The Analysis of Time Management and Students’ Self-efficacy of Blended Learning: A Case Study of College English Course in the University of Science and Technology Liaoning

Abstract

Background and Aim: This study delves into the realm of time management training within an English blended learning course, focusing on its influence on student self-efficacy and its subsequent effects on learning outcomes and perceptions. Anchored in the theories of Complex Adaptive Blended Learning Systems (CABLS), Goal Setting, and Self-efficacy, the research aims to uncover the combined impact of time management and self-efficacy enhancement on students' competence, and overall learning experiences. The objective is to assess how structured time management training, when integrated with blended learning strategies, can improve students’ self-efficacy. Materials and Methods: Employing a mixed-methods approach, this study utilizes quantitative tools such as independent samples t-tests and multilinear regression analyses to evaluate the intervention's effectiveness in altering student’ self-efficacy (SE) and other factors like engagement (EN), autonomous learning (AL), teachers’ support (TS), social influence (SI), intention to use (IU) and self-efficacy (SE) levels. The intervention includes time management training facilitated through the Xuexitong Platform, aiming to leverage the advantages of blended learning. This methodological framework allows for a comprehensive analysis of the training's impact, providing a robust evaluation of changes in student engagement, autonomous learning, teachers’ support, social influence, and self-efficacy. Results: The quantitative results revealed significant differences between the control and experimental groups in engagement (EN), autonomous learning (AL), teacher support (TS), social influence (SI), and self-efficacy (SE) except the factor intention to use (IU). In multilinear regression, engagement (EN), social influence (SI), and intention to use (IU) positively predicted higher self-efficacy, while autonomous learning (AL) had a minor negative effect. Teachers’ support (TS) lacked a statistically significant association with self-efficacy. The qualitative data supported and supplemented the findings, highlighting the above 6 factors’ improvement with high frequency in the related codings, and high occurrence of codings like improved in learning, enriching, interesting, growth, and motivation also showed the deep and multidimensional analysis of the findings, and managing time and goals effectively cultivated independence and responsibility. Overall, the qualitative insights provided nuanced, experiential perspectives complementing the quantitative model connecting factors like engagement, autonomous learning, teachers’ support, social influence, intention to use, and self-efficacy. Conclusion: This research demonstrates the pivotal role of structured time management training in enhancing educational outcomes within blended learning environments. By demonstrating the benefits of integrating time management training, the study contributes novel insights into improving students’ development. The findings advocate for the development of more effective educational strategies and instructional designs, emphasizing the complex interplay between various factors and their impact on self-efficacy, especially AI integrated into blended learning. The study paves the way for further investigations into the integration of time management training and other self-efficacy enhancement techniques in blended learning environments. In this way, it encourages researchers to explore the potential synergies between time management, goal setting, and self-efficacy enhancement strategies in various educational contexts. Moreover, the findings can inform the development of more effective educational strategies and instructional designs, leading to improved pedagogical practices and student learning experiences in the long run.