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BRIEF RESEARCH REPORT article

Front. Educ.

Sec. Assessment, Testing and Applied Measurement

Volume 10 - 2025 | doi: 10.3389/feduc.2025.1678302

Psychometric Validation of the Information Technology Acceptance Scale for Chinese High School Teacher

Provisionally accepted
  • Faculty of Education, Yunnan University, Kunming, China

The final, formatted version of the article will be published soon.

This study aimed to examine the psychometric properties of the Information Technology Acceptance Scale for High School Teachers, developed in Chinese and grounded in the Technology Acceptance Model (TAM). The scale measured four key constructs: perceived usefulness, perceived ease of use, attitude toward technology use, and intention to use. A total of 682 Chinese high school teachers participated by completing a paper-based questionnaire. Confirmatory factor analysis supported a refined 16-item version with a stable four-factor structure and satisfactory model fit. Internal consistency was acceptable to strong across all factors (Cronbach's α > 0.799, McDonald's ω > 0.801, construct reliability H > 0.801). Evidence for convergent and discriminant validity was obtained through analyses of average variance extracted, Heterotrait-Monotrait Ratio, and inter-construct correlations. Measurement invariance across gender was established at configural, metric, scalar, and strict levels, and latent mean differences were minimal. Structural equation modeling supported all hypothesized relationships within the TAM framework. Attitude toward use emerged as the strongest predictor of intention to use and also mediated the effects of perceived usefulness and perceived ease of use. The model explained 57.5% of the variance in intention to use. These results provide preliminary but robust psychometric support for the scale and suggest its utility in assessing Chinese high school teachers' acceptance of educational technology.

Keywords: Information technology acceptance, High school teacher, psychometric properties, Measurement invariance, latent mean comparisons

Received: 04 Aug 2025; Accepted: 16 Oct 2025.

Copyright: © 2025 DOU and Feng. 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: Gang DOU, dougang@hotmail.com

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