Correlation Between AI Tool Usage Frequency and Perceived Learning Effectiveness in Programming Education

This study investigates the relationship between the frequency of AI tool use and students' perceived learning effectiveness in programming in a university-level IT classroom. During lab hours, Google Forms were used to collect data from students across all college levels. A sample size of 342 students was obtained using statistical techniques. The utility of AI technologies was assessed using a Likert scale, and correlation analysis was used to uncover links between usage frequency and perceived effectiveness. The findings revealed a statistically significant positive relationship between the frequency of AI tool use and students' perceived usefulness of these tools. Gender differences were also examined, with female students reporting slightly higher perceived utility of AI technologies than male students. Furthermore, academic year levels were investigated, with first-year students having the highest frequency of weekly AI tool use. This trend is attributed to their reliance on AI tools for foundational programming concepts, debugging, and problem-solving during their initial exposure to programming, which helps them navigate the steep learning curve typical of beginner courses. Strict ethical protocols, including data security and confidentiality measures, were enforced throughout the study. The findings highlight the need for further research to explore the specific factors influencing the relationship between AI tool usage and programming learning outcomes, as well as to inform targeted instructional strategies for diverse student demographics.