Identifying Key Factors Influencing Teaching Quality: A Computational Pedagogy Approach

Abstract

Although previous research has explored the correlation between teacher characteristics and teaching quality, effective methods for identifying key factors that influence teaching quality are still lacking. This study aims to address this issue by developing an identification methodology based on a computational pedagogy research paradigm to identify the key characteristics of teachers and courses that influence their teaching quality. We developed quantitative models to quantify the characteristics of teaching quality, based on those identified in previous studies. Correlation and multiple correlation analyses were conducted to identify the key influencing characteristics, and grey correlation analysis was used to calculate the degree of correlation between these key characteristics and teaching quality. Our methodology was applied to 27 computer science discipline teachers and 82 courses, and validated with teaching data from eight additional teachers. Our findings demonstrate the effectiveness of our method in identifying the key influence characteristics of teachers and courses on teaching quality and confirm significant correlations between these key influential characteristics and teaching quality. This innovative approach provides new insights and tools for predicting and improving the teaching quality across disciplinary majors. Our research has significant implications for future education studies, particularly for the development of effective methods for identifying key factors that influence teaching quality. By providing a more comprehensive understanding of the key factors that influence teaching quality, our study can inform the development of evidence-based strategies to improve the teaching effectiveness for different disciplinary majors.