A Data-Driven Optimization Model of Important Multidimensional Factors Affecting College Students’ Cognitive Engagement in Ideological and Political Theory Course

Author:

Wang Liangliang12ORCID

Affiliation:

1. School of Marxism, Northwestern Polytechnical University, Xi’an 710072, Shaanxi, China

2. School of Marxism, Xi’an Shiyou University, Xi’an 710065, Shaanxi, China

Abstract

The optimization of important multidimensional factors is conducive to cognitive engagement, which is a crucial dimension of student engagement and plays a significant role in college students’ learning of the Ideological and Political Theory Course. However, because there are many influencing factors associated with cognitive engagement, the influence mechanism and analysis strategy of this kind of model are relatively complex. In order to solve this research gap, this paper establishes an optimization model affecting Chinese college students’ cognitive engagement in IPTC on the basis of sample collection and investigation. In this process, 4,700 questionnaires were distributed to 47 colleges and universities across the country, and copies were effectively recovered (N = 3992); the effective recovery rate was 84.94%. Cronbach’s alpha of 0.759 indicates that the scale has high reliability and Pearson’s correlation coefficient P  ≤ 0.001 shows that the scale has good validity. The KMO value of 0.703 in the Bartlett sphere test also shows that the scale is suitable for factor analysis. Firstly, according to the method of factor analysis, there are six important factor dimensions affecting college students’ cognitive engagement in the IPTC, namely, attention and motivation factor dimension, behavior and value attainment factor dimension, interest and practicality factor dimension, personality and will factor dimension, evaluation and time factor dimension, and knowledge and strategy factor dimension. Then, through descriptive analysis, it is found that personality and will factor dimension (M = 6.5837) plays a relatively major role while knowledge motivation dimension (M = 6.3505) has a weak impact on cognitive engagement. Finally, from linear regression analysis, there is a significant positive correlation between cognitive engagement and other variables. In addition, undergraduates are slightly lacking motivation in the learning of the course, and vigorously strengthening college students’ cognitive engagement is still necessary, so as to effectively enhance the effectiveness of the IPTC in the future.

Funder

Shaanxi Association of Higher Education 2019 Higher Education Scientific Research Project

Publisher

Hindawi Limited

Subject

Computer Science Applications,Software

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