Digital-enabled Optimization of Ideological and Political Education-oriented Student Management: A study on the Collaborative Mechanism of Mental Health Monitoring and Ideological Literacy Cultivation

Abstract

In the context of the deep integration of digital transformation and ideological and political education, university student management faces the dual challenge of increasingly complex mental health risks and insufficient precision in ideological literacy cultivation. This study constructs a collaborative mechanism for mental health monitoring and ideological literacy development under ideological and political guidance by using multi-source data fusion and intelligent analysis. Data from academic performance, consumption behavior, social interaction, psychological assessment, and campus activity systems are integrated to build dynamic student profiles. On this basis, a mental health risk identification model and an ideological literacy development assessment model are developed to realize realtime perception, risk warning, and precise intervention for students’ mental states and educational needs. The study shows that the digital empowerment mechanism significantly improves the accuracy and timeliness of mental health crisis identification and supports the differentiated matching of ideological and political education resources. The proposed mechanism promotes the transformation of student management from experience-driven response to datasupported collaborative governance.