ORIGINAL RESEARCH article
Front. Psychol.
Sec. Educational Psychology
Determinants of Perceived Usefulness, Satisfaction and Behavioral Intention of Using AI in Lesson Planning among English Teachers
Provisionally accepted
- 1Lishui University, Lishui, China
- 2The University of Hong Kong, Hong Kong, Hong Kong, SAR China
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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 (p< 0.001). JR and RD significantly and positively influence PU (β = 0.435, p < 0.001 for RD; β = 0.185, p < 0.001 for JR) but show no significant direct effect on NS (p > 0.05). Furthermore, both PU (β = 0.428, p < 0.001) and NS (β = 0.180, p < 0.001) directly and significantly predict BI, with NS serving as a significant mediator in the PU-BI pathway (β =0.095, p < 0.05). These findings offer a solid theoretical and empirical foundation for understanding the cognitive and psychological mechanisms underlying teachers' AI adoption behavior, and provide targeted practical implications for the design and promotion of AI educational tools.
Keywords: artificial intelligence, Behavioral Intention, English teachers, lesson planning, needs satisfaction, technology acceptance
Received: 26 Oct 2025; Accepted: 09 Feb 2026.
Copyright: © 2026 Sun, Jin and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Liangyong, Li
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