<p>The objective of this research was to measure the structural relationships between intelligent algorithm recommendations, data collection, student-level engagement, feedback loop and healthy social mentality. The respondents of the current study were college students in China. In this method, primary data was collected from the respondents using a self-administered questionnaire and 1752 responses were considered to analyze the data. A partial least square–structural equation model (PLS-SEM) was used to measure the findings. The study found that data collection does not affect the healthy social mentality of the students. Furthermore, it was discovered that there were significant correlations between intelligent algorithm recommendations, data collection, student-level engagement and feedback loop. The study also found the significant impact of intelligent algorithm recommendations on data collection, feedback loop and healthy social mentality of the students. Besides, student engagement level is confirmed as a significant mediator between data collection, feedback loop and healthy social mentality of students. The research contributes a novel framework to the knowledge which addresses gaps in the previous studies. The discussion of intelligent algorithm recommendations for students’ healthy social mentality in this research is novel. This research highlights the importance of intelligent algorithm recommendations for improving the healthy social mentality of college students. It is useful to deal with data management related to the students, improving student engagement and addressing feedback loops that are critical for students’ healthy social mentality.</p>