The student Ibrahim M. Melhem from the Computer Science Master program defended his thesis with the title “Learning Progress Monitoring: Towards an Early Warning System”
The jury was formed of Dr.Jad Najjar (Supervisor), Dr.Badie Sartawi (Co-Supervisor), Dr. Raid Zaghal (Internal examiner) and Dr. Faisal Khamayseh (Palestine Polytechnic University - External examiner).
Huge amounts of data and traces on learning progress are collected in the diverse systems
where learning experience is delivered or occurs. This data about learning traces can be complementing to information about learning outcomes and assessment results. In this paper, we implement an analytics engine that will use learning traces to support an Early Progress Warning System (EPWS). Our engine uses data gathered from Learning Management Systems (LMS), Student In-formation System and Virtual Learning Platforms (Videoconferencing). Based on learning analytics techniques, we focus on providing awareness on how students do, in real time during the course. Providing learning progress monitoring and early progress warning framework, enhance students performance and stimulate them to do better and enables early proactive intervention from teachers and other stakeholders in the educational system.