Analysing Learning Styles for Engineering Capstone Projects: 4MAT Analysis on Student Outcomes and Perceptions
Keywords:
Bayesian Belief Networks; Capstone project; Education; Engineering; 4MAT systemAbstract
Capstone projects are integrated into engineering curricula to combine various subjects and impart essential professional skills that may be difficult to teach solely through traditional lecture-based courses. These projects play a crucial role in preparing students for their future roles as professional engineers, thereby significantly impacting a university’s industry reputation and ranking. The challenge in engineering education lies in aligning the teaching approach of educators with the diverse learning styles of their students. This study aims to examine the impact of the learning style of the students measured by their watching-doing scores using the 4MAT tool, on the attainment of the benefits of the graduation project (GP). The Bayesian Belief Networks (BBN) approach was adopted in this study to analyse the data collected from 271 students enrolled in both GP1 and GP2 semesters in the engineering department of United Arab Emirates University. Results show that regardless of learning style, both watching and doing category students share similar perspectives on various aspects of the GP course, such as the optimal team performance ratio. However, when assessing the overall effectiveness of the GP programme, doing students exhibit a higher level of agreement than watching students. The study provides valuable insights to faculty members, helping them navigate the optimal balance between providing mentorship and fostering students’ independence during the different stages of their final-year design capstone projects. These findings underscore the importance of tailored educational strategies to accommodate diverse learning styles, contributing to more effective engineering education and better-prepared graduates.
https://doi.org/10.26803/ijlter.23.8.20
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