Examining Knowledge Management Factors in College Students' Acceptance of Engineering Language MOOCs: An Extended TAM Approach

Abstract

This study explores the impact of Knowledge Management (KM) factors—knowledge acquisition (KAC), knowledge storage (KST), knowledge sharing (KSH), and knowledge application (KAP)—on the acceptance of Engineering Language Massive Open Online Courses (E-LMOOCs) by English as a foreign language (EFL) learners majoring in engineering sciences at Shahid Chamran University of Ahvaz, Iran. Using the extended Technology Acceptance Model (TAM), the research assesses how these KM factors influence perceived usefulness (PU) and perceived ease of use (PEOU) of E-LMOOCs, as well as learners' behavioural intention (BI) to use them. A total of 853 responses were collected from engineering students between September 2020 and September 2024 and analysed using structural equation modelling (SEM). The results show that PEOU significantly affects PU and BI, and PU significantly influences BI, which in turn significantly impacts actual behaviour (AB). KAC significantly affects PU and PEOU, KSH significantly affects PEOU and BI (but not PU), KST affects only PEOU, and KAP significantly impacts PU. However, the hypotheses regarding KSH's effects on PU and KST's effects on PU and BI were not supported. The findings highlight the importance of PEOU and PU in driving learner acceptance of E-LMOOCs and suggest that improving KM practices, especially KAC and KAP, can enhance the effectiveness and adoption of E-LMOOCs among Iranian engineering EFL learners. This study discusses the implications of the findings and provides recommendations for further research.