Analyzing the Learning Effectiveness of Generative AI for Software Development for Undergraduates in Sri Lanka

Abstract

As the demand for skilled software developers continues to rise, the integration of Generative Artificial Intelligence (Generative AI) in educational settings has garnered attention. This research investigates the effectiveness of Generative AI in enhancing coding proficiency in a diverse cohort of participants. The study employs pre-, mid-, and post-tests to measure coding skills, employing a nuanced analysis across various demographic variables. The findings reveal a substantial increase in average scores, indicating positive impacts of Generative AI on coding abilities. The N-Gain value of 0.33 signifies a medium learning gain, establishing Generative AI as a valuable tool in coding education. A detailed exploration of demographic variables, including gender, age, academic level, A/L stream, A/L district, and preferred programming language, provides insights into the intersectionality of these factors with learning outcomes. This research contributes to the discourse on the impact of Generative AI on coding skills, offering practical insights for educators, policymakers, and practitioners. The study recommends tailored interventions to address specific demographic variables, fostering a more inclusive and effective learning environment.

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