Using hidden markov models to characterize student behaviors in learning-by-teaching environments

Hogyeong Jeong, Amit Gupta, Rod Roscoe, John Wagster, Gautam Biswas, Daniel Schwartz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

29 Citations (Scopus)

Abstract

Using hidden Markov models (HMMs) and traditional behavior analysis, we have examined the effect of metacognitive prompting on students' learning in the context of our computer-based learning-by-teaching environment. This paper discusses our analysis techniques, and presents evidence that HMMs can be used to effectively determine students' pattern of activities. The results indicate clear differences between different interventions, and links between students learning performance and their interactions with the system.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages614-625
Number of pages12
Volume5091 LNCS
DOIs
StatePublished - 2008
Externally publishedYes
Event9th International Conference on Intelligent Tutoring Systems, ITS 2008 - Montreal, QC, Canada
Duration: Jun 23 2008Jun 27 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5091 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other9th International Conference on Intelligent Tutoring Systems, ITS 2008
CountryCanada
CityMontreal, QC
Period6/23/086/27/08

Fingerprint

Student Learning
Hidden Markov models
Markov Model
Teaching
Students
Interaction
Learning
Context
Evidence

Keywords

  • Behavior Analysis
  • Hidden Markov modeling
  • Learning by Teaching environments
  • Metacognition

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Jeong, H., Gupta, A., Roscoe, R., Wagster, J., Biswas, G., & Schwartz, D. (2008). Using hidden markov models to characterize student behaviors in learning-by-teaching environments. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5091 LNCS, pp. 614-625). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5091 LNCS). https://doi.org/10.1007/978-3-540-69132-7-64

Using hidden markov models to characterize student behaviors in learning-by-teaching environments. / Jeong, Hogyeong; Gupta, Amit; Roscoe, Rod; Wagster, John; Biswas, Gautam; Schwartz, Daniel.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5091 LNCS 2008. p. 614-625 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5091 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Jeong, H, Gupta, A, Roscoe, R, Wagster, J, Biswas, G & Schwartz, D 2008, Using hidden markov models to characterize student behaviors in learning-by-teaching environments. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 5091 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5091 LNCS, pp. 614-625, 9th International Conference on Intelligent Tutoring Systems, ITS 2008, Montreal, QC, Canada, 6/23/08. https://doi.org/10.1007/978-3-540-69132-7-64
Jeong H, Gupta A, Roscoe R, Wagster J, Biswas G, Schwartz D. Using hidden markov models to characterize student behaviors in learning-by-teaching environments. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5091 LNCS. 2008. p. 614-625. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-540-69132-7-64
Jeong, Hogyeong ; Gupta, Amit ; Roscoe, Rod ; Wagster, John ; Biswas, Gautam ; Schwartz, Daniel. / Using hidden markov models to characterize student behaviors in learning-by-teaching environments. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5091 LNCS 2008. pp. 614-625 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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