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Cited by 106Artificial Intelligence in EducationGender and Technology in EducationTeaching and Learning Programming

Factors Influencing Students' Behavioral Intention to Continue Artificial Intelligence Learning

Chai, Ching Sing, Lin, Pei-Yi, Jong, Morris Siu-yung, Dai, Yun, Chiu, Thomas K.F., Huang, Biyun·2020·2020 International Symposium on Educational Technology (ISET)
DOI 10.1109/iset49818.2020.00040
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Abstract

Artificial intelligence (AI) is increasingly employed in education for enhancing teaching practices and meeting students' learning needs. A number of AI learning opportunities in K-12 and higher education continue to grow across the world. Yet, little research has been done to investigate K-12 students' behavioral intention to learn AI. This study, which involved a sample of 131 primary students, examined the factors that affect students' behavioral intention to engage in AI learning. The exploratory factor analysis was employed to validate a four-factor survey. The general factor model includes (i) AI literacy, (ii) confidence in AI, (iii) AI for social good, and (iv) behavioral intention. The results showed that the first 3 factors were positively associated with the last factor. Students perceive the purpose of learning AI for social good as the most powerful predictor for their behavioral intention.

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Crossref · 10.1109/iset49818.2020.00040

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  • Although articles showed slight variations on the definition of AI literacy, they support the notion that everyone, especially K-12 children, acquire basic AI knowledge and abilities, enhance motivation for future career, as well as use AI-enabled technology.

    “Overall, although these articles showed slight variations on the definition of AI literacy, they support the notion that everyone, especially K-12 children, acquire basic AI knowledge and abilities, enhance motivation for future career, as well as use AI-enabled technology (Chai, Lin, et al., 2020).”

    From Conceptualizing AI literacy: An exploratory review (2021) · cites this paper as Chai, Lin, et al., 2020

  • Chai, Wang, and Xu (2020) and Chai, Lin, et al. (2020) designed a 6-item questionnaire to understand students' confidence, perceived relevance of learning AI and readiness towards AI.

    “For example, Chai, Wang, and Xu (2020) and Chai, Lin, et al. (2020) designed a 6-item questionnaire to understand students' confidence, perceived relevance of learning AI and readiness towards AI.”

    From Conceptualizing AI literacy: An exploratory review (2021) · cites this paper as Chai, Lin, et al. (2020)

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Authors
Chai, C. S., Lin, P.-Y., Jong, M. S.-Y., Dai, Y., Chiu, T. K. F., & Huang, B.
Affiliations
Chinese University of Hong Kong (HK)
ORCID
Venue
2020 International Symposium on Educational Technology (ISET)
Publisher
IEEE
Published
2020-08
Pages
147-150
DOI
10.1109/iset49818.2020.00040
OpenAlex
W3092083327
Cited by
106
References
3
Citations by year
2026: 12 · 2025: 34 · 2024: 25 · 2023: 17 · 2022: 13 · 2021: 4 · 2020: 1
FWCI
6.64
Type
conference paper
Language
en
Open access
closed
Licence
Locations
International Symposium on Educational Technology (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Social Sciences › Gender Studies › Gender and Technology in Education
  • Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
Keywords
artificial intelligence in education, behavioral intention, K-12 students, elementary school students, AI literacy, AI for social good

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