Promoting tacit knowledge sharing through online collaborative learning in higher education: evidence from Logit–ISM analysis

While the effects of online collaborative learning have been extensively studied, tacit knowledge sharing within this context remains underexplored. This study aims to promote tacit knowledge sharing in the context of online collaborative learning. A logit regression model and interpretive structural modeling (ISM) are employed to identify the key variables influencing college students’ tacit knowledge sharing during online collaborative learning and to uncover the hierarchical structure among these significant factors. A total of 619 valid data points were analyzed using SPSS 26.0 and MATLAB R2017a. The results indicate that 22 variables significantly affect tacit knowledge sharing and can be categorized into five hierarchical levels. For long-term planning, it is essential to establish a supportive virtual environment for tacit knowledge sharing, encompassing expressive ability, file sharing, reciprocity, virtual identity, and information selection. These represent the deep-level variables of tacit knowledge sharing. For short-term goals, attention should focus on shared empathy, status/reputation, revenue/reward, and enhanced competitiveness – direct variables that influence tacit knowledge sharing in online collaborative learning. By combining the strengths of logit regression and ISM, this study systematically examines tacit knowledge sharing in online collaborative learning environments and provides practical suggestions for its promotion.