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Volume 8,Issue 8

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15 April 2026
Acceptance and Influencing Factors of AI-Assisted Ideological and Political Teaching among Application-oriented University Students
Xiaobang Wu ,  You Chen
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1 College of Foreign Studies, Guangdong University of Science and Technology, Dongguan 523083, Guangdong, China,
ssr 2026 , 8(3), 81–92; https://doi.org/10.26689/ssr.v8i3.14449
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Abstract

This study focuses on the acceptance of AI-assisted ideological and political teaching (IPT) by application-oriented university students and its influencing factors. Based on the Technology Acceptance Model (TAM), an integrated model incorporating situational variables such as perceived ease of use (PEOU), perceived usefulness (PU), teaching adaptability (TA), trust (TR), perceived ethical risk (PER), social influence (SI), facilitating conditions (FC), attitude (ATT) and acceptance (ACC) is constructed, and 209 valid samples are collected via questionnaire survey for empirical testing. The results demonstrate that PEOU significantly enhances PU, and both variables positively influence students’ ATT toward AI-assisted IPT. PU and ATT further contribute to students’ ACC of AI-assisted teaching. TR, SI, and FC also positively affect ATT, while PER has a negative effect. Among these factors, TR and FC demonstrate particularly strong impacts. Based on these findings, this study suggests that universities should improve the usability and pedagogical alignment of AI tools, strengthen students’ trust in AI-generated content, address ethical concerns, and offer adequate institutional support and training. This research extends the application of TAM in value-oriented educational contexts and provides practical implications for universities seeking to integrate AI technologies into ideological and political education (IPE).

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