Factors Influencing Higher Vocational College Students' Participation in Extracurricular Activities on Their Computer Academic Performance: A Social Cognitive Perspective

Abstract

In the current era of rapid technological development, computer skills have become essential competencies in vocational education. The impact of extracurricular activities on students' academic performance in computer science has attracted considerable attention. This study used full-time junior college students participating in extracurricular activities at Quanzhou College of Technology as its sample. Based on the Social Cognitive Theory, the questionnaire survey method was used to collect data, and methods such as descriptive statistics, independent-sample t-tests, one - way ANOVA, and multiple linear regression analysis were employed to deeply explore the impacts of demographic variables, psychological factors, and environmental factors on students' computer academic performance. The research found that gender had no significant impact on students' computer academic performance; grade differences significantly affected computer scores, with third - year students achieving higher scores; non - boarding students had relatively higher scores; majors had no significant impact on scores; the types of extracurricular activities significantly affected classroom participation, and the duration of activities was positively correlated with computer academic performance. Among psychological factors, motivation and self-efficacy had significant positive effects on scores, whereas pressure did not. Among environmental factors, family support, the learning environment, and teacher quality had significant positive impacts on scores. In contrast, the impacts of campus culture and peer influence were not significant due to collinearity. This study enriches the application of the Social Cognitive Theory in the field of vocational education, provides practical guidance for educational institutions, teachers, and policymakers, and also points out directions for follow-up research, such as expanding the sample range, conducting longitudinal research, paying attention to the impacts of emerging technologies, and comprehensively considering more factors.