Rhaydae Jebli

Work place: SIGL Laboratory, ENSATE, Abdelmalek Essaadi University, Tetuan, Morocco

E-mail: rhaydaejeb@gmail.com


Research Interests: E-learning experience management, E-learning, Machine Learning


Rhaydae Jebli is a PhD student at the SIGL Laboratory, University Abdelmalek Essaadi, National School of Applied Sciences Tetouan-Morocco. She holds a master’s degree (2017) from University Abdelmalek Essaadi and BSC Degree (2015) from University Mohamed First. Her research interests are educational technologies, e-learning environments, machine learning.

Author Articles
A Proposed Algorithm for Assessing and Grading Automatically Student UML Diagrams

By Rhaydae Jebli Jaber El Bouhdidi Mohamed Yassin Chkouri

DOI: https://doi.org/10.5815/ijmecs.2024.01.04, Pub. Date: 8 Feb. 2024

Digital technologies and innovative methods have shown a significant impact on educational systems, and have made work easier for both learners and teachers. Additionally, they have improved the quality and the capability to digitize the assessment of student work produced during a learning process. Assessing and scoring students’ UML diagrams has become a challenging task for teachers, especially with the growing number of students, as well as the necessity to better manage their time. Consequently, there will be a necessity to automate the assessment of these learners. This paper presents an approach for assessing and grading automatically the student’s UML diagrams. The approach uses an algorithm implemented in Java, which takes the tutor's and student's solution diagrams as input, then provides the student's scores and identifies differences and errors made. Our algorithm was tested and evaluated in a real case within a web platform, and the results obtained demonstrate the effectiveness of our solution.

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