Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/4146 2018 2018 Lecturer, Educational Technology Center, Faculty of Education, Mansoura University, Egypt Ramy Ramy Professor of Fashion Manufacturing Technology, Faculty of Human Sciences and Design, King Abdulaziz University, Saudi Arabia Shadia Salah Salem Professor of Educational Technology, Faculty of Education, Mansoura University, Egypt Reham Mohamed Al Al-Ghoul 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. 2026 2026 413 432 10.54216/FPA.210226 https://www.americaspg.com/articleinfo/3/show/4146