Perceptions of and Behavioral Intentions towards Learning Artificial Intelligence in Primary School Students
Artificial Intelligence (AI) is increasingly popular, and educators are paying increasing attention to it. For students, learning AI helps them better cope with emerging societal, technological, and environmental challenges. This theory of planned behavior (TPB)-based study developed a survey questi...
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Published in | Educational Technology & Society Vol. 24; no. 3; pp. 89 - 101 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
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International Forum of Educational Technology & Society
01.07.2021
International Forum of Educational Technology & Society |
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Abstract | Artificial Intelligence (AI) is increasingly popular, and educators are paying increasing attention to it. For students, learning AI helps them better cope with emerging societal, technological, and environmental challenges. This theory of planned behavior (TPB)-based study developed a survey questionnaire to measure behavioral intention to learn AI (n = 682) among primary school students. The questionnaire was administered online, and it measured responses to five TPB factors. The five factors were (1) self-efficacy in learning AI, (2) AI readiness, (3) perceptions of the use of AI for social good, (4) AI literacy, and (5) behavioral intention. Exploratory factor analysis and a subsequent confirmatory factor analysis were used to validate this five-factor survey. Both analyses indicated satisfactory construct validity. A structural equation model (SEM) was constructed to elucidate the factors' influence on intention to learn AI. According to the SEM, all factors could predict intention to learn AI, whether directly or indirectly. This study provides new insights for researchers and instructors who are promoting AI education in schools. |
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AbstractList | Artificial Intelligence (AI) is increasingly popular, and educators are paying increasing attention to it. For students, learning AI helps them better cope with emerging societal, technological, and environmental challenges. This theory of planned behavior (TPB)-based study developed a survey questionnaire to measure behavioral intention to learn AI (n = 682) among primary school students. The questionnaire was administered online, and it measured responses to five TPB factors. The five factors were (1) self-efficacy in learning AI, (2) AI readiness, (3) perceptions of the use of AI for social good, (4) AI literacy, and (5) behavioral intention. Exploratory factor analysis and a subsequent confirmatory factor analysis were used to validate this five-factor survey. Both analyses indicated satisfactory construct validity. A structural equation model (SEM) was constructed to elucidate the factors' influence on intention to learn AI. According to the SEM, all factors could predict intention to learn AI, whether directly or indirectly. This study provides new insights for researchers and instructors who are promoting AI education in schools. Artificial Intelligence (AI) is increasingly popular, and educators are paying increasing attention to it. For students, learning AI helps them better cope with emerging societal, technological, and environmental challenges. This theory of planned behavior (TPB)-based study developed a survey questionnaire to measure behavioral intention to learn AI (n = 682) among primary school students. The questionnaire was administered online, and it measured responses to five TPB factors. The five factors were (1) self-efficacy in learning AI, (2) AI readiness, (3) perceptions of the use of AI for social good, (4) AI literacy, and (5) behavioral intention. Exploratory factor analysis and a subsequent confirmatory factor analysis were used to validate this five-factor survey. Both analyses indicated satisfactory construct validity. A structural equation model (SEM) was constructed to elucidate the factors' influence on intention to learn AI. According to the SEM, all factors could predict intention to learn AI, whether directly or indirectly. This study provides new insights for researchers and instructors who are promoting AI education in schools. Keywords: Artificial intelligence, Self-efficacy, Readiness, Social good, Literacy, Behavioral intention |
Audience | Elementary Education Academic |
Author | Ching Sing Chai Yun Dai Thomas K. F. Chiu Jianjun Qin Pei-Yi Lin Morris Siu-Yung Jong |
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SubjectTerms | Artificial Intelligence Behavior behavioral intention Beliefs, opinions and attitudes Educational Technology Elementary School Students Foreign Countries Intention Learning Motivation Learning Readiness Literacy Public opinion readiness Self Efficacy social good Special Issue Articles Student Attitudes Study and teaching |
Title | Perceptions of and Behavioral Intentions towards Learning Artificial Intelligence in Primary School Students |
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