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AI Avatar-Based Online Learning Content Acceptance : The Predictive Roles of Expected Usefulness and Perceived Concerns

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2026, 31(10), pp.331~341
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : July 28, 2026
  • Accepted : October 8, 2026
  • Published : October 30, 2026

Hyeyeong Kim 1,  Hyojung Jung 1

1단국대학교

Accredited

ABSTRACT

This study examined how university students’ Digital Competency, Expected Usefulness, and Perceived Concerns are associated with Functional Utilization Intention and Overall Use Intention toward AI avatar-based online learning content. The main regression analyses used 245 valid cases after excluding missing data. Expected Usefulness positively predicted both Functional Utilization Intention and Overall Use Intention. Perceived Concerns did not add significant explanatory power for Functional Utilization Intention (ΔR²=.000, p=.966), but did so for Overall Use Intention (ΔR²=.048, p<.001). The coefficient difference for Perceived Concerns between the two outcome models was also significant (χ²(1)=18.32, p<.001). However, in the supplementary analysis using Preference by Learning Situation, Perceived Concerns showed a positive relationship, suggesting that concerns should not be interpreted as consistently lowering all forms of utilization intention. Because Overall Use Intention was measured with a single item, the findings should be interpreted cautiously as referring to general intention to use AI avatar-based online learning content.

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This paper was written with support from the National Research Foundation of Korea.