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Original Research | Computer Science | Volume 15 Issue 7, July 2026 | Pages: 640 - 642 | India
Exploring Students' Experiences and Learning Outcomes of Python through BBC Micro:bit in the Age of Generative AI: A Mixed-Methods Classroom Action Research Study
Abstract: In the realm of programming education, the rise of Generative Artificial Intelligence (GenAI) tools like ChatGPT, Gemini, and GitHub Copilot has revolutionized the way students learn. Programming education has undergone a transformation thanks to Generative Artificial Intelligence (GenAI) tools such as ChatGPT, Gemini, and GitHub Copilot, which allow students to create functioning Python programs in mere moments. These tools offer excellent support, but can lead to superficial learning, reduced computational thinking, less debugging of code, and less creativity. This study explores the possibilities of using physical computing with BBC Micro:bit to address these challenges in the CBSE Class XI Computer Science curriculum. The study followed a classroom action research convergent mixed methods approach with 40 Senior secondary students for 40 days of intervention. Through hands-on projects, students were introduced to the concepts of Python: variables, data types, conditional statements, loops, functions, events, sensors, LED displays, music and radio communication. Amongst the projects were a Digital Dice, Rock-Paper-Scissors Game, Emotion Badge, Earthquake Monitor, Water Reminder, Footstep Tracker and an Alzheimer's Patient Tracker. The quantitative survey results showed that 94.7% of students found physical computing more engaging than traditional programming, while 84.2% noted that they had better logic-building skills when using physical computing. The qualitative thematic analysis provided evidence that students preferred hardware-based learning to software-based because it is interactive, visible, and meaningful, and that project-based learning allows for creativity and independence, while debugging is challenging but rewarding. The results indicate that using physical computing improves engagement, confidence, creativity and computational thinking, and decreases dependence on AI-generated solutions. The study suggests that project-driven learning based on actual hardware can continue to foster learner agency and critical thinking even in the era of AI-supported coding, a vital aspect of secondary computer science education.
Keywords: Generative Artificial Intelligence, Python Programming, BBC Micro:bit, Physical Computing, Computational Thinking, Classroom Action Research, Qualitative Research, Project-Based Learning, Computer Science Education, Experiential Learning, CBSE, Student Engagement
How to Cite?: A. Shikha Shah, "Exploring Students' Experiences and Learning Outcomes of Python through BBC Micro:bit in the Age of Generative AI: A Mixed-Methods Classroom Action Research Study", Volume 15 Issue 7, July 2026, International Journal of Science and Research (IJSR), Pages: 640-642, https://www.ijsr.net/getabstract.php?paperid=SR26705204512, DOI: https://dx.doi.org/10.21275/SR26705204512