Generative Artificial Intelligence in Education: Bridging the Gap between Opportunity and Teacher Readiness via the Extended UTAUT Framework

Abstract

The world of education is undergoing a transformative paradigm shift, as generative artificial intelligence is being integrated into the learning environment. The rapid development in Generative AI recently have revolutionized the classroom and teaching methodologies. In that regard, this study focuses on how teachers perceive generative AI under the formulation of an Extended UTAUT (Unified Theory of Acceptance and Use of Technology) model, the advantages and challenges related with its application. A descriptive method was adopted for this study and teachers' perceptions in regard to Performance Expectancy (pedagogical effectiveness) and Effort Expectancy (AI literacy) was explored. Data were obtained from 146 teachers through use of survey methodology. Descriptive and inferential statistics were used in the analysis of the collected data. The result has a crucial difference, because the perceived pedagogical utility and the technical expertise may amend the teacher's confidence for using the system. However, lack of indispensable facilitating conditions (deficient training, unclear governance etc) and ethical concerns may hinder implementation. These findings emphasize the urgent demand for professional development and clear institutional policy, announced by the UNESCO (2023) and Floridi et al. (2018) normative anchors. By isolating the crucial components of fairness, accountability, and agency which underpin the factors most predictive of teacher readiness, this study lays a framework for leaders and policy makers searching to translate teacher doubt into enthusiastic and responsible carrying out of AI tools. Clearly defining governing rules, strengthening facilitating conditions, will help address the fears that shortly impede the adoption of generative AI in schools.