A crowdsourcing-based approach to assess concentration levels of students in class videos

Hu Cheng Lee, Chao Lin Wu, Ling Jyh Chen

Research output: Contribution to conferencePaper

1 Citation (Scopus)

Abstract

Concentration is important for students to conduct efficient learning in a class, and an effective assessment of students' concentration level in a class is useful for students to review class materials after lessons, as well as for lecturers to adjust their teaching strategies for self-improvement. Although a number of concentration assessment approaches have been proposed, conventional approaches are generally time/money expensive (e.g., expert opinions), inaccurate (e.g., computer vision-based approaches), and intrusive (e.g., wearable sensor-based approaches). In this study, we propose a novel approach, called Concentration Level Assessment System (CLAS), which combines a markovian Doze-and-Wake Model (DAWM) and the emerging crowdsourcing technique to enable effective concentration assessment of class videos. Using realistic datasets of class videos, we conduct a comprehensive set of synthetic analysis and Internet experiments, the results demonstrate that CLAS is capable of yielding an accuracy up to 98% with 86% cost savings. Moreover, CLAS is simple, effective, and scalable, and it shows promises in facilitating advanced applications for efficiency, productivity, and safety in the future.

Original languageEnglish
Pages228-233
Number of pages6
DOIs
Publication statusPublished - 2013 Jan 1
Event2013 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2013 - Taipei, Taiwan
Duration: 2013 Dec 62013 Dec 8

Other

Other2013 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2013
CountryTaiwan
CityTaipei
Period13/12/613/12/8

Keywords

  • concentration assessment
  • crowdsourcing
  • experiment

ASJC Scopus subject areas

  • Artificial Intelligence

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  • Cite this

    Lee, H. C., Wu, C. L., & Chen, L. J. (2013). A crowdsourcing-based approach to assess concentration levels of students in class videos. 228-233. Paper presented at 2013 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2013, Taipei, Taiwan. https://doi.org/10.1109/TAAI.2013.53