FEEDBACK IN THE ERA OF GENERATIVE AI
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Date
2023-07-03
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Abstract
Purpose: The purpose of this study is to investigate the perception of students and educators in
higher education towards feedback provided by large-language model AI, with feedback
and interaction with human educators.
Theory: Drawing on the dialogism framework and considering the emotional and relational aspects
of feedback, this study examines the role of dialogue and interaction in feedback processes
and the implications of integrating AI-generated feedback with human feedback.
Method: Adopting a qualitative research methodology, the study encompassed focus group
interviews with 17 university students and nine educators across two esteemed Swedish
universities. The gathered data was dissected via thematic analysis, spotting themes that
resonate with the participants' experiences and views on feedback with generative AI and
human instances.
Results: The analysis revealed three main themes, highlighting various aspects of feedback in the
context of using generative AI tools such as ChatGPT alongside human educators. These
themes emphasised the importance of understanding the nature of generative AI and
human feedback, addressing the emotional dimensions of feedback, recognising potential
risks and ethical concerns of using generative feedback, and exploring the integration of
AI-generated feedback with human feedback practices to enhance learning engagement
and outcomes. The findings contribute to the understanding of the potential and risks of
AI-generated feedback in higher education and inform the development of best practices
for integrating AI and human feedback ethically.
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Keywords
AI-generated Feedback,, Dialogism Feedback in Higher Education,, Focus Group Interviews Human Feedback,, Qualitative Research,, Thematic analysis, ChatGPT,, Dialogic Feedback,