Research Article
Enhancing Python Programming Education with an AI-Powered Code Helper: Design, Implementation, and Impact
Sayed Mahbub Hasan Amiri*
,
Md Mainul Islam
Issue:
Volume 11, Issue 1, March 2025
Pages:
1-17
Received:
23 March 2025
Accepted:
31 March 2025
Published:
28 April 2025
Abstract: This is the study that presents an AI-Python-based chatbot that helps students to learn programming by demonstrating solutions to such problems as debugging errors, solving syntax problems or converting abstract theoretical concepts to practical implementations. Traditional coding tools like Integrated Development Environments (IDEs) and static analyzers do not give robotic help while AI-driven code assistants such as GitHub Copilot focus on getting things done. To close this gap, our chatbot combines static code analysis, dynamic execution tracing, and large language models (LLMs) to provide the students with relevant and practical advice, hence promoting the learning process. The chatbot’s hybrid architecture employs CodeLlama for code embedding, GPT-4 for natural language interactions, and Docker-based sandboxing for secure execution. Evaluated through a mixed-methods approach involving 1,500 student submissions, the system demonstrated an 85% error resolution success rate, outperforming standalone tools like pylint (62%) and GPT-4 (73%). Quantitative results revealed a 59.3% reduction in debugging time among users, with pre- and post-test assessments showing a 34% improvement in coding proficiency, particularly in recursion and exception handling. Qualitative feedback from 120 students highlighted the chatbot’s clarity, accessibility, and confidence-building impact, though critiques included occasional latency and restrictive code sanitization. Emphasizing the ethical aspects of the project, the bias principle led to the discrimination of gendered reasons for 83% and the GDPR-iPad-like procedures to anonymity were followed. The chatbot's productivity points to its ability to make coding education available to everyone and to give 24/7 aid to students in some not well-funded schools. Future work will expand multilingual support through localized datasets and culturally adapted examples, integrate gamification to enhance engagement, and develop collaborative learning features. By balancing technical innovation with pedagogical empathy, this research provides a blueprint for AI tools that prioritize educational equity and long-term skill retention over mere code completion. The chatbot exemplifies how AI can augment human instruction, fostering deeper conceptual understanding in programming education.
Abstract: This is the study that presents an AI-Python-based chatbot that helps students to learn programming by demonstrating solutions to such problems as debugging errors, solving syntax problems or converting abstract theoretical concepts to practical implementations. Traditional coding tools like Integrated Development Environments (IDEs) and static ana...
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Review Article
Agile Integration in Software Development: Principles, Practices, and Challenges
Felix Temole*,
Desislava Atanasova
Issue:
Volume 11, Issue 1, March 2025
Pages:
18-29
Received:
31 July 2025
Accepted:
30 August 2025
Published:
19 September 2025
DOI:
10.11648/j.se.20251101.12
Downloads:
Views:
Abstract: Agility in software development has evolved from a niche methodology to a mainstream paradigm that enables organizations to respond rapidly to changing market demands and customer expectations. This paper explores the integration of agility into software development through modern agile methodologies such as Scrum, Extreme Programming (XP), and Kanban. It highlights the core benefits of agility, including improved adaptability, faster delivery cycles, and enhanced customer satisfaction, while also addressing persistent challenges such as documentation gaps, progress measurement, and organizational resistance to change. Beyond current practices, the paper examines the future trajectory of agile development, emphasizing the growing influence of emerging technologies such as artificial intelligence (AI) and DevOps. These technologies are reshaping agile workflows by enabling greater automation, predictive analytics, and continuous delivery. Drawing on recent scholarly and industry research, the paper outlines best practices for successful agile transformation, including the alignment of agile practices with strategic business goals, the cultivation of a supportive organizational culture, and the use of modern tools to enhance transparency and performance analytics. By synthesizing empirical findings and forward-looking insights, this study provides a comprehensive roadmap for agile adoption and continuous improvement, offering valuable guidance for practitioners, managers, and researchers aiming to build resilient, customer-centric software systems in increasingly complex and technology-driven environments.
Abstract: Agility in software development has evolved from a niche methodology to a mainstream paradigm that enables organizations to respond rapidly to changing market demands and customer expectations. This paper explores the integration of agility into software development through modern agile methodologies such as Scrum, Extreme Programming (XP), and Kan...
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