TPACK and digital literacy among foreign language teachers in higher education institutions: a cross-sectional serial mediation analysis
Abstract
Preparing foreign language teachers for AI-assisted teaching requires instructional knowledge and critical, responsible technology use. However, the roles of technology acceptance and psychological resilience in the association between teachers’ integration knowledge and digital literacy remain insufficiently explored. Informed by the theory of planned behavior, this study examined these relationships using cross-sectional survey data from a convenience sample of 721 foreign language teachers in Chinese higher education institutions. Structural equation modeling examined a theoretically specified serial mediation model, with gender, age, academic rank, and educational attainment included as control variables for digital literacy. The literacy measure covered self-reported AI understanding, use, social impact awareness, and ethical behavior. Technological pedagogical content knowledge (TPACK) was positively associated with digital literacy. The model yielded positive indirect associations through technology acceptance and psychological resilience separately, as well as along the theoretically proposed sequence from technology acceptance to psychological resilience. These findings highlight the relevance of teachers’ technology evaluations and psychological resources alongside instructional knowledge, while distinguishing classroom integration knowledge from broader digital capabilities. The study offers a rationale for developing and evaluating professional learning that combines pedagogical knowledge, critical appraisal of AI tools, and support for managing technology-related demands.
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BibTeX
@article{zhu2026tpack,
title = {{TPACK and digital literacy among foreign language teachers in higher education institutions: a cross-sectional serial mediation analysis}},
author = {Shan Zhu and Xinyue Cao and Jiefei Hu and Zonglin Dai and Jinling Ma},
journal = {Scientific Reports},
year = {2026},
month = oct,
doi = {10.1038/s41598-026-75679-7},
url = {https://www.nature.com/articles/s41598-026-75679-7},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - TPACK and digital literacy among foreign language teachers in higher education institutions: a cross-sectional serial mediation analysis
AU - Shan Zhu
AU - Xinyue Cao
AU - Jiefei Hu
AU - Zonglin Dai
AU - Jinling Ma
PY - 2026
DA - 2026/10/13
JO - Scientific Reports
DO - 10.1038/s41598-026-75679-7
UR - https://www.nature.com/articles/s41598-026-75679-7
AB - Preparing foreign language teachers for AI-assisted teaching requires instructional knowledge and critical, responsible technology use. However, the roles of technology acceptance and psychological resilience in the association between teachers’ integration knowledge and digital literacy remain insufficiently explored. Informed by the theory of planned behavior, this study examined these relationships using cross-sectional survey data from a convenience sample of 721 foreign language teachers in Chinese higher education institutions. Structural equation modeling examined a theoretically specified serial mediation model, with gender, age, academic rank, and educational attainment included as control variables for digital literacy. The literacy measure covered self-reported AI understanding, use, social impact awareness, and ethical behavior. Technological pedagogical content knowledge (TPACK) was positively associated with digital literacy. The model yielded positive indirect associations through technology acceptance and psychological resilience separately, as well as along the theoretically proposed sequence from technology acceptance to psychological resilience. These findings highlight the relevance of teachers’ technology evaluations and psychological resources alongside instructional knowledge, while distinguishing classroom integration knowledge from broader digital capabilities. The study offers a rationale for developing and evaluating professional learning that combines pedagogical knowledge, critical appraisal of AI tools, and support for managing technology-related demands.
SN - 2045-2322
ER -