Comparison of Students’ Programming Skills Before and After Using AI Gemini in Colab with Python - OUKCHALEUN, Xayxavath; MEKTHANAVANH, Vinath; KHONGKETH, Thongphet; ILAISACK, Bounthanome; KITTIKHOUN, Sangviane (Souphanouvong University Journal Multidisciplinary Research and Development, 2026)
his study investigated the impact of AI Gemini integration in Google Colab on Python programming skills development among 70 computer engineering and information technology students at Souphanouvong University. Using a one-group pretest-posttest design, the research employed programming assessments, time tracking, and observational methods to evaluate skill enhancement. Results demonstrated significant improvements: average programming scores increased from 64.59 to 79.53 (23.1% improvement, p ≤ 0.001) and average problem-solving time decreased from 47.42 to 30.51 minutes (35.7% reduction). Qualitative analysis revealed enhanced conceptual understanding of programming fundamentals, improved debugging capabilities, and increased student confidence. AI Gemini served as an effective real-time learning assistant, providing immediate feedback and facilitating systematic problem-solving approaches. The findings support AI Gemini integration in programming education as a valuable tool for enhancing learning outcomes, promoting computational thinking skills, and improving programming efficiency. This research contributes to understanding AI-assisted learning environments in computer science education and provides practical implications for programming pedagogy in higher education institutions.