A Multi-Project Evaluation of Engineering Students’ Performance for Online PBL: Taking the Sustainable Decision Analysis Course as an Example

Abstract

In order to meet the growing demand for engineering professionals who can incorporate sustainable solutions into their work, sustainability courses have been launched in online problem-based learning (PBL) environments through various real-life projects. Nonetheless, the conventional one-off grading approach may fail to capture the intricate variations in students’ performance across different projects. To address this problem, a multi-project evaluation framework utilizing the probability exceedance method (PEM) is proposed, which can fuse linguistic evaluation data presented in probability distributions without the need to obtain weights of criteria. In the case study, a comprehensive evaluation of the performance of students majoring in engineering management is conducted within a study group over an online PBL course on sustainable decision analysis. The sensitivity analysis demonstrates that consistent scores can be achieved after assigning different values of fuzzy measures to each criterion. This study enables teachers to holistically evaluate students without being bound by rigid numerical standards or strict weighting schemes, thus allowing them to focus on other educational tasks while ensuring effective and reliable results. Moreover, it contributes to educational innovation by introducing a modern and comprehensive approach for engineering student assessment in online PBL, aligning with the evolving needs of educational sustainability in higher education.