Factors Influencing University Students' AI Use and Knowledge Acquisition

Stella Xin Yin*, Dion Hoe Lian Goh

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Despite the growing emphasis on artificial intelligence (AI) education, there is relatively little research on the motivational factors that influence students' intention regarding AI knowledge acquisition and the utilization of AI applications. Understanding these factors helps educators and researchers to develop appropriate interventions to promote AI education. Guided by expectancy-value theory and theory of planned behavior, we examined how university students' beliefs influenced their motivation to learn about and engage with AI technologies. Our findings demonstrated the significant role of expectancy-value beliefs in shaping students' behavioral intention. Additionally, we identified gender differences, which can inform educators in designing gender-specific interventions to enhance female students' motivation in AI learning.

Original languageEnglish
Pages (from-to)1162-1164
Number of pages3
JournalProceedings of the Association for Information Science and Technology
Volume61
Issue number1
DOIs
Publication statusPublished - Oct 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
87 Annual Meeting of the Association for Information Science & Technology | Oct. 25 – 29, 2024 | Calgary, AB, Canada.

ASJC Scopus Subject Areas

  • General Computer Science
  • Library and Information Sciences

Keywords

  • Artificial intelligence
  • Education
  • Expectancy-value theory
  • Gender differences
  • Theory of planned behavior

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