The Big Data Analytics Center (BIDAC)

In an increasingly complex world, the demand for skills inherited from science, technology, engineering, and mathematics (STEM) education is dominating the global economy. Yet, despite the increasing demand, the supply of STEM employees remains insufficient, leaving the market with the so-called “skills gap”.

Experts estimate that if the gap continues to increase, the economic security would be at risk. This concern caught the attention of the authorities in the United Arab Emirates (UAE) to take corrective actions to meet these challenges. So, in 2010, UAE announced “Vision 2021” as a key endeavor to develop a diversified economy by encouraging UAE students to engage in STEM fields. Despite the efforts, the number of male graduates in STEM disciplines, reported by the United Arab Emirates University (UAEU), appears to be below expectations when compared to non-STEM disciplines. So, in this work, we propose a novel model to help UAEU students meet expectations and graduate at a faster rate. We address this issue from a curricular analytics perspective, a relatively novel compared with the traditional approaches followed elsewhere. We perceive that the complexity of the curricula structure in the STEM programs at UAEU imposes unnecessary complications that restrict students from traversing their degree requirements smoothly while maintaining the quality of education.

So, we intend to reform the structure of STEM programs at UAEU by reducing their respective complexities while maintaining their learning outcomes. Complementing the curricular analytics model, we also propose a data-driven personalized degree plan recommender system that addresses graduation rates at the individual level. In general, students have different academic backgrounds and demographic characteristics, so it is more convenient to provide them with customized degree plans that better fit their backgrounds and characteristics. This process will also help them graduate in a timely fashion.