TY - GEN
T1 - Assessment and Feedback in the Generative AI Era: Transformative Opportunities, Novel Assessment Strategies and Policies in Higher Education
AU - Souppez, Jean-Baptiste R. G.
AU - Goswami, Debjani
AU - Yuen, Joe
N1 - This is an accepted manuscript of a paper accepted for presentation at the 2023 IFNTF Symposathon.; International Federation of National Teaching Fellows Symposathon 2023, IFNTF Symposathon 2023 ; Conference date: 04-12-2023 Through 05-12-2023
PY - 2023/12/4
Y1 - 2023/12/4
N2 - Technological advances influence and shape education to ensure learners meet the ever-evolving real-world demand. The advent of generative artificial intelligence (GAI) has profoundly and suddenly disrupted higher education. While concerns have been raised about the ethical use of GAI, particularly to ensure academic integrity, artificial intelligence in education (AIEd) offers transformative opportunities for learners, educators, and institutions. Here we show the transformative potential of AIEd in Assessment and Feedback, address academic integrity concerns while offering assessment strategies that empower learners and educators to employ GAI. Further, we offer a review of latest policies, and an overview of upcoming changes to policies inherent to the use of GAI in higher education. These findings provide novel insight into the fast-changing field of AIEd, inform educators about relevant assessment strategies in the generative AI era, and may contribute to the development and enhancement of policies associated with assessment and feedback.
AB - Technological advances influence and shape education to ensure learners meet the ever-evolving real-world demand. The advent of generative artificial intelligence (GAI) has profoundly and suddenly disrupted higher education. While concerns have been raised about the ethical use of GAI, particularly to ensure academic integrity, artificial intelligence in education (AIEd) offers transformative opportunities for learners, educators, and institutions. Here we show the transformative potential of AIEd in Assessment and Feedback, address academic integrity concerns while offering assessment strategies that empower learners and educators to employ GAI. Further, we offer a review of latest policies, and an overview of upcoming changes to policies inherent to the use of GAI in higher education. These findings provide novel insight into the fast-changing field of AIEd, inform educators about relevant assessment strategies in the generative AI era, and may contribute to the development and enhancement of policies associated with assessment and feedback.
M3 - Conference contribution
BT - IFNTF Symposathon, Augmenting Teaching Excellence: Embracing the future of Education with AI and Emerging Technologies
PB - International Federation of National Teaching Fellows
ER -