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Proposer
Abhishek Ghai
Title
Student Performance and Dropout Risk Predictor
Goal
Description
Students source or select a dataset containing academic and/or engagement-related data, and design a predictive model capable of identifying students likely to underperform or disengage. Beyond model accuracy, the project should address how predictions are explained to a non-technical audience such as a teacher or academic advisor, including what factors are driving a given prediction. Students should also consider and discuss fairness, whether the model's predictions could disadvantage particular groups of students, as part of their evaluation.
Resources
Background
Url
Difficulty Level
Easy
Ethical Approval
None
Number Of Students
1
Supervisor
Abhishek Ghai
Keywords
data mining, predictive analytics, educational data mining, learning analytics, classification, explainable ai, risk prediction
Degrees
Bachelor of Science in Computational Sciences and Software Engineering
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