Reseña

This guide offers a structured approach to integrating generative AI (GenAI) into academic workflows. It distinguishes between education (teaching/learning) and research (discovery/analysis), and provides frameworks, tools, and ethical guidelines for each. The most effective way to view GenAI in academia is as a tireless research assistant. It excels at summarization, translation, and code generation, but it lacks reliable sources and a genuine understanding of GenAI code when not properly reviewed. In short, for educators and students, GenAI shifts the focus from content retention to critical evaluation.