Our school project utilized Moodle Analytics, an advanced educational data analysis tool, to identify students at risk of not meeting the minimum passing grade in our school’s online courses on Moodle. Harnessing the power of predictive analytics, we tailored an intervention strategy that aimed to enhance the students’ learning journey and, in turn, their academic performance.
The project involved designing algorithms and machine learning models that processed vast amounts of data, from student interaction logs to assessment results, and predicted potential academic risks. The results yielded significant insights, enabling us to implement a proactive approach in our educational support system. This presentation will highlight our methods, findings, and the profound implications of data-driven pedagogical strategies in modern education.