Learning analytics of the relationships among learning behaviors, learning performance, and motivation

Xuewang Geng, Yufan Xu, Li Chen, Hiroaki Ogata, Atsushi Shimada, Masanori Yamada

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

Abstract

Previous research has established that motivation has a positive impact on the learning processes and behaviors [1] [2]. Learning analytics (LA) can play an important role in addressing the issue of collecting learning behaviors. In this study, we observed the teaching activities of three classes and examined the relationships among learning motivation, learning performance, and learning behaviors of students in digital learning material readers.

Original languageEnglish
Title of host publicationProceedings - IEEE 20th International Conference on Advanced Learning Technologies, ICALT 2020
EditorsMaiga Chang, Demetrios G Sampson, Ronghuai Huang, Danial Hooshyar, Nian-Shing Chen, Kinshuk Kinshuk, Margus Pedaste
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages161-163
Number of pages3
ISBN (Electronic)9781728160900
DOIs
Publication statusPublished - Jul 2020
Event20th IEEE International Conference on Advanced Learning Technologies, ICALT 2020 - Virtual, Online, Estonia
Duration: Jul 6 2020Jul 9 2020

Publication series

NameProceedings - IEEE 20th International Conference on Advanced Learning Technologies, ICALT 2020

Conference

Conference20th IEEE International Conference on Advanced Learning Technologies, ICALT 2020
CountryEstonia
CityVirtual, Online
Period7/6/207/9/20

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Safety, Risk, Reliability and Quality
  • Media Technology
  • Education

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