"Personalized Feedback in Formative Assessment: A Case Study in Mexican Higher Education in the Era of AI"

Abstract

This paper explores the effectiveness of short personalized feedback in formative assessment within the context of higher education, particularly concerning the increasing use of artificial intelligence (AI) in learning assessment. The main objective is to investigate how personalized feedback enhances the learning experience compared to AI-generated feedback, identify challenges and opportunities, and propose practical recommendations. Methodology combines a literature review and case analysis from institutions implementing AI in formative assessment. Results show that while AI feedback is beneficial for its immediacy, personalized feedback has a greater impact on student motivation and comprehension. Conclusion: both forms of feedback can complement each other, but human intervention remains crucial.