Supplementary materials from an educational study on RE4HCAI and Human-Centered AI Requirements Engineering.

This dataset compiles the teaching and research materials used in an educational study conducted with undergraduate students at the Federal University of Amazonas. The study investigated the use of an educational approach to support the teaching of Requirements Engineering for AI-based systems. The instruments were developed and/or adapted to support the teaching-learning process, foster a critical understanding of the RE4HCAI framework guidelines, and collect evidence about the students' experiences.The repository includes:Informed Consent Form: A document signed by the participants describing the objectives of the study, the methodology, voluntary participation, and the use of the collected data for academic and scientific purposes.Lecture Slides: A set of illustrative slides in Portuguese, designed to present the six RE4HCAI guidelines in an accessible way, including practical examples and language appropriate for undergraduate students.Checklist (adapted version): A Portuguese adaptation of the original checklist proposed by Ahmad et al. (2023), reduced from over 100 items to 63 items, with linguistic adjustments and a pedagogical focus to support conceptual understanding and critical classroom discussion. Practical Activity Support Material: Description of a fictitious AI-based system (an academic search portal) created to allow the application of the checklist guidelines in a realistic requirements gathering scenario.Participant Characterization Form: Pre-activity questionnaire to collect participant profile data (e.g., course/semester and familiarity with AI and Requirements Engineering).Evaluation and Feedback Form: Instrument applied after the activity, including specific questions about the guidelines and a general evaluation section to capture perceptions, learning outcomes, difficulties, and suggestions on the use of the framework.These materials can be reused, adapted, or replicated by researchers and instructors interested in critical and human-centered approaches to teaching Requirements Engineering for Artificial Intelligence systems.