Utilizing NotebookLM as an AI Tool to Increase the Productivity of Lecturers Teaching Introductory Economics Courses

Abstract

Introduction to Economics (IE) courses are often challenging for lecturers due to their dense material and limited credit allocation, covering both micro and macroeconomic aspects. This study aims to explore the effectiveness of NotebookL.M, a Large Language Model (LLM)-based tool, in improving lecturer productivity in preparing IEE course materials. Using a descriptive case study approach, the tool was applied to the Introduction Chapter of the IEE module. The results show that NotebookLM significantly reduced material preparation time by providing quick summaries, identifying references, and extracting key points, allowing lecturers to control the flow of the material more efficiently. Furthermore, the tool proved effective in generating trigger questions that increased student engagement in the module and accelerated their understanding of graphical illustrations. This use of Al technology demonstrates lecturers' ability to adapt to digital innovation, which has become increasingly crucial post-COVID-19 pandemic. The results of this study indicate that exploring dense, quantitative material can be facilitated with Al tools, potentially creating a more focused and. enjoyable learning experience for students.