Factors influencing student engagement and behavioral differences based on K-means cluster analysis

Student engagement is a crucial predictor of learning outcomes. The study constructed measurement indicators primarily based on five dimensions: learning beliefs, behavioral tendencies, emotional attitudes, self-efficacy in learning ability, and self-efficacy in learning behavior. It collected questionnaire data from 347 students who had been promoted from junior college to undergraduate studies. The survey data were processed using correlation analysis, regression analysis, and the K-means clustering algorithm. The study found that learning attitudes and learning self-efficacy are significantly positively correlated with learning engagement and can predict student learning engagement at an 82% level; the student population is mainly divided into three types: proactive explorers, passive obstacles, and general passives, with proportions of 32.56%, 26.51%, and 40.92%, respectively; the three different types of student groups show significant differences in learning engagement ( p < 0.05), with proactive explorers having the highest level of learning engagement, general passives in the middle, and passive obstacles at the lowest. To enhance student engagement, it is suggested that teachers should pay attention to fostering correct learning attitudes in students, take proactive measures to enhance students’ self-efficacy in learning, and adhere to the educational concept of personalized teaching throughout the teaching process, implementing differentiated teaching strategies such as layered instruction to more effectively meet individualized student needs.