An Extended Technology Model (ETAM) Framework for Understanding the Adaptation of Smart Teaching in Chinese Higher Education

Despite China’s extensive investment in “Smart Education” infrastructure, classroom adoption remains inconsistent. This study applies an Extended Technology Acceptance Model (ETAM) to examine how students and teachers in a public university perceive and adapt smart teaching technologies. A mixed-methods design was employed, involving 539 students and 53 faculty members. Data were collected through structured questionnaires measuring 9 ETAM constructs and semi-structured interviews with 15 participants. Quantitative analysis utilized descriptive statistics, correlations, and regression, while qualitative insights were derived from thematic coding. Findings highlight Perceived Usefulness (PU) as the strongest predictor of adoption. Students reported higher consensus on academic benefits (M = 4.20) compared to teachers (M = 3.91). Both groups expressed neutral views on technological and pedagogical challenges, though qualitative data revealed persistent issues such as unstable internet connectivity and limited IT support. Students emphasized user experience and ease of use, while teachers were more influenced by institutional support and social influence. The results underscore a digital divide between infrastructure availability and effective classroom integration. While smart tools enhance productivity and real-time feedback, gaps in institutional support and training hinder deeper pedagogical transformation. The proposed ETAM framework demonstrates that successful adoption requires aligning technological investment with stakeholder-specific motivations. University leaders should prioritize holistic strategies that integrate infrastructure, training, and institutional policies to ensure sustainable smart teaching practices.