Improving learning outcomes in engineering education with a closed-loop control system method

Education plays a critical role in equipping individuals with the knowledge, skills, and competencies necessary for success. However, traditional educational approaches often struggle to address the diverse learning paces, styles, and needs of students. This challenge is particularly pronounced in technical fields such as engineering, where personalized and adaptive learning methods are essential. This study proposes a novel approach leveraging closed-loop control systems to enhance the attainment of course learning outcomes. The proposed method is demonstrated through a case study on Circuit Analysis, a fundamental course in Electrical and Electronics Engineering. The study quantifies and systematically implements course learning outcomes using various assessment tools, including quizzes, exams, projects, and laboratory evaluations, all integrated into a closed-loop control framework. A numerical correlation is also established between course learning outcomes and broader program outcomes. Unlike traditional systems where assessment results are isolated, the proposed method incorporates adaptive mechanisms that adjust subsequent assessments and learning interventions based on earlier performance. This closed-loop approach enables personalized tracking of students' progress, tailored learning materials, and adaptive teaching strategies that address individual strengths and weaknesses. The findings indicate that closed-loop control systems can transform educational methodologies, offering a robust framework for personalized learning and maximizing students’ potential, particularly in technical disciplines. Furthermore, this approach aligns seamlessly with quality accreditation processes, making it applicable across a wide range of courses.