ArticleFrontiers in psychology2026
Determinants of perceived usefulness, satisfaction and behavioral intention of using AI in lesson planning among English teachers.
Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Artificial Intelligence (AI) can help teachers plan lessons more efficiently, but it also raises concerns about increased cognitive load, loss of autonomy, and uniform lesson plans. This study aims to investigate drivers of English teacher perceived usefulness (PU), needs satisfaction (NS), and behavioral intention (BI) towards AI-assisted lesson planning tools. By integrating Technology Acceptance Model 2 (TAM2), Decomposed Technology Acceptance Model (DTAM) and Self-Determination Theory (SDT), we propose a research model positioning output quality (OQ), job relevance (JR), and result demonstrability (RD) as antecedents, PU and NS as mediators, and BI as the outcome variable. Data were collected from 485 English teachers via a questionnaire survey and data were analyzed using partial least squares structural equation modeling (PLS-SEM). The results revealed that OQ significantly enhances both PU and NS (
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