A COMPARATIVE ANALYSIS OF AI-GENERATED AND INSTRUCTOR-DESIGNED LESSON PLANS: UNDERGRADUATE ACADEMIC ACHIEVEMENT IN NUCLEAR PHYSICS

Abstract

This study presents a comparison of the academic success of undergraduate students studying nuclear physics when they were taught using lesson plans developed by ChatGPT versus lesson plans developed by their teacher. We evaluated the effectiveness of artificial intelligence in designing lesson plans and the potential of such tools to complement traditional teaching methods. We had a qualitative and a quantitative component to our study. The former consisted of a comparison of the academic achievement of the two groups of students. The second section determined the perception of the students and the instructors regarding the corresponding lesson plans and their effectiveness in understanding nuclear physics. Both groups were given pre- and post-tests.  We were interested to know how the instruction was given, the extent to which students were involved in the instruction given, and the level of satisfaction they had with the whole experience. There were substantial learning acquisitions in the experimental as well as control group. However, the lesson plans developed with ChatGPT seemed to be just as effective, if not more so in some areas, as the teacher-developed plans in facilitating students’ deeper understanding of the material. This study looks at the possible ways AI can help traditional teaching methods and emphasizes a collaborative, partnership approach to lesson design. The results feed into the increasing conversation about what happens when educators integrate AI into their programs and the effect it will have on something as foundational as STEM education.