Modeling English Teachers' Behavioral Intention to Use Artificial Intelligence in Middle Schools

Autor/inn/en	An, Xin; Chai, Ching Sing; Li, Yushun; Zhou, Ying; Shen, Xi; Zheng, Chunping; Chen, Mengyuan
Titel	Modeling English Teachers' Behavioral Intention to Use Artificial Intelligence in Middle Schools
Quelle	In: Education and Information Technologies, 28 (2023) 5, S.5187-5208 (22 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (An, Xin)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1360-2357
DOI	10.1007/s10639-022-11286-z
Schlagwörter	Artificial Intelligence; Middle School Teachers; English (Second Language); Language Teachers; Pedagogical Content Knowledge; Technological Literacy; Foreign Countries; China + Suchen Sie Ihr Suchwort? Künstliche Intelligenz; Middle school; Middle schools; Teacher; Teachers; Mittelschule; Mittelstufenschule; Lehrer; Lehrerin; Lehrende; English as second language; English; Second Language; Englisch als Zweitsprache; Language teacher; Sprachunterricht; Pädagogische Kompetenz; Technisches Wissen; Ausland
Abstract	Artificial intelligence (AI) provides new opportunities for K-12 English as foreign language (EFL) teachers to improve their teaching. To address the emerging trend of integrating AI into teaching, this study investigated EFL teachers' perceptions, knowledge, and behavioral intention to use AI to support teaching and learning of English in middle schools. This study combined relevant aspects of the Unified Theory of Acceptance and Use of Technology (UTAUT) and Technological Pedagogical and Content Knowledge (TPACK) as the theoretical basis. A survey was conducted in an AI education demonstration district in China. This survey adopted a 5-point Likert scale which was developed from previous research and the interview records of EFL teachers. A total of 470 valid responses were collected. The reliability and validity of the scale were satisfied with eight constructs: Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), AI language technological knowledge (AIL-TK), AI technological pedagogical knowledge (AI-TPK), AI-TPACK, and Behavioral Intention (BI). The results showed that the EFL teachers were positive with regard to the measured factors. PE, SI, AIL-TK, and AI-TPACK had significant positive predictive power on BI; and EE, FC, AI-TPK had indirect effects on BI. The complex interrelations were mapped out to provide educators and policymakers with a theoretically grounded scheme to foster teachers' BI to use AI in teaching. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01