To accept or not to accept? An IRT-TOE Framework to Understand Educators' Resistance to Generative AI in Higher Education
Project Overview
The document examines the role of Generative Artificial Intelligence (GenAI) in higher education, emphasizing the challenges educators encounter in adopting these technologies. It identifies a gap in existing research that predominantly focuses on student acceptance of GenAI tools, while neglecting the educators' perspectives, which are vital for successful integration. To address this, the authors advocate for a theoretical framework that merges Innovation Resistance Theory (IRT) with Technology-Organization-Environment (TOE) models to better comprehend the resistance educators may face. They propose a mixed-method research approach to investigate these barriers, underscoring the importance of understanding both acceptance and resistance to enhance technology use in educational settings. The findings suggest that addressing educators' concerns and perspectives is essential for the effective implementation of GenAI in higher education, ultimately leading to improved teaching and learning outcomes.
Implementation Barriers
Psychological Barrier
Resistance stemming from established norms and practices within academic institutions, alongside concerns regarding the impact of GenAI on academic integrity and personal reputation.
Proposed Solutions: Educators require support and guidance to adapt to changes and new technologies, alongside promoting discussions on academic integrity and providing resources that emphasize ethical use of GenAI.
Risk Barrier
Concerns about academic fraud, reliance on AI tools, and the potential for inaccuracy in outputs.
Proposed Solutions: Develop guidelines for verifying outputs and educating students on critical thinking.
Usage Barrier
Challenges in evaluating student work due to the ease of generating content with GenAI tools.
Proposed Solutions: Adapt evaluation methods to assess student understanding beyond traditional assignments.
Value Barrier
Concerns about the equitable access and intrinsic value of GenAI tools in education.
Proposed Solutions: Ensure equitable access to GenAI tools and provide training on their educational value.
Organizational Barrier
Lack of institutional support and policies for the integration of GenAI tools.
Proposed Solutions: Establish institutional policies that support the use of GenAI in education and provide training for educators.
Environmental Barrier
External regulations and societal pressures that influence the adoption of GenAI tools.
Proposed Solutions: Engage stakeholders in discussions about the implications of regulations and promote a culture of innovation.
Project Team
Jan-Erik Kalmus
Researcher
Anastasija Nikiforova
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Jan-Erik Kalmus, Anastasija Nikiforova
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai