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The desire path: unleashing expectations, discussing apprehensions, and proposing a way forward for GAI use in higher education
This qualitative study examines the expectations, concerns, and future directions regarding the use of generative artificial intelligence (GAI) in higher education from the faculty’s viewpoint. It employs a combination of the Social Construction of Technology (SCOT) framework to evaluate faculty perceptions of GAI usability and the Technological Acceptance Model (TAM) to illustrate how human behaviors influence the adoption and utilization of technology. The Desire Path approach is employed to chart the way forward based on expectations and apprehensions toward GAI use. The thematic analysis of interviews with eleven participants illuminates their opinions regarding the GAI integration in education. The methodological section of the article outlines the use of GAI for conducting thematic analysis of the interviews and has practical application for research. The findings revealed strategies for successfully incorporating GAI into educational settings, taking into account diverse expectations, including the idea of continuous technology improvement, gradual user adjustment and acclimatization, and context-dependent utilization. They also emphasized the significance of collective intelligence and interdisciplinary collaboration in balancing the pros and cons of GAI for teaching and learning. The concerns related to the risks of undermining fundamental aspects of higher education, reducing human involvement, causing ethical shortcomings, and challenging in terms of data privacy and security. The Desire Path lies in embracing data-driven decision-making regarding GAI, prioritizing professional development, and engaging with different stakeholders.