MOOC Student Learning Analytics for Automotive Technology Programme in Vocational College

Abstract

This study aims to study the analysis of how students learning and see what they do in their Massive Open Online Course in the learning of Automotive Technology Course at Technical and Vocational Education Training institutions. This study used analytics tools, data and reports as part of an educational endeavor. At the beginning of each learning session, all students will be able to participate in this course. The participation of students enrolled in this large-scale course makes it challenging to help students individually achieve their learning objectives. Through the analytical features offered by the MOOC platform, it has made it easier for course coordinators and educators to view student learning activities in the online supplementary restraint system (SRS) course conducted through the MOOC. The findings of student learning analytics found that there are several types of learners and the tendency to follow learning by competency unit in online learning using open learning. Therefore, in this study, the analytical assessment of TVET student learning is used in achieving TVET course learning objectives. The use of learning analysis among TVET students can be used to observe interest and achievement in each unit of competency and identify students at risk during their learning process by analyzing student engagement on the page. By analyzing these interactions, learning analytics has the potential to provide predictive insights about future challenges. These predictions are used to evaluate the adaptability of the content presentation and improve the performance of the learning TVET MOOC process in the future.