An improved teaching behavior estimation model from student evaluations

Yusuke Kometani; Takahito Tomoto; Takehiro Furuta; Takako Akakura

doi:10.1007/978-3-319-07863-2_7

An improved teaching behavior estimation model from student evaluations

Yusuke Kometani, Takahito Tomoto, Takehiro Furuta, Takako Akakura

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

2 Citations (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 language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publisher	Springer Verlag
Pages	59-68
Number of pages	10
Volume	8522 LNCS
Edition	PART 2
ISBN (Print)	9783319078625
DOIs	https://doi.org/10.1007/978-3-319-07863-2_7
Publication status	Published - 2014
Externally published	Yes
Event	16th 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 22 → 2014 Jun 27

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	8522 LNCS
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Other

Other	16th International Conference on Human Interface and the Management of Information: Information and Knowledge Design and Evaluation, HCI International 2014
Country/Territory	Greece
City	Heraklion, Crete
Period	14/6/22 → 14/6/27

Keywords

Lesson improvement
Student evaluation
Teaching behavior
Teaching behavior estimation model

ASJC Scopus subject areas

Computer Science(all)
Theoretical Computer Science

Access to Document

10.1007/978-3-319-07863-2_7

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 et al.
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 proceeding › Conference 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). doi: 10.1007/978-3-319-07863-2_7

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

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