Self-Regulated Learning for Web-Enhanced Control Engineering Education

Web enhanced active learning has been demonstrated to be an effective approach in Engineering Higher Education, as it provides students with more flexibility in dealing with the development of skills related to professional knowledge. However, students require a sufficient level of self-efficacy and control over their own learning, which might impact negatively on their effort and academic performance. Therefore, promoting self-regulated learning among students would help them to develop effective strategies they could adopt in planning, monitoring and evaluating their learning process. In this paper, a web-enhanced active learning approach is proposed which integrates a self-regulated learning strategy that supports Control Engineering students in managing their learning process. In order to evaluate the effectiveness of the proposed approach, a three-year quasi-experimental study was performed in the context of an undergraduate Automatic Control course at the Università Politecnica delle Marche, Italy. This involved 418 students and 4 teachers. Both quantitative and qualitative measurement tools were used for the evaluation. The results of the study confirmed the effectiveness of a learning design specifically tailored to implement self-regulated learning features in a web-enhanced active learning approach for undergraduate engineering students. Moreover, the qualitative-quantitative evaluation model proved to be effective in capturing and gauging a more comprehensive and detailed picture of the triggered self-regulated learning dynamics.