Abstract
Operation Aries! is a computer environment that helps students learn about scientific methods and inquiry. The system has several components designed to optimize learning and motivation, such as game features, animated agents, natural language communication, trialogues among agents, an eBook, multimedia, and formative assessment. The present focus is on a Case Study learning module that involves critiquing reports of scientific findings in news media that have flawed scientific methodology. After the human student lists the methodological flaws of a Case Study in natural language, a teacher agent and a peer agent hold a trialogue with the student that evaluates each listed flaw and that uncovers additional flaws that that student missed.
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References
Aleven, V.: Using Background Knowledge in Case-based Legal Reasoning: A Computational Model and an Intelligent Learning Environment. A.I. 150, 183–237 (2003)
Ashley, K.D., Brüninghaus, S.: Automatically Classifying Case Texts and Predicting Outcomes. Artificial Intelligence and Law 17, 125–165 (2009)
Kolodner, J., Cox, M., Gonzalez-Calero, P.: Case-based Reasoning-inspired Approaches to Education. The Knowledge Engineering Review 20, 299–303 (2005)
Leake, D.: CBR in Context: The Present and Future. In: Case-Based Reasoning: Experiences, Lessons, and Future Directions, pp. 3–30. AAAI Press/MIT Press, Menlo Park (1996)
Schank, R.C.: Dynamic Memory Revisited. Cambridge University Press, Cambridge (2009)
Parker, L.E., Lepper, M.R.: Effects of Fantasy Contexts on Children’s Learning and Motivation: Making Learning More Fun. Jour. of Pers. and Social Psych. 62, 625–633 (1992)
Halpern, D.F.: Thought & Knowledge: An Introduction to Critical Thinking. Erlbaum, Mahwah (2003)
Cai, Z., Graesser, A.C., Millis, K.K., Halpern, D., Wallace, P., Moldovan, C., For-syth, C.: ARIES!: An Intelligent Tutoring System Assisted by Conversational Agents. In: Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling, p. 796. IOS Press, Amsterdam (2009)
Graesser, A., Chipman, P., Haynes, B., Olney, A.: AutoTutor: An Intelligent Tutoring System with Mixed-initiative Dialogue. IEEE Transactions on Education 48, 612–618 (2005)
Millis, K., Cai, Z., Graesser, A., Halpern, D., Wallace, P.: Learning Scientific In-quiry by Asking Questions in an Educational Game. In: Proceedings of World Con-ference on E-Learning in Corporate, Government, Healthcare, and Higher Educa-tion, pp. 2951–2956. AACE, Chesapeake (2009)
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Graesser, A. et al. (2010). Critiquing Media Reports with Flawed Scientific Findings: Operation ARIES! A Game with Animated Agents and Natural Language Trialogues. In: Aleven, V., Kay, J., Mostow, J. (eds) Intelligent Tutoring Systems. ITS 2010. Lecture Notes in Computer Science, vol 6095. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13437-1_60
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DOI: https://doi.org/10.1007/978-3-642-13437-1_60
Publisher Name: Springer, Berlin, Heidelberg
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