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Proposer
Radu-Casian Mihailescu
Title
Data-Driven Prediction and Categorization of Student Performance for Educational Decision Support
Goal
Description
As educational institutions increasingly adopt data-driven strategies, there is growing interest in leveraging predictive analytics to improve student outcomes. Understanding and forecasting student performance enables timely interventions and informed decision-making. However, existing methods often lack scalability, adaptability, or precision when applied in dynamic educational environments. Research Problem: How can student performance be predicted and categorized accurately using data-driven approaches to support early intervention and strategic planning in educational settings?
Resources
Background
Url
Difficulty Level
Moderate
Ethical Approval
None
Number Of Students
1
Supervisor
Radu-Casian Mihailescu
Keywords
Degrees
Bachelor of Science in Computer Science
Bachelor of Science in Computer Systems
Bachelor of Science in Information Systems
Master of Engineering in Software Engineering
Master of Design in Games Design and Development
Master of Science in Artificial Intelligence
Master of Science in Artificial Intelligence with SMI
Master of Science in Business Information Management
Master of Science in Computer Science for Cyber Security
Master of Science in Computer Systems Management
Master of Science in Computing (2 Years)
Master of Science in Data Science
Master of Science in Human Robot Interaction
Master of Science in Information Technology (Business)
Master of Science in Information Technology (Software Systems)
Master of Science in Network Security
Master of Science in Robotics
Master of Science in Software Engineering
Bachelor of Science in Computing Science
Bachelor of Engineering in Robotics
Bachelor of Science in Computer Science (Cyber Security)
Master of Science in Robotics with Industrial Application
Postgraduate Diploma in Artificial Intelligence
Bachelor of Science in Statistical Data Science
BSc Data Sciences
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