The Role of Generative AI Tools in Case-Based Learning and Teaching Evaluation of Medical Biochemistry (Preprint)

Abstract

<sec> <title>BACKGROUND</title> With the continuous progress and development of the medical field, medical biochemistry, as an important basic course in medical education, has an increasingly large and complex knowledge system. The traditional teaching mode is often difficult to meet students' in-depth understanding of knowledge and individualized learning needs. Students may feel confused and overwhelmed when facing a large number of biochemical concepts, chemical reactions, molecular structures and other contents. </sec> <sec> <title>OBJECTIVE</title> Generative AI tools are expected to be a powerful assistant in course teaching, while such tools are still rarely applied in biochemistry courses. This study attempts to investigate the important contribution of AI tools to students' knowledge expansion and teaching evaluation in medical biochemistry CBL teaching through a comparative study. </sec> <sec> <title>METHODS</title> In this study, we assessed the important role of AI tools in assisting students' CBL learning by analyzing the specific learning performances of students in the control group (N=40) and the experimental group (N=39) in CBL learning. We also compared and analyzed the data on the evaluation scores of students' work by teachers and AI tools at the same time in an attempt to identify whether AI tools can replace teachers' comprehensive evaluation. In addition, a questionnaire was used to investigate the positive and negative impacts of AI tools on case study to identify whether the AI tool can be used as an important adjunct to medical biochemistry classroom teaching. </sec> <sec> <title>RESULTS</title> The results of the study showed that AI tools in the experimental group significantly shorten the time students spend on assignments in case study and assist students to obtain higher scores in quizzes (P&lt;0.05). In addition, the questionnaire data showed no significant difference between the AI evaluation and the instructor's evaluation scores (P&gt;0.05), but the group using the AI tool scored higher than the control group (P&lt;0.05). And while the majority of students (M=8.5) agreed with the idea that AI tools can provide basic information retrieval and knowledge expansion, more students (M=4.2) also believed that AI tools have flaws in answering complex and logical questions. In addition, students (M=7.17) generally have concerns that the use of AI tools reduces the communication between teachers and students and the tools have limitations in offering innovative and creative knowledge (M=5.5). As a result, such tools are not a complete replacement for existing digital resources and can lead to homogenized learning (M=8.12). </sec> <sec> <title>CONCLUSIONS</title> GAI tools as “smart teaching assistants” can significantly improve students' learning efficiency in medical biochemistry CBL learning and result in better performance (assignments and exam scores). </sec>

Ähnliche Arbeiten