Using case-based learning to enhance students’ performance in mechanical engineering undergraduates

Abstract

Among the myriad of instructional approaches in engineering education, case-based learning (CBL) has emerged as a promising pedagogical strategy that promotes active learning, critical thinking, and real-world application of knowledge. This study investigates student performance and satisfaction with CBL methodologies in the context of mechanical engineering education, conducted in Sri Lanka. A mixed-methods approach was employed, including paired t-tests to analyze academic performance data and a survey to assess student perceptions and practices. The results indicate a positive relationship with grades and perception of CBL among students, with a majority expressing agreement or strong agreement with its implementation. Additionally, results from the survey discovered that conversational AI systems and chatbots emerged as a much-preferred supplementary resource utilized by students. Recommendations for future higher education methodologies include enhancing the integration of CBL, leveraging technology-driven resources, promoting active learning strategies, implementing continuous assessment and feedback mechanisms, investing in educator professional development, and promoting research and evaluation initiatives. These findings contribute valuable insights into student experiences and preferences, informing the development of evidence-based instructional practices in higher education.