METHOD FOR RISK ASSESSMENT OF PROJECT-BASED LEARNING FAILURE VIA AHP AND BBN AIMING AT IMPROVING THE QUALITY OF ENGINEERING EDUCATION

Abstract Project-based learning (PBL) has become a prominent approach in engineering education, fostering students' professional knowledge. However, universities often encounter unforeseen challenges with PBL, leading to a return to conventional teaching methods. The complexities of PBL introduce numerous variables, increasing the risk of failure. This study proposes a method to identify risk factors in employing PBL for teaching engineering students. It involves assessing risk probability and impact to derive global risk scores, utilizing the Bayesian Belief Network (BBN), and crafting responses to high-scoring risks. A case study validated the method, gathering data from various sources. Risk factors were identified, categorized, and assessed using a survey and Analytic Hierarchy Process (AHP). BBN and sensitivity analysis identified high probability risks, allowing for the formulation of response actions. The proposed method enhances the PBL process, offering a proactive risk mitigation process and insights into the education sector that benefit professors, students, and decision-makers.