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Paper Type
Complete
Abstract
Generative Artificial Intelligence (GenAI) tools, such as ChatGPT and DALL-E, are poised to disrupt higher education (HE), with many academics advocating their broader adoption. Yet, this has been met with resistance from policymakers as they have imposed strict bans on these AI tools, citing numerous concerns. This study addresses this dichotomy between research enthusiasm and the lack of practical application by conducting a scoping literature review into GenAI’s suggested uses and any associated challenges. The findings show diverse applications for GenAI tools in academia, ranging from "Content Delivery Improvement" and "Assessment Aid" for educators to "Personalized Learning," "Writing Support," and "In-Time Feedback" for students. However, these advantages are counterbalanced by challenges, many of which lack straightforward solutions. This research contributes to the ongoing discourse regarding the potential of GenAI tools in HE. It identified a significant gap in the current literature as well as recommends cautious adoption of GenAI tools.
Paper Number
1636
Recommended Citation
Pit, Pagnarith; Linden, Tanya; and Mendoza, Antonette, "Generative Artificial Intelligence in Higher Education: One Year Later" (2024). AMCIS 2024 Proceedings. 11.
https://aisel.aisnet.org/amcis2024/is_education/is_education/11
Generative Artificial Intelligence in Higher Education: One Year Later
Generative Artificial Intelligence (GenAI) tools, such as ChatGPT and DALL-E, are poised to disrupt higher education (HE), with many academics advocating their broader adoption. Yet, this has been met with resistance from policymakers as they have imposed strict bans on these AI tools, citing numerous concerns. This study addresses this dichotomy between research enthusiasm and the lack of practical application by conducting a scoping literature review into GenAI’s suggested uses and any associated challenges. The findings show diverse applications for GenAI tools in academia, ranging from "Content Delivery Improvement" and "Assessment Aid" for educators to "Personalized Learning," "Writing Support," and "In-Time Feedback" for students. However, these advantages are counterbalanced by challenges, many of which lack straightforward solutions. This research contributes to the ongoing discourse regarding the potential of GenAI tools in HE. It identified a significant gap in the current literature as well as recommends cautious adoption of GenAI tools.
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