2692-4048ISSN (Online)
2770-0070ISSN (Print)
Volume 21 , Issue 2 , PP: 413-432, 2026 | Cite this article as | XML | Html | PDF | Full Length Article
Ramy Samir Mohammed ALSeragy 1 * , Shadia Salah Salem 2 , Reham Mohamed Al-Ghoul 3
Doi: https://doi.org/10.54216/FPA.210226
MLOps, short for Machine Learning Operations, is a practice that aims to streamline and automate the process of deploying, monitoring, and managing machine learning models in production. In the context of educational technology, MLOps can help optimize the performance of learning algorithms, ensure scalability and reliability. By implementing MLOps, educators can utilize real-time data to identify patterns of behavior that may indicate a student is struggling. This proactive approach allows timely interventions to be put in place, addressing issues before they escalate and potentially lead to academic failure. Additionally, MLOps can also help educators personalize learning experiences for students, catering to their individual needs and preferences. The participants were 60 learners enrolled in the Ready-Made Garment Manufacturing Technologies course, part of the Fashion Manufacturing Technology specialization in the Faculty of Human Sciences and Design at King Abdulaziz University. The findings of research found that integration of MLOps in educational technology has the potential to support and guide students in their learning through detecting undesirable student behaviors and adjusting early.
MLOps , Learner behaviors , Adjusting early , Fashion Manufacturing Technology
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