MPM model: A cross-platform massive open online course (MOOC) performance monitoring and measurement model based on MOOC learning analytics

Abstract

Over the past ten years, most higher education institutions have employed Massive Open Online Courses (MOOCs) to deliver educational materials and activities. MOOC learning analytics data is readily available, which is one of its primary characteristics. Sadly, there are still problems with student dropout, retention, and engagement on MOOCs, which reduces their usefulness as a learning tool. More research is urgently needed to determine how to monitor, assess, and enhance learning delivered through online platforms. The researchers designed the research to solve specific practical problems and answer certain questions. The Ministry of Education Malaysia's requirement partly motivates this study, and the semantic web concept inspires it to investigate learning analytics in different MOOC platforms. The aim is to find a way to utilise the existing learning analytics data from MOOCs for monitoring and measuring a course or learner performance. An initial study led this research to three main research questions and research objectives. The first research objective is identifying parameters and algorithms for measuring course and learner performance using existing learning analytics. The second research objective is to propose a generic model for monitoring course and learner performance at macro and micro levels using MOOC learning analytics, which resembles the cross-platform features. The third objective is to observe and evaluate the MPM Model’s usability. This study used Applied research using mixed methods. The researchers designed the research to solve specific practical problems and answer certain questions. A combination of various research methods and activities, such as observation, simulations, experiments, and surveys, are used throughout different phases of this research study. Phase 1 is a literature review and preliminary study. Phase 2 is data analysis and algorithm development. Phase 3 is the MPM model design, development and experiments. Phase 4 is MPM Model user usability testing and feedback. Phase 5 is results, discussion and report preparation. A Series of simulations provides us with the information to consider in completing the algorithm design and development of the MPM Model. The MPM Model experiments showed more insight from analysed MOOC learning analytics data. User usability testing conducted with 20 selected participants indicates good feedback on how a user can use the MPM model, what information it gives them to justify their MOOCs course or learner performance, and what to consider for future improvement. As this study ends, I have effectively addressed and met the established goals and research questions. I assert that MOOC learning analytics will now be more accessible to comprehend and utilise thanks to the MPM Model. This work advances the fields of data science and MOOC education research, particularly in the areas of cross-platform MOOC analytic monitoring and performance reporting.

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Identifiers

ORCID for Wan Sazli Nasaruddin Saifudin: orcid.org/0009-0001-1232-1026

ORCID for Dame Wendy Hall: orcid.org/0000-0003-4327-7811

ORCID for Leslie Carr: orcid.org/0000-0002-2113-9680

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