The Future of Education
The Desired Path: Generative AI in Higher Education
Diana Koroleva, Higher School of Economics, Institute of Education, Laboratory for Educational Innovation Research, Moscow (Russian Federation)
Abstract
The rapid advancement of generative artificial intelligence (GAI) has spurred innovative transformations in higher education. Universities, as bastions of Innovations, must adapt to the evolving landscape. Understanding faculty responses towards the instructional use of GAI is crucial for predicting its educational impact. Firstly, concerns and expectations aids in formulating interventions to alleviate apprehensions and foster an environment conducive to GAI adoption. Secondly, comprehending faculty expectations ensures that technical advancements align with instructional objectives. Faculty input is invaluable in developing GAI systems that adhere to educational best practices.
This study guided by the Technology Acceptance Model and the concept of the Desired Path. Data were collected from university faculties. Semi-structured interviews conducted via Zoom allowed for in-depth exploration of faculty perspectives (N=10). The methodological section of the article outlines the use of ChatGPT for conducting thematic analysis and includes original prompts.
This research identifies worries, including doubts about GAI-supported teaching aids' effectiveness, job displacement, and loss of autonomy. Stakeholders should coordinate efforts to address those by providing methodological support, capacity building, and reassurance to faculty transitioning to GAI-enhanced instructional approaches. Fostering a culture of cooperation, shared decision-making, and transparency promotes faculty ownership and autonomy. Furthermore, integrating GAI advancements with faculty expectations and instructional objectives is paramount. Seeking faculty feedback on desired features, functions, and ethical considerations enables developers to design GAI tools aligned with educational best practices.
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Keywords |
AI, Innovations, desired path |
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References |
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