Exploratory Study on Correlations between Students' Characteristics and Effects in the Case of Online Learning on University Students

Ryo Sugawara, Shun Okuhara, Yuki Fukuyama, Yoshikazu Sato

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

1 Citation (Scopus)

Abstract

The failure to ensure spontaneous e-learning may not, in fact, be due to structural problems in the e-learning system itself, but may rather be attributable to a gap between the instructional design of materials provided by e-learning and the learning characteristics (approaches to learning) of students. Learning of 'Low completion rate' has been brought up as one of the teething problems of e-learning. When one does e-learning is drawing great attention anew as a problem yet to be solved. In this research, we propose, put forward, test...the hypothesis. There could be students who are not suitable to e-learning because the learning effect of e-learning varies depending on the approaches to learning as a cause of poor completion rate of students and conducted verification of this hypothesis. Verification revealed that the task fulfillment rate of e-learning varies depending on the approaches to learning, which is divided into seven categories. Outcomes of our study suggest that e-learning can produce almost no learning effect when the approaches to learning do not match the suitable e-learning instructional design. This issue from results also seems to be relevant for highlighting: 'high placement test scores are relevant to the respective constant learning characteristics over the entire period of e-learning'.

Original languageEnglish
Title of host publication2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages720-722
Number of pages3
ISBN (Electronic)9781728149851
DOIs
Publication statusPublished - Feb 2020
Event2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020 - Fukuoka, Japan
Duration: Feb 19 2020Feb 21 2020

Publication series

Name2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020

Conference

Conference2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020
Country/TerritoryJapan
CityFukuoka
Period2/19/202/21/20

All Science Journal Classification (ASJC) codes

  • Information Systems and Management
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Signal Processing

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