academic management, generative artificial intelligence, Gemini 2.5 Pro, educational automation, prompt (#292)

Authors

Mena, Lucas

Cavalcanti, Dorian

Wong, Lenis

Abstract

Student management often faces challenges related to organizing academic information and producing timely, accurate reports. To address these limitations, this work proposes an approach for improving student management using Gemini 2.5 Pro. The development process involved four stages: (i) preprocessing an academic dataset containing 311 records and 35 variables; (ii) designing tailored prompts to generate personalized reports; (iii) integrating the model through the Google Generative AI API; and (iv) implementing a web-based prototype capable of producing performance summaries, study plans, and formal communications. Evaluation with a student user showed that the system successfully generated study plans, overall performance summaries, recommendations, review plans, progress analyses, attendance reports, and insights on strengths and learning habits. The outputs were coherent, contextually relevant, and clearly articulated. These results highlight the potential of advanced AI tools to support school management processes, streamline academic tasks through automation, and enhance pedagogical monitoring by leveraging real institutional data.