Muscat – A novel research at Al Buraimi University College has shown that use of artificial intelligence can greatly help monitor student performance and devise measures for timely intervention.

The study – titled An artificial intelligence approach to monitor student performance and devise preventive measures – led by IT instructor Dr Ijaz Muhammad Khan explores the potential of AI in the educational sector, particularly in identifying and supporting students needing additional help.

Khan informed that one of the persistent challenges for academic instructors is effective monitoring of students’ academic progress. Traditional methods often fail timely identification of students who are lagging, preventing early intervention. With educational institutions accumulating vast amounts of data on students, there is growing need to leverage this data to improve educational outcomes and enhance institutional reputation.

The research utilised data from Al Buraimi University College to test various AI approaches, focusing on machine learning classifiers that could predict students’ academic performances early in their courses. In particular, the study evaluated the effectiveness of these classifiers in identifying key indicators that warrant early intervention.

Among the machine learning models tested, Decision Tree was found to be the most effective, outperforming others like k-Nearest Neighbours, Artificial Neural Networks and Naive Bayes in terms of accuracy and efficacy. Crucial predictors such as attendance records, cumulative grade point average (CGPA) and midterm exam results emerged as significant indicators for identifying at-risk students.

An actionable model developed using Decision Tree now allows instructors to easily interpret and act on the data, offering personalised support to underperforming students promptly after key assessments. This proactive approach aims not only to bolster students’ academic performance but also to enhance their overall educational experience.

Khan highlighted the transformative potential of AI in education, advocating its broader implementation to foster a more supportive learning environment. He envisions AI as a foundational element in educational practices, propelling innovation and improving learning outcomes.

The findings from this pioneering research – with contributions from Dr Abdul Rahim Ahmad, Dr Nafaa Jabeur and Dr Mohammed Najah Mahdi – were published in the journal Smart Learning Environments. 

This research marks a significant step towards integrating advanced technologies in education, setting a benchmark for other institutions aiming to enhance academic support through innovative means.