Self-regulation of learning from a peer feedback approach: insights from generative AI

Abstract

This research presents how the adoption of self-regulation strategies using peer feedback and chatbots promotes the transformation of online assessment. The evaluation of the design of a learning activity that integrates a peer feedback intervention to suggest improvements in academic essay writing is described. Based on a design-based research approach, three main phases are established, a first one for the design of the proposal and two consecutive implementations. In the first, a satisfaction questionnaire was distributed to 348 students and the analysis of the responses was used to redesign the proposal. In the second implementation, a questionnaire was used with 24 students and a group interview with the faculty. The results allowed a positive assessment of the relationship between peer feedback and the development of self-regulation and learning to learn competencies. Finally, it is concluded that it is necessary to propose more often strategies of this type that also include the use of AI, thus giving more opportunities to students in the development of their autonomy and a conscious and efficient management of their learning process, so this article also presents a design proposal for a new iteration with AI.