Impact of generative artificial intelligence feedback on online student satisfaction

Abstract

Introduction The rapid expansion of Generative Artificial Intelligence (GAI) is reshaping pedagogical practices and educational policies worldwide. One of its most notable contributions is its capacity to deliver personalized feedback, which has the potential to enhance student learning and academic performance. This study aims to propose and validate a conceptual model that examines the factors influencing student behavior in response to GAI-mediated feedback in online learning environments. Methods A Massive Open Online Course (MOOC) titled “Transforming Education with AI: ChatGPT” was designed within a university setting, in which students received feedback on their activities through the GAI tool ChatGPT. Data were collected through a survey completed by 161 participants. The proposed model was evaluated and validated using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results Findings indicate that students hold a positive perception of GAI as a tool for receiving feedback within their learning process. Although concerns related to privacy and security remain, these factors do not exert a significant influence on students’ overall satisfaction with GAI-mediated feedback. Discussion The results suggest that GAI-mediated feedback is well-received by students and can be integrated effectively into online learning environments. While issues surrounding privacy and security should not be overlooked, they do not appear to hinder students’ acceptance or satisfaction. These insights contribute to the development of evidence-based strategies for the pedagogical incorporation of GAI in higher education.

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