Classifying interaction behaviors of students and conversational agents through dialog analysis

Michael Procter; Robert Heller; Fuhua Lin

doi:10.1007/978-3-319-91464-0_42

Classifying interaction behaviors of students and conversational agents through dialog analysis

Michael Procter, Robert Heller, Fuhua Lin

Athabasca University

Research output: Chapter in Book/Report/Conference proceeding › Published Conference contribution › peer-review

3 Citations (Scopus)

Abstract

E-learning systems based on a conversational agent (CA) provide the basis of an intuitive and engaging interface for the student. The goal of this paper is to propose a method for detecting conversational interaction behaviors of learners and CAs, using an agent-based framework, for the purpose of improving the communication between students and CA-based intelligent tutoring systems. Our framework models both the student and the CA and uses agents to represent data sources for each. We show how the framework uses the detection of conversational behaviors to initiate interventions to improve student conversational engagement. The results of initial user testing are reported.

Original language	English
Title of host publication	Intelligent Tutoring Systems - 14th International Conference, ITS 2018, Proceedings
Editors	Julita Vassileva, Roger Nkambou, Roger Azevedo
Pages	373-379
Number of pages	7
DOIs	https://doi.org/10.1007/978-3-319-91464-0_42
Publication status	Published - 2018
Event	14th International Conference on Intelligent Tutoring Systems, ITS 2018 - Montreal, Canada Duration: 11 Jun. 2018 → 15 Jun. 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10858 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	14th International Conference on Intelligent Tutoring Systems, ITS 2018
Country/Territory	Canada
City	Montreal
Period	11/06/18 → 15/06/18

Access to Document

10.1007/978-3-319-91464-0_42

Cite this

Procter, M., Heller, R., & Lin, F. (2018). Classifying interaction behaviors of students and conversational agents through dialog analysis. In J. Vassileva, R. Nkambou, & R. Azevedo (Eds.), Intelligent Tutoring Systems - 14th International Conference, ITS 2018, Proceedings (pp. 373-379). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10858 LNCS). https://doi.org/10.1007/978-3-319-91464-0_42

Procter, Michael ; Heller, Robert ; Lin, Fuhua. / Classifying interaction behaviors of students and conversational agents through dialog analysis. Intelligent Tutoring Systems - 14th International Conference, ITS 2018, Proceedings. editor / Julita Vassileva ; Roger Nkambou ; Roger Azevedo. 2018. pp. 373-379 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{90917dea1dc34828b25903109b463504,

title = "Classifying interaction behaviors of students and conversational agents through dialog analysis",

abstract = "E-learning systems based on a conversational agent (CA) provide the basis of an intuitive and engaging interface for the student. The goal of this paper is to propose a method for detecting conversational interaction behaviors of learners and CAs, using an agent-based framework, for the purpose of improving the communication between students and CA-based intelligent tutoring systems. Our framework models both the student and the CA and uses agents to represent data sources for each. We show how the framework uses the detection of conversational behaviors to initiate interventions to improve student conversational engagement. The results of initial user testing are reported.",

author = "Michael Procter and Robert Heller and Fuhua Lin",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2018.; 14th International Conference on Intelligent Tutoring Systems, ITS 2018 ; Conference date: 11-06-2018 Through 15-06-2018",

year = "2018",

doi = "10.1007/978-3-319-91464-0_42",

language = "English",

isbn = "9783319914633",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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booktitle = "Intelligent Tutoring Systems - 14th International Conference, ITS 2018, Proceedings",

}

Procter, M, Heller, R & Lin, F 2018, Classifying interaction behaviors of students and conversational agents through dialog analysis. in J Vassileva, R Nkambou & R Azevedo (eds), Intelligent Tutoring Systems - 14th International Conference, ITS 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10858 LNCS, pp. 373-379, 14th International Conference on Intelligent Tutoring Systems, ITS 2018, Montreal, Canada, 11/06/18. https://doi.org/10.1007/978-3-319-91464-0_42

Classifying interaction behaviors of students and conversational agents through dialog analysis. / Procter, Michael; Heller, Robert ; Lin, Fuhua.
Intelligent Tutoring Systems - 14th International Conference, ITS 2018, Proceedings. ed. / Julita Vassileva; Roger Nkambou; Roger Azevedo. 2018. p. 373-379 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10858 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Published Conference contribution › peer-review

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AB - E-learning systems based on a conversational agent (CA) provide the basis of an intuitive and engaging interface for the student. The goal of this paper is to propose a method for detecting conversational interaction behaviors of learners and CAs, using an agent-based framework, for the purpose of improving the communication between students and CA-based intelligent tutoring systems. Our framework models both the student and the CA and uses agents to represent data sources for each. We show how the framework uses the detection of conversational behaviors to initiate interventions to improve student conversational engagement. The results of initial user testing are reported.

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DO - 10.1007/978-3-319-91464-0_42

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Intelligent Tutoring Systems - 14th International Conference, ITS 2018, Proceedings

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Procter M, Heller R , Lin F. Classifying interaction behaviors of students and conversational agents through dialog analysis. In Vassileva J, Nkambou R, Azevedo R, editors, Intelligent Tutoring Systems - 14th International Conference, ITS 2018, Proceedings. 2018. p. 373-379. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-91464-0_42

Classifying interaction behaviors of students and conversational agents through dialog analysis

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