AI-ZPD Connection: Scaffolding Learner Experience with Generative Tools

Abstract

The use of generative AI in education is not just a trend—it's an inevitability. These tools are rapidly becoming an integral and growing part of the learning landscape. The applicability is both in teaching and learning methodology. Freshmen computer programming students utilize AI tools in their laboratory product tasks. This is to either supplement them, help jumpstart it, or view sample codes to make them understand better. This study is directed to assess learner performance in a computer programming course using the Java language taking the BSIT degree. It undermines the theory of ZPD, zone of proximal development. In the ZPD level of potential development, they solve Java machine problems under guidance of a more knowledgeable individual and in the level of actual development, they solve them on their own without any learning scaffolds. The paper also aims to mount learner experience from the level of potential development based on a questionnaire inquiring the utilization of generative AI tools while solving machine problems through coding and executing their coursework. The study shows that 87% of the 117 students claimed they are using ChatGPT, or other AI-powered integrated development environments while answering their machine problems in the Computer Programming course. It has also been revealed that students received higher grading average of 90.2% when utilizing generative AI tools and only 77.9% otherwise. When 79% of the students asserted that they tapped the use of generative AI tools to understand Java concepts and 72% professed they were seeking code explanations, utilization was indeed inevitable. The dependence of the students on the tools may play in the zone of proximal development, which is identified as the distance between the two levels.