An Adaptive and AI-Powered Interactive Learning Assistant for Python Programming

The rapid growth of online education has increased the demand for intelligent and personalized learning systems. This paper presents the design and development of an Adaptive and Interactive Python Learning Assistant, aimed at enhancing the learning experience for students through automation and artificial intelligence. The system integrates adaptive learning techniques to analyze user performance and provide personalized recommendations based on individual progress. It features an interactive coding environment that allows users to practice Python programming with real-time feedback. An automated grading system evaluates user-submitted code using predefined test cases, ensuring accuracy and immediate assessment. Additionally, an AI-powered chatbot is incorporated to assist learners with debugging and conceptual understanding. The platform also includes gamification elements such as badges and leaderboards to improve engagement and motivation. A comprehensive dashboard provides insights into user performance and learning patterns. The system is developed using React for the frontend, Django REST framework for the backend, and PostgreSQL as the database. The proposed solution demonstrates how intelligent systems can significantly improve learning efficiency, engagement, and performance in programming education.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-24
DOI
https://doi.org/10.5281/zenodo.19204899
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
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An Adaptive and AI-Powered Interactive Learning Assistant for Python Programming

Sree Renuga
Zenodo (CERN European Organization for Nuclear Research)
AI in Service Interactions
article

An Adaptive and AI-Powered Interactive Learning Assistant for Python Programming

Sree Renuga
article en

Abstract

The rapid growth of online education has increased the demand for intelligent and personalized learning systems. This paper presents the design and development of an Adaptive and Interactive Python Learning Assistant, aimed at enhancing the learning experience for students through automation and artificial intelligence. The system integrates adaptive learning techniques to analyze user performance and provide personalized recommendations based on individual progress. It features an interactive coding environment that allows users to practice Python programming with real-time feedback. An automated grading system evaluates user-submitted code using predefined test cases, ensuring accuracy and immediate assessment. Additionally, an AI-powered chatbot is incorporated to assist learners with debugging and conceptual understanding. The platform also includes gamification elements such as badges and leaderboards to improve engagement and motivation. A comprehensive dashboard provides insights into user performance and learning patterns. The system is developed using React for the frontend, Django REST framework for the backend, and PostgreSQL as the database. The proposed solution demonstrates how intelligent systems can significantly improve learning efficiency, engagement, and performance in programming education.

Zenodo (CERN European Organization for Nuclear Research)
Grace College & Seminary (US), Grace University (US)
Quality Education
Openalex Percentile: Top 12%
AI in Service Interactions
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