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Model-Based Systems Engineering Applied to Engineering Learning Analytic Systems (ELAS) to Enhance Student's Learning and Performance
  • Pallavi Singh ,
  • Liliana Villavicencio Lopez,
  • Wilfrido Moreno
Pallavi Singh
Electrical Engineering Department, University of South Florida Tampa

Corresponding Author:[email protected]

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Liliana Villavicencio Lopez
Electrical Engineering Department, University of South Florida Tampa
Wilfrido Moreno
Electrical Engineering Department, University of South Florida Tampa


Engineering education is a complex that involves multiple stakeholders, including students, educators, administrators, and industry partners. It is continuously evolving to meet the demands of modern industry and society. The traditional teaching and learning methodologies are being replaced by a more integrated skillset that focuses on developing students' cognitive, social, and emotional skills. The shift towards this integrated approach is gaining momentum, and it is important to have a framework that has been proven to solve complex systems. The usage of systems engineering tools to model engineering education systems is not often seen. In this paper, a novel application of Model-Based Systems Engineering using Systems Modeling Language (SysML) to develop an Engineering Learning Analytic System (ELAS) framework that consists of multi-dimensional elements related to educational systems. The core of this study involves a rigorous Requirements Verification and Validation (V&V) process to ensure stakeholder needs which systematically were map with system capabilities. ELAS model simulations provided predictive insights into soft skill development, enabling decision-making via targeted interventions that could significantly enhance students' skill sets. ELAS highlights that a data-driven approach, enabled by SysML, significantly enhances the ability to enact timely by relevant interventions at various levels of the educational management process. The proposed ELAS model offers a strategic blueprint for continuous improvement within educational institutions, demonstrating a pathway toward a responsive and self-improving educational system. The refining of the ELAS model, for broadening simulation scopes, and further integrating predictive analytics into administrative decision-making processes is an ongoing endeavor.
12 Mar 2024Submitted to TechRxiv
19 Mar 2024Published in TechRxiv