The construction of evaluation system of ideological and political education effect assisted by deep learning

At present, China updates the goal and pursuit of ideological and political education reform to the implementation of students’ core literacy, and since then ideological and political education has ushered in a new era of core literacy. Deep learning, as the antithesis of shallow learning, whose nurturing purpose is to cultivate future masters of social practice, is intrinsically unified with the cultivation of core literacy in ideological and political disciplines, and is an important hand in the implementation of core literacy in ideological and political disciplines in colleges and universities as well as a key focus in the evaluation of the effectiveness of ideological and political education. Based on the CIPP evaluation model, using core literature and policy documents as the resource base and Nvivo software coding, this paper initially constructs an evaluation system of ideological and political education effect with 4 first-level evaluation indexes, 10 second-level evaluation indexes and 26 third-level evaluation indexes. On this basis, after three rounds of expert consultation, the preliminary system was revised and improved through the analysis of the satisfaction data of the evaluation indicators, and the final evaluation indicator system was formulated to contain 4 first-level indicators, 10 second-level indicators and 25 third-level indicators. With the help of hierarchical analysis and MATLAB software operation, the weight coefficient of each evaluation index was determined. Finally, the research is carried out with University D as an example, the problems existing in the evaluation process are analyzed, and several optimization countermeasures are given.