Integrating Competitive Programming Platforms and AI-Based Feedback to Improve Programming and OOP Learning
Supervisor Name
Mohammed Khalil
Supervisor Email
m.khalil@ptuk.edu.ps
University
Palestine Technical University - Kadoorie
Research field
Computer Science – Software Engineering and Artificial Intelligence
Bio
Dr. Mohamed Khalil is a faculty member in the Computer Engineering Department, with research focused on Artificial Intelligence (AI) and Machine Learning (ML). His interests include chatbots, intelligent software systems, software engineering, Data Science, Natural Language Processing (NLP), and Computer Vision, with several research publications in these areas.
Description
This project investigates the effectiveness of integrating competitive programming platforms and Artificial Intelligence (AI)-based assessment tools to improve learning outcomes in programming and Object-Oriented Programming (OOP) courses. Traditional programming instruction often relies on lectures and limited assignments, which may not provide sufficient opportunities for hands-on practice, continuous feedback, and real-world problem-solving. As a result, many students experience difficulties in developing programming logic, problem-solving skills, and coding proficiency. The proposed project introduces a technology-enhanced learning approach that combines structured programming practice with AI-supported feedback and assessment. Students will solve level-based programming exercises using competitive programming platforms such as Codeforces and HackerRank. These platforms provide an interactive environment that encourages active problem-solving, frequent coding practice, and progressive skill development. To further support learning, the project integrates an AI-based chatbot that analyzes student programming submissions and provides instant and personalized feedback. The AI system evaluates solution correctness, code quality, and programming structure, and provides explanations, improvement suggestions, and guidance to help students better understand programming concepts and improve their solutions. In addition to supporting students, the AI system will assist instructors in the assessment process by automatically analyzing submissions, tracking student learning progress, and identifying common programming difficulties. This enables instructors to monitor student performance more efficiently and provide targeted instructional support when needed. The study will be conducted at Palestine Technical University – Kadoorie (PTUK) and will involve approximately 250 undergraduate students enrolled in a first-year Object-Oriented Programming course. A quasi-experimental design will be used to compare students from previous semesters (control group) who studied using traditional teaching methods with students in the current semester (experimental group) who will use competitive programming platforms and AI-assisted feedback. The effectiveness of the proposed approach will be evaluated using multiple indicators, including academic performance (exam and assignment results), programming skill development (code quality, readability, and modularity), problem-solving success rates, and student engagement metrics such as submission frequency and participation. The project aims to provide empirical evidence on how integrating competitive programming environments and AI-assisted feedback can enhance programming education and support both student learning and instructional assessment. In addition, the study will contribute practical insights for educators on how AI-supported feedback and competitive programming platforms can be effectively integrated into programming courses to improve student engagement and learning outcomes. The findings of this project may also support the development of more interactive and data-driven teaching approaches in computer science education at PTUK and similar institutions.
