Work

Teachers’ basic psychological need satisfactions and their intentions to use generative artificial intelligence: the mediating role of engagement in professional development

Year: 2026

Type: article

Abstract: Introduction Generative artificial intelligence (GenAI) offers new opportunities for instructional innovation, yet the psychological mechanisms underlying teachers’ intentions to adopt it remain unclear. Intrinsic motivation is an important internal factor shaping teachers’ intentions to use GenAI and is closely linked to the satisfaction of their basic psychological needs. Drawing on self-determination theory (SDT), this study develops and tests a theoretical framework linking teachers’ basic psychological need satisfaction to their intention to use GenAI through intrinsic motivation and engagement in professional development. Such engagement may foster innovation in GenAI-supported teaching practices. Methods Survey data were collected from 146 teachers participating in a GenAI learning program. Structural equation modeling was used to examine the hypothesized relationships among basic psychological need satisfaction, intrinsic motivation, engagement in professional development, and intention to use GenAI. Results Perceived competence in using GenAI was significantly and positively associated with intrinsic motivation, whereas perceived autonomy and relatedness were not significantly associated with intrinsic motivation. Engagement in professional development mediated the relationship between intrinsic motivation and intention to use GenAI. Discussion These findings provide a nuanced understanding of the psychological mechanisms underlying teachers’ intentions to adopt GenAI, highlighting the roles of perceived competence, intrinsic motivation, and engagement in professional development. They also offer practical implications for supporting the integration of GenAI into teaching.

Source: Frontiers in Psychology

DOI: 10.3389/fpsyg.2026.1981507

Authors: Shuhan Yuan, Yang Yang, Guoqing Zhao, Siqi Li

Institution: Beijing Normal University

Language: English

Topic: Artificial Intelligence in Education

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $3,801