
Engineering education is undergoing significant transformations to address global technological advancements, industry demands, and sustainable use of resources. While traditional curricula emphasize technical knowledge, modern engineers require interdisciplinary collaboration, innovation, and sustainability awareness. However, existing educational frameworks lack a structured integration of Course Learning Outcomes (CLOs), Engineers Australia Professional Engineer (EA PE) competencies, and Sustainable Development Goals (SDGs), making it difficult to assess students' competencies effectively. To address this gap, this study proposes a new assessment model integrating CLOs, EA PE competencies, and SDGs. The model employs statistical modeling techniques, specifically Structural Equation Modeling (SEM) to evaluate students' learning progress, competency development, and sustainability awareness. By applying quantitative and qualitative analysis, this framework provides a systematic approach to improving engineering curricula. The findings will contribute to better assessment methods and curriculum development strategies, ensuring that future engineers are well-equipped to meet evolving industry and sustainability challenges.
Professional Competencies, SDGs, Engineering Curriculum Design
Professional Competencies, SDGs, Engineering Curriculum Design
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
