Keywords: Intelligent Agents, Educational Games, User Modeling, Dynamic Bayesian Networks.
Focus: Assist learning for children who have lost interest in math and science by using intelligent games
Terms from this paper to get familiar with: intelligent (also animated) pedagogical agent, target instructional domain, pedagogically effective,
High Level Overview: Highly entertaining games don’t always trigger learning. Introducing pedagogical agents that provide individualized instruction is explored. This paper describes an agent developed for Prime Climb, a game on number factorization. Learning to play the game does not necessarily imply learning the target instructional domain. Learning happens only when students actively build the connections between game moves and the underlying knowledge. Two main challenges for this approach are that it’s difficult to assess student’s knowledge and learning from the game and how to trigger individualized interventions without interfering with the high level of engagement. A Microsoft Agent package was added to Prime Climb to interject hints along the game play. Hints appear if the student asks for a hint, if the student performs wrong move, or if the student does a correct move but may have done it through guessing. Dynamic Bayesian Networks (DBNs) handle uncertainty. This technique shows promise in improving effectiveness, but further study needs to be done on how the agent can be used and not try to avoid interfering too much. This might be determined by having the game learn more about the student. (My take on it)
Research papers to read from this article:
2. Conati, C. and J. Fain Lehman. Toward a Model of Student Education in Microworlds. Proc. of the 15th Annual Conference of the Cognitive Science Society, 1993, Boulder, CO, U.S.A.
7. Klawe, M. When Does The Use Of Computer Games And Other Interactive Multimedia Software Help Students Learn Mathematics? NCTM Standards 2000 Technology Conference, 1998, Arlington, VA, U.S.A.
11. Randel, J.M., B.A. Morris, C.D. Wetzel, and B.V. Whitehill,
The effectiveness of games for educational purposes: A review of recent research. Simulation & Gaming, 1992, 23(3).
13. Shute, V.J., A comparison of learning environments: All that glitters..., in Computers as Cognitive Tools, S. Lajoie, P. and S. Derry, Editors, 1993, Lawrence Erlbaum Associates: Hillsdale, NJ.
Keywords: Intelligent Agents, Educational Games, User Modeling, Dynamic Bayesian Networks.
Focus: Assist learning for children who have lost interest in math and science by using intelligent games
Terms from this paper to get familiar with: intelligent (also animated) pedagogical agent, target instructional domain, pedagogically effective,
High Level Overview: Highly entertaining games don’t always trigger learning. Introducing pedagogical agents that provide individualized instruction is explored. This paper describes an agent developed for Prime Climb, a game on number factorization. Learning to play the game does not necessarily imply learning the target instructional domain. Learning happens only when students actively build the connections between game moves and the underlying knowledge. Two main challenges for this approach are that it’s difficult to assess student’s knowledge and learning from the game and how to trigger individualized interventions without interfering with the high level of engagement. A Microsoft Agent package was added to Prime Climb to interject hints along the game play. Hints appear if the student asks for a hint, if the student performs wrong move, or if the student does a correct move but may have done it through guessing. Dynamic Bayesian Networks (DBNs) handle uncertainty. This technique shows promise in improving effectiveness, but further study needs to be done on how the agent can be used and not try to avoid interfering too much. This might be determined by having the game learn more about the student. (My take on it)
Research papers to read from this article:
2. Conati, C. and J. Fain Lehman. Toward a Model of Student Education in Microworlds. Proc. of the 15th Annual Conference of the Cognitive Science Society, 1993, Boulder, CO, U.S.A.
7. Klawe, M. When Does The Use Of Computer Games And Other Interactive Multimedia Software Help Students Learn Mathematics? NCTM Standards 2000 Technology Conference, 1998, Arlington, VA, U.S.A.
11. Randel, J.M., B.A. Morris, C.D. Wetzel, and B.V. Whitehill,
The effectiveness of games for educational purposes: A review of recent research. Simulation & Gaming, 1992, 23(3).
13. Shute, V.J., A comparison of learning environments: All that glitters..., in Computers as Cognitive Tools, S. Lajoie, P. and S. Derry, Editors, 1993, Lawrence Erlbaum Associates: Hillsdale, NJ.