The challenges of ideological and political education in higher education institutions in the era of big data and its path analysis

Abstract

Abstract With the continuous development of information technology, digitalization and networking have become the main features of today’s society; in such a context, ideological and political education in higher education institutions faces many challenges. In this paper, the acceptance process of ideological and political education for higher vocational students is divided into five major elements: transmission subject, acceptance subject, acceptance object, acceptance intermediary, and acceptance environment, and the interaction mechanism between the five major elements is analyzed. Secondly, it proposes to adopt the knowledge tracking of fusion learning factors (EKPT) model to decompose contradictory factors for the prior probability of curriculum fusion ideological and political knowledge matrix V and the prior probability of fusion ideological and political elements modeling students’ knowledge level tensor U. The final results of the empirical analysis of acceptance of ideological and political education based on the EKPT model show that the correlation coefficients between teaching efficacy and acceptance of ideological and political teaching behaviors range from 0.361-0.559, and the correlation coefficients between psychological strength, psychological optimism, total psychological resilience scores, and ideological and political teaching efficacy show high correlations ranging from 0.538-0.683. The research in this paper helps higher education institution’s ideological and political education to better adapt to the needs of the data era and improve students’ ideological and political quality and comprehensive literacy.