Learning Analytics with Multi-faced Data for Cybersecurity Education

Kosuke Kaneko, Toshie Igarashi, Kosetsu Kayama, Takuya Takeuchi, Takuya Suzuki, Atsushi Kawase, Tomoyuki Sunaga, Masayuki Okuhara, Koji Okamura

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

Abstract

This paper presents several learning analytics results for cybersecurity education. The results were obtained by analyzing multi-faced data; pre-/post-test data, personality data, operation logs, behavior logs, learning motivation data and free described questionnaires. These data were collected throughout a cybersecurity intensive course. This paper explains the contents of the intensive course and the analysis results. Also, this paper discusses effective instructional designs in consideration with the analysis results.

Original languageEnglish
Title of host publicationProceedings - 2020 9th International Congress on Advanced Applied Informatics, IIAI-AAI 2020
EditorsTokuro Matsuo, Kunihiko Takamatsu, Yuichi Ono, Sachio Hirokawa
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages244-249
Number of pages6
ISBN (Electronic)9781728173979
DOIs
Publication statusPublished - Sep 2020
Event9th International Congress on Advanced Applied Informatics, IIAI-AAI 2020 - Kitakyushu, Japan
Duration: Sep 1 2020Sep 15 2020

Publication series

NameProceedings - 2020 9th International Congress on Advanced Applied Informatics, IIAI-AAI 2020

Conference

Conference9th International Congress on Advanced Applied Informatics, IIAI-AAI 2020
Country/TerritoryJapan
CityKitakyushu
Period9/1/209/15/20

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Information Systems and Management

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