Exploring Intrinsic Motivation Types in Augmented Reality Systems: Differences in Technology Acceptance, Learning Performance, and Behavior

Xuewang Geng, Masanori Yamada

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

Abstract

This study investigated the types of intrinsic motivation of learners in augmented reality (AR) learning activities by cluster analysis. We explored the differences in technology acceptance, learning performance, and behavior among learners with different intrinsic motivation types using ANOVA and post hoc tests. The results revealed that there were three different types of intrinsically motivated learners: high intrinsically motivated learners, learners with high interest only, and learners with high choice only. The high intrinsically motivated learners were the highest in AR technology acceptance and learning performance. However, the results of the frequency of learning behaviors indicated no difference among the three different types of intrinsically motivated learners.

Original languageEnglish
Title of host publicationTALE 2021 - IEEE International Conference on Engineering, Technology and Education, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages405-411
Number of pages7
ISBN (Electronic)9781665436878
DOIs
Publication statusPublished - 2021
Event2021 IEEE International Conference on Engineering, Technology and Education, TALE 2021 - Wuhan, China
Duration: Dec 5 2021Dec 8 2021

Publication series

NameTALE 2021 - IEEE International Conference on Engineering, Technology and Education, Proceedings

Conference

Conference2021 IEEE International Conference on Engineering, Technology and Education, TALE 2021
Country/TerritoryChina
CityWuhan
Period12/5/2112/8/21

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Engineering (miscellaneous)
  • Media Technology
  • Education

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