From Technology‐Challenged Teachers to Empowered Digitalized Citizens: Exploring the Profiles and Antecedents of Teacher AI Literacy in the Chinese EFL Context
От учителей, испытывающих трудности с технологиями, до наделённых силами цифровых граждан: исследование профилей и предшествующих факторов AI-грамотности преподавателей в китайском контексте изучения английского как иностранного
2025-01-27
SCID: 54.1/8qps6qrj
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AI AssessmentAI DesignAI EthicsAI KnowledgeAI UseAI literacy scaleChinese EFLMplus 7.4age and teaching experiencelatent profile analysismultinomial logistic regressionteacher AI literacy
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Abstract (AI)
ABSTRACT Artificial Intelligence (AI) literacy has come to the spotlight, empowering individuals to adeptly navigate the modern digitalised world. However, studies on teacher AI literacy in the English as a Foreign Language (EFL) context remain limited. This study aims to identify intraindividual differences in AI literacy and examine its associations with age and years of teaching experience among 782 English teachers. Given the absence of a reliable instrument to measure teacher AI literacy, we first constructed and validated a scale encompassing five sub‐scales: AI Knowledge , AI Use , AI Assessment , AI Design , and AI Ethics . Subsequently, latent profile analysis (LPA) was conducted using Mplus 7.4, with the results revealing four distinct profiles: Poor AI literacy (C1: 12.1%), Moderate AI literacy (C2: 45.5%), Good AI literacy (C3: 28.4%), and Excellent AI literacy (C4: 14.1%). Multinomial logistic regression analyses indicated significant associations between teacher AI literacy and both age and years of teaching experience. Additionally, 32 respondents participated in semi‐structured interviews. The qualitative data analysed with MAXQDA 2022 triangulated the quantitative results and offered deeper insights into teachers’ perceptions of their AI literacy. This study provides both theoretical and practical implications for understanding teacher AI literacy in the Chinese EFL context.
Key Findings
1
A five-subscale teacher AI literacy scale was developed and validated, covering AI Knowledge, AI Use, AI Assessment, AI Design, and AI Ethics.
2
Latent profile analysis of 782 English teachers identified four distinct AI literacy profiles: Poor (12.1%), Moderate (45.5%), Good (28.4%), and Excellent (14.1%).
3
Multinomial logistic regression found significant associations between teacher AI literacy profiles and both age and years of teaching experience.
4
Qualitative interviews with 32 respondents triangulated quantitative results and provided deeper insights into teachers’ perceptions of their AI literacy.
Research Object
Teacher AI literacy among Chinese EFL (English as a Foreign Language) teachers
Research Subject
Profiles, intraindividual differences, antecedents, and associations of teacher AI literacy (including five subscales: AI Knowledge, AI Use, AI Assessment, AI Design, AI Ethics) with age and years of teaching experience
Publication Details
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2025-01-27
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