Enhancing Programming Proficiency, Evaluating the Impact of AI-powered Code Assistant Tools on Learning Outcomes

Abstract

There always exists a naiver, tinier approach to writing good code and, likewise, a longer and more comprehensive way. Imagine a tool that takes advantage of deep machine learning algorithms to fish the most appropriate code and put it in a drop-down menu only for a programmer to select. In recent years, the use of AI-powered programming tools has grown in leaps and bounds and gained much attention. Whereas AI has been around for roughly 30 years, it is still uncertain for educators on how to make instructive advantage of it on a larger scale and how it can essentially have a profound effect on teaching and learning in tertiary education. This article investigates the effectiveness of AI-powered code assistant tools in learning programming. For the research, two leading coding platforms were picked (eclipse and VS code) and a selected AI-powered code assistant tool (Tabnine) was installed. After training the research participants, an experiment was carried out, whereby all 40 participants were given two tests, one on AI-assistant enabled coding platform and the other on non-AI-assistant enabled coding platform. Results indicate that AI-coding tools significantly increase students’ coding efficiency and general motivation to code. Results also show that AI code assistant tools do not affect participant’s code comprehension. From the results found it is recommended that AI code assistant tools must be incorporated to aid students in developing a positive attitude towards programming and also to improve their coding efficiency.

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