Predicting Students At-Risk
Student engagement information is transformed, through smart data processing, to extract concrete student activity information on the digital platform. This dashboard visualizes the demographics of the openly accessible Open University’s data and the results of the deployed AI prediction models to predict the academic performances of students in terms of pass, fail and withdrawn. AI models are also deployed to predict the early performances of students, during an on-going course. Such early prediction models assist the administration in formulating corrective strategies for timely intervening the students at-risk of a failure/withdrawal.
Data source: https://analyse.kmi.open.ac.uk/open_dataset
Insights about Students At-Risks
Overall Results
Data includes demographical information of students such as gender, age and qualification, their courses taken and their engagement with the online learning platform. Students’ interaction with the online platform is provided in the form of 20 different activities which is transformed in a week-wise format for early prediction of withdrawals. Activity clicks relevant to each academic performance are also provided.