The impact of attitude toward artificial intelligence on teaching satisfaction: The mediating role of teachers’ self-efficacy of teaching innovation skills among chinese faculty in Thai universities

With the expansion of Sino–Thai higher education cooperation, many Chinese faculty members are teaching in Thai universities. The integration of artificial intelligence (AI) into teaching offers opportunities for innovation but also presents challenges, especially in cross-cultural contexts. Understanding how Attitude toward Artificial Intelligence (AIA) influence Teaching Satisfaction (TS) through Teachers’ Self-Efficacy of Teaching Innovation Skills (TISE) is therefore essential. This study surveyed 475 Chinese faculty in Thai universities to examine the relationships among AIA, TISE, and TS. Structural equation modeling (SEM) was employed to assess the proposed mediation model, in which AIA was hypothesized to exert an indirect effect on TS via TISE. Reliability and validity analyses were conducted to ensure the robustness of the measurement instruments. Findings show that AIA has a weak but significant direct effect on TS (β = 0.084, p < .05), but a much stronger total effect (β = 0.441, p < .001). AIA significantly predicts TISE (β = 0.573, p < .001), and TISE strongly predicts TS (β = 0.658, p < .001). Mediation analysis indicates that TISE accounts for 81.6% of the total effect of AIA on TS, confirming a dominant partial mediation. The model demonstrates good fit indices (χ²/df = 3.959, RMSEA = 0.079, CFI = 0.936, SRMR = 0.042). Investigation of AI adoption among cross-cultural faculty represents the key contribution of this study to the literature, validating the TISE scale, and extending theoretical perspectives on faculty development. Practical recommendations include strengthening AI-related training, establishing institutional support mechanisms, and refining faculty evaluation to improve teaching satisfaction and facilitate the intelligent transformation of higher education in Thailand.

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Publication Details

Journal
Decision Science Letters
Published
2025-12-17
DOI
https://doi.org/10.5267/j.dsl.2025.9.001
Citations
1
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
2.48
Controls
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article

The impact of attitude toward artificial intelligence on teaching satisfaction: The mediating role of teachers’ self-efficacy of teaching innovation skills among chinese faculty in Thai universities

Sen Xie, Haiying Zhang, Dong Yang
1 citations
Decision Science Letters
AI in Service Interactions
2.48
article

The impact of attitude toward artificial intelligence on teaching satisfaction: The mediating role of teachers’ self-efficacy of teaching innovation skills among chinese faculty in Thai universities

Sen Xie, Haiying Zhang, Dong Yang
article en
1 citations

Abstract

With the expansion of Sino–Thai higher education cooperation, many Chinese faculty members are teaching in Thai universities. The integration of artificial intelligence (AI) into teaching offers opportunities for innovation but also presents challenges, especially in cross-cultural contexts. Understanding how Attitude toward Artificial Intelligence (AIA) influence Teaching Satisfaction (TS) through Teachers’ Self-Efficacy of Teaching Innovation Skills (TISE) is therefore essential. This study surveyed 475 Chinese faculty in Thai universities to examine the relationships among AIA, TISE, and TS. Structural equation modeling (SEM) was employed to assess the proposed mediation model, in which AIA was hypothesized to exert an indirect effect on TS via TISE. Reliability and validity analyses were conducted to ensure the robustness of the measurement instruments. Findings show that AIA has a weak but significant direct effect on TS (β = 0.084, p < .05), but a much stronger total effect (β = 0.441, p < .001). AIA significantly predicts TISE (β = 0.573, p < .001), and TISE strongly predicts TS (β = 0.658, p < .001). Mediation analysis indicates that TISE accounts for 81.6% of the total effect of AIA on TS, confirming a dominant partial mediation. The model demonstrates good fit indices (χ²/df = 3.959, RMSEA = 0.079, CFI = 0.936, SRMR = 0.042). Investigation of AI adoption among cross-cultural faculty represents the key contribution of this study to the literature, validating the TISE scale, and extending theoretical perspectives on faculty development. Practical recommendations include strengthening AI-related training, establishing institutional support mechanisms, and refining faculty evaluation to improve teaching satisfaction and facilitate the intelligent transformation of higher education in Thailand.

Decision Science LettersVol. 15(1)
Openalex Percentile: Top 8%
AI in Service Interactions
2.48
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The impact of attitude toward artificial intelligence on teaching satisfaction: The mediating role of teachers’ self-efficacy of teaching innovation skills among chinese faculty in Thai universities — Sen Xie, Haiying Zhang, et al. · Decision Science Letters (2025) | TGRS Research Map | TGRS