AI2P: artificial intelligence tools and pair programming to enhance students self-efficacy and confidence to learn python programming

This study explores the impact of integrating artificial intelligence (AI) tools and pair programming on the self-efficacy and confidence of secondary school students in learning Python programming. The study was conducted with 74 secondary school students with no experience in programming. The research is based on Quasi-Experimental (Pretest-Posttest Design). Over an 8-week period, students engaged in a structured Python programming class that combined the use of AI tools for coding aid and pair programming techniques. Self-efficacy and confidence levels were measured through pre- and post-intervention surveys. A test was used to analyze the differences in the pre- and post-intervention scores. The t-test analysis revealed a statistically significant improvement in students' self-efficacy and confidence levels in learning Python programming after the intervention. The mean self-efficacy score increased from 5.24 (SD = 0.8) to 6.31 (SD = 0.4), and the mean confidence score increased from 4.27 (SD = 0.7) to 6.3 (SD = 0.4), both at a significance level of p < 0.01. The integration of AI tools and pair programming significantly enhances the self-efficacy and confidence of secondary school students in learning Python programming. These findings suggest that educational strategies incorporating AI and collaborative learning can be effective in promoting positive learning outcomes in computer science education.