The Bane of AI in Teaching: Innovation Resistance in Higher Education Instructional Design & Delivery

Abstract

Technology integration is becoming a norm in the education industry, with Al gaining increasing popularity to help improve academic productivity and efficiency. This study proposes to take a different perspective of technology adoption by examining resistance to the use of Al by higher education teachers, despite the tools' and applications' known advantages. The study involves the use of an extended innovation resistance theory (IRT) to achieve the research objective of identifying different functional and psychological barriers, as well as technological and self- inefficacy barriers to Al adoption in instructional design. Moreover, the extent of innovation resistance will be further determined based on the use of Al technologies in various instructional design phases based on the ADDIE Model and expected teaching practitioners' skills and competencies based on the SEIA 8 standards. A mixed-method approach will be used to collect and analyze both quantitative data about Al utilization and qualitative data to determine the barriers, including why such exist. The output of this research aims to help identify opportunities for enhancing teacher competency in technology integration in higher education, Al advocacy, and policy development on the responsible and ethical use of Al in instructional design.