Abstract
To accurately model and represent student knowledge is a challenging task, and it is especially difficult for ill-defined domains, characterized by uncertainty and ambiguity. We propose a way to represent students’ positions as they analyze case studies in the Professional Ethics domain. We designed our representation with the goal not only to model students’ knowledge, but also to encourage positive behaviour in students, and increase the quality of their case analyses. As our experiment demonstrates our representation was successful in stimulating certain desired actions in students, but didn’t seem to significantly affect the quality of students’ case analyses.
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References
Goldin, I., Ashley, K., Pinkus, R.: Assessing case analyses in bioengineering ethics education: Reliability and training. In: Proceedings of International Conference on Engineering Education, San Juan, Puerto Rico (2006)
Lynch, C., Pinkwart, N., Ashley, K., Aleven, V.: What do argument diagrams tell us about students aptitude or experience? A statistical analysis in an ill-defined domain. In: Intelligent Tutoring Systems for Ill-Defined Domains: Assessment and Feedback in Ill-Defined Domains, p. 56 (2008)
Landauer, T., McNamara, D., Dennis, S., Kintsch, W.: Handbook of Latent Semantic Analysis. Lawrence Erlbaum Associates Publishers (2007)
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© 2013 Springer-Verlag Berlin Heidelberg
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Sharipova, M., McCalla, G. (2013). Modelling Students’ Knowledge of Ethics. In: Lane, H.C., Yacef, K., Mostow, J., Pavlik, P. (eds) Artificial Intelligence in Education. AIED 2013. Lecture Notes in Computer Science(), vol 7926. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39112-5_97
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DOI: https://doi.org/10.1007/978-3-642-39112-5_97
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39111-8
Online ISBN: 978-3-642-39112-5
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