Generative AI Adoption in Classroom in Context of Technology Acceptance Model (TAM) and the Innovation Diffusion Theory (IDT)
This research addresses the challenge of integrating AI tools in education by identifying key acceptance factors for educators, though it is incremental as it applies existing theoretical frameworks to a new context.
The study investigated factors influencing educators' acceptance of generative AI and large language models in classrooms, finding a strong positive correlation between perceived usefulness and acceptance, with perceived ease of use also playing a significant role.
The burgeoning development of generative artificial intelligence (GenAI) and the widespread adoption of large language models (LLMs) in educational settings have sparked considerable debate regarding their efficacy and acceptability.Despite the potential benefits, the assimilation of these cutting-edge technologies among educators exhibits a broad spectrum of attitudes, from enthusiastic advocacy to profound skepticism.This study aims to dissect the underlying factors influencing educators' perceptions and acceptance of GenAI and LLMs.We conducted a survey among educators and analyzed the data through the frameworks of the Technology Acceptance Model (TAM) and Innovation Diffusion Theory (IDT). Our investigation reveals a strong positive correlation between the perceived usefulness of GenAI tools and their acceptance, underscoring the importance of demonstrating tangible benefits to educators. Additionally, the perceived ease of use emerged as a significant factor, though to a lesser extent, influencing acceptance. Our findings also show that the knowledge and acceptance of these tools is not uniform, suggesting that targeted strategies are required to address the specific needs and concerns of each adopter category to facilitate broader integration of AI tools.in education.