Real-time learning analytics dashboard for students in online classes

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

Abstract

In recent years, online classes have been increasingly conducted in various situations. However, in these classes, especially non-face-to-face and large-scale ones, it is more difficult for teachers and students to understand the status of the class during a lecture. To address this issue, we propose a real-time learning analytics dashboard that provides summarized information on teachers' instruction and students' learning activities during lectures. In this article, we introduce the real-time learning analytics dashboard and report its effectiveness through experiments in an online class at our university.

Original languageEnglish
Title of host publicationProceedings of 2020 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2020
EditorsHiroyuki Mitsuhara, Yoshiko Goda, Yutato Ohashi, Ma. Mercedes T. Rodrigo, Jun Shen, Neelakantam Venkatarayalu, Gary Wong, Masanori Yamada, Leon Chi-Un Lei
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages523-529
Number of pages7
ISBN (Electronic)9781728169422
DOIs
Publication statusPublished - Dec 8 2020
Event2020 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2020 - Virtual, Takamatsu, Japan
Duration: Dec 8 2020Dec 11 2020

Publication series

NameProceedings of 2020 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2020

Conference

Conference2020 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2020
CountryJapan
CityVirtual, Takamatsu
Period12/8/2012/11/20

All Science Journal Classification (ASJC) codes

  • Engineering (miscellaneous)
  • Media Technology
  • Education

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