Formative feedback with generative artificial intelligence: A case study

Abstract

Generative artificial intelligence has burst into the teaching and learning process in higher education, where one of the representative developments is OpenIA's ChatGPT. Likewise, among the most useful uses of this tool are evaluative processes where they allow automatic and personalized feedback to be provided. An exploratory study is presented whose objective was to analyze the capacity of generative artificial intelligence to offer formative feedback to a learning activity of a subject of the psychology career of the National Autonomous University of Mexico that is taught with the support of a Technological platform. As part of the study methodology, four works prepared by the students were randomly selected and evaluated and provided feedback by the teacher responsible for the subject, the same ones that the ChatGPT-4 was fed with. The results indicate that the intelligent system partially identifies the quality of the activities carried out, there was a discrepancy in the grades assigned with the responsible teacher, however, its ability to provide personalized feedback in accordance with the selected model stands out. It is concluded that it is necessary to train the system with a greater number of tasks and precision in the instructions (prompts).