Abstract
Scenario-based tutoring systems influence affective states due to two distinct mechanisms during learning: (1) reactions to performance feedback and (2) responses to the scenario context or events. To explore the role of affect and engagement, a scenario-based ITS was instrumented to support unobtrusive facial affect detection. Results from a sample of university students showed relatively few traditional academic affective states such as confusion or frustration, even at decision points and after poor performance (e.g., incorrect responses). This may show evidence of “over-flow,” with a high level of engagement and interest but insufficient confusion/disequilibrium for optimal learning.
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References
Core, M.G., Georgila, K., Nye, B.D., Auerbach, D., Liu, Z.F., DiNinni, R.: Learning, adaptive support, student traits, and engagement in scenario-based learning. In: Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC) (2016)
D’Mello, S., Graesser, A.: Dynamics of affective states during complex learning. Learn. Instr. 22(2), 145–157 (2012)
Fraser, K., Ma, I., Teteris, E., Baxter, H., Wright, B., McLaughlin, K.: Emotion, cognitive load and learning outcomes during simulation training. Med. Educ. 46(11), 1055–1062 (2012)
Hays, M.J., Campbell, J.C., Trimmer, M.A., Poore, J.C., Webb, A.K., King, T.K.: Can role-play with virtual humans teach interpersonal skills? In: Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC) (2012)
Littlewort, G., Whitehill, J., Wu, T., Fasel, I., Frank, M., Movellan, J., Bartlett, M.: The computer expression recognition toolbox (CERT). In: IEEE International Conference on Automatic Face and Gesture Recognition, pp. 298–305 (2011)
Robison, J., McQuiggan, S., Lester, J.: Evaluating the consequences of affective feedback in intelligent tutoring systems. In: Affective Computing and Intelligent Interaction ACII 2009, pp. 1–6. IEEE (2009)
Rowe, J.P., Shores, L.R., Mott, B.W., Lester, J.C.: Integrating learning, problem solving, and engagement in narrative-centered learning environments. Int. J. Artif. Intell. Educ. 21(1–2), 115–133 (2011)
Acknowledgment
The effort described here is sponsored by the U.S. Army Research Laboratory (ARL) under contract number W911NF-14-D-0005. Any opinion, content or information presented does not necessarily reflect the position or the policy of the United States Government, and no official endorsement should be inferred.
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Nye, B. et al. (2017). Analyzing Learner Affect in a Scenario-Based Intelligent Tutoring System. In: André, E., Baker, R., Hu, X., Rodrigo, M., du Boulay, B. (eds) Artificial Intelligence in Education. AIED 2017. Lecture Notes in Computer Science(), vol 10331. Springer, Cham. https://doi.org/10.1007/978-3-319-61425-0_60
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DOI: https://doi.org/10.1007/978-3-319-61425-0_60
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