Using HCI task modeling techniques to measure how deeply students model

Sylvie Girard; Lishan Zhang; Yoalli Hidalgo-Pontet; Kurt VanLehn; Winslow Burleson; Maria Elena Chavez-Echeagaray; Javier Gonzalez-Sanchez

doi:10.1007/978-3-642-39112-5_108

Using HCI task modeling techniques to measure how deeply students model

Sylvie Girard, Lishan Zhang, Yoalli Hidalgo-Pontet, Kurt VanLehn, Winslow Burleson, Maria Elena Chavez-Echeagaray, Javier Gonzalez-Sanchez

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

User modeling in AIED has been extended in the past decades to include affective and motivational aspects of learner's interaction in intelligent tutoring systems. In order to study those factors, various detectors have been created that classify episodes in log data as gaming, high/low effort on task, robust learning, etc. In this article, we present our method for creating a detector of shallow modeling practices within a meta-tutor instructional system. The detector was defined using HCI (human-computer interaction) task modeling as well as a coding scheme defined by human coders from past users' screen recordings of software use. The detector produced classifications of student behavior that were highly similar to classifications produced by human coders with a kappa of.925.

Original language	English (US)
Title of host publication	Artificial Intelligence in Education - 16th International Conference, AIED 2013, Proceedings
Publisher	Springer Verlag
Pages	766-769
Number of pages	4
ISBN (Print)	9783642391118
DOIs	https://doi.org/10.1007/978-3-642-39112-5_108
State	Published - 2013
Event	16th International Conference on Artificial Intelligence in Education, AIED 2013 - Memphis, TN, United States Duration: Jul 9 2013 → Jul 13 2013

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7926 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	16th International Conference on Artificial Intelligence in Education, AIED 2013
Country/Territory	United States
City	Memphis, TN
Period	7/9/13 → 7/13/13

Keywords

Human-computer interaction
Intelligent tutoring system
Robust learning
Shallow learning
Task modeling

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-39112-5_108

Cite this

Girard, S., Zhang, L., Hidalgo-Pontet, Y., VanLehn, K., Burleson, W., Chavez-Echeagaray, M. E., & Gonzalez-Sanchez, J. (2013). Using HCI task modeling techniques to measure how deeply students model. In Artificial Intelligence in Education - 16th International Conference, AIED 2013, Proceedings (pp. 766-769). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7926 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-642-39112-5_108

Using HCI task modeling techniques to measure how deeply students model. / Girard, Sylvie; Zhang, Lishan; Hidalgo-Pontet, Yoalli et al.
Artificial Intelligence in Education - 16th International Conference, AIED 2013, Proceedings. Springer Verlag, 2013. p. 766-769 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7926 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Girard, S, Zhang, L, Hidalgo-Pontet, Y, VanLehn, K, Burleson, W, Chavez-Echeagaray, ME & Gonzalez-Sanchez, J 2013, Using HCI task modeling techniques to measure how deeply students model. in Artificial Intelligence in Education - 16th International Conference, AIED 2013, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7926 LNAI, Springer Verlag, pp. 766-769, 16th International Conference on Artificial Intelligence in Education, AIED 2013, Memphis, TN, United States, 7/9/13. https://doi.org/10.1007/978-3-642-39112-5_108

Girard S, Zhang L, Hidalgo-Pontet Y, VanLehn K, Burleson W, Chavez-Echeagaray ME et al. Using HCI task modeling techniques to measure how deeply students model. In Artificial Intelligence in Education - 16th International Conference, AIED 2013, Proceedings. Springer Verlag. 2013. p. 766-769. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-39112-5_108

Girard, Sylvie ; Zhang, Lishan ; Hidalgo-Pontet, Yoalli et al. / Using HCI task modeling techniques to measure how deeply students model. Artificial Intelligence in Education - 16th International Conference, AIED 2013, Proceedings. Springer Verlag, 2013. pp. 766-769 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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AU - Chavez-Echeagaray, Maria Elena

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Using HCI task modeling techniques to measure how deeply students model

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Keywords

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