An improved teaching behavior estimation model from student evaluations

Yusuke Kometani, Takahito Tomoto, Takehiro Furuta, Takako Akakura

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

1 Citation (Scopus)

Abstract

Many universities conduct student evaluations. Their purpose is to encourage improvement in teaching. However, the evaluations are merely subjective assessments by students, meaning that instructors cannot necessarily easily relate evaluations to areas for improvement in teaching. To address this issue, we suggest a teaching behavior estimation model that can estimate teaching behaviors from student evaluations of each lesson. In previous research, we built a model on the assumption that teaching behaviors are not correlated with other behaviors and that student evaluation items are uncorrelated to other evaluation items. However, this assumption could not be verified. Our research suggests a new teaching behavior estimation model that represents the correlation between factors of teaching and factors of student evaluations. To analyze this, we conducted canonical correlation between two kinds of factors and obtained correlations. This result shows that it is possible to construct a teaching behavior estimation model based on factors of teaching behavior and factors of student evaluations.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages59-68
Number of pages10
Volume8522 LNCS
EditionPART 2
ISBN (Print)9783319078625
DOIs
Publication statusPublished - 2014
Externally publishedYes
Event16th International Conference on Human Interface and the Management of Information: Information and Knowledge Design and Evaluation, HCI International 2014 - Heraklion, Crete, Greece
Duration: 2014 Jun 222014 Jun 27

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume8522 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other16th International Conference on Human Interface and the Management of Information: Information and Knowledge Design and Evaluation, HCI International 2014
CountryGreece
CityHeraklion, Crete
Period14/6/2214/6/27

Fingerprint

Teaching
Students
Evaluation
Model
Canonical Correlation
Model-based
Estimate

Keywords

  • Lesson improvement
  • Student evaluation
  • Teaching behavior
  • Teaching behavior estimation model

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Kometani, Y., Tomoto, T., Furuta, T., & Akakura, T. (2014). An improved teaching behavior estimation model from student evaluations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 2 ed., Vol. 8522 LNCS, pp. 59-68). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8522 LNCS, No. PART 2). Springer Verlag. https://doi.org/10.1007/978-3-319-07863-2_7

An improved teaching behavior estimation model from student evaluations. / Kometani, Yusuke; Tomoto, Takahito; Furuta, Takehiro; Akakura, Takako.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8522 LNCS PART 2. ed. Springer Verlag, 2014. p. 59-68 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8522 LNCS, No. PART 2).

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

Kometani, Y, Tomoto, T, Furuta, T & Akakura, T 2014, An improved teaching behavior estimation model from student evaluations. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 2 edn, vol. 8522 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 8522 LNCS, Springer Verlag, pp. 59-68, 16th International Conference on Human Interface and the Management of Information: Information and Knowledge Design and Evaluation, HCI International 2014, Heraklion, Crete, Greece, 14/6/22. https://doi.org/10.1007/978-3-319-07863-2_7
Kometani Y, Tomoto T, Furuta T, Akakura T. An improved teaching behavior estimation model from student evaluations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 2 ed. Vol. 8522 LNCS. Springer Verlag. 2014. p. 59-68. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). https://doi.org/10.1007/978-3-319-07863-2_7
Kometani, Yusuke ; Tomoto, Takahito ; Furuta, Takehiro ; Akakura, Takako. / An improved teaching behavior estimation model from student evaluations. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8522 LNCS PART 2. ed. Springer Verlag, 2014. pp. 59-68 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).
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