Principal Investigator: Christopher Munsell, Associate Professor of Professional Practice in Real Estate Finance (GSAPP)
Summary: In 2023, our research investigated how large language models (LLMs) can be effectively leveraged in a real estate finance course and in professional practice. We chose the Joint Venture (JV) Waterfall (an essential real estate finance concept) as a learning objective and used a mixed-methods approach to evaluate the effectiveness of ChatGPT as an instructional tool, assigning students to either a control group with traditional instruction or a treatment group using ChatGPT to independently complete a JV waterfall modeling assignment in Microsoft Excel.
In our 2023 iteration of the study, we assessed ChatGPT as a replacement for classroom instruction by comparing classroom instruction without ChatGPT vs. ChatGPT without classroom instruction. At the ARES conference, the discussant suggested a follow-up iteration of the study that would assess ChatGPT as a supplement to classroom instruction by introducing a new comparison group: ChatGPT WITH course instruction, again compared to classroom instruction without ChatGPT. Our finding that ChatGPT impaired learning provides an important counterpoint to a number of studies reporting enhanced student performance with AI assistance in professional schools (Kavadella et al., 2024). Our proposed second iteration examining ChatGPT WITH course instruction is required to draw a complete conclusion about whether LLMs are detrimental to learning or whether they can supplement but not replace classroom instruction (Altamimi et al., 2023).