Detecting student frustration based on handwriting behavior

Hiroki Asai; Hayato Yamana

doi:10.1145/2508468.2514718

Detecting student frustration based on handwriting behavior

Hiroki Asai, Hayato Yamana

School of Fundamental Science and Engineering

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

11 Citations (Scopus)

Abstract

Detecting states of frustration among students engaged in learning activities is critical to the success of teaching assistance tools. We examine the relationship between a student's pen activity and his/her state of frustration while solving handwritten problems. Based on a user study involving mathematics problems, we found that our detection method was able to detect student frustration with a precision of 87% and a recall of 90%. We also identified several particularly discriminative features, including writing stroke number, erased stroke number, pen activity time, and air stroke speed.

Original language	English
Title of host publication	UIST 2013 Adjunct - Adjunct Publication of the 26th Annual ACM Symposium on User Interface Software and Technology
Pages	77-78
Number of pages	2
DOIs	https://doi.org/10.1145/2508468.2514718
Publication status	Published - 2013
Event	26th Annual ACM Symposium on User Interface Software and Technology, UIST 2013 - St. Andrews, United Kingdom Duration: 2013 Oct 8 → 2013 Oct 11

Publication series

Name	UIST 2013 Adjunct - Adjunct Publication of the 26th Annual ACM Symposium on User Interface Software and Technology

Conference

Conference	26th Annual ACM Symposium on User Interface Software and Technology, UIST 2013
Country/Territory	United Kingdom
City	St. Andrews
Period	13/10/8 → 13/10/11

Keywords

digital ink
learner tracking

ASJC Scopus subject areas

Human-Computer Interaction
Software

Access to Document

10.1145/2508468.2514718

Cite this

Asai, H., & Yamana, H. (2013). Detecting student frustration based on handwriting behavior. In UIST 2013 Adjunct - Adjunct Publication of the 26th Annual ACM Symposium on User Interface Software and Technology (pp. 77-78). (UIST 2013 Adjunct - Adjunct Publication of the 26th Annual ACM Symposium on User Interface Software and Technology). https://doi.org/10.1145/2508468.2514718

Detecting student frustration based on handwriting behavior. / Asai, Hiroki; Yamana, Hayato.
UIST 2013 Adjunct - Adjunct Publication of the 26th Annual ACM Symposium on User Interface Software and Technology. 2013. p. 77-78 (UIST 2013 Adjunct - Adjunct Publication of the 26th Annual ACM Symposium on User Interface Software and Technology).

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

Asai, H & Yamana, H 2013, Detecting student frustration based on handwriting behavior. in UIST 2013 Adjunct - Adjunct Publication of the 26th Annual ACM Symposium on User Interface Software and Technology. UIST 2013 Adjunct - Adjunct Publication of the 26th Annual ACM Symposium on User Interface Software and Technology, pp. 77-78, 26th Annual ACM Symposium on User Interface Software and Technology, UIST 2013, St. Andrews, United Kingdom, 13/10/8. https://doi.org/10.1145/2508468.2514718

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Detecting student frustration based on handwriting behavior

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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