BIG DATA AND AI-BASED STRATEGIES FOR IDENTIFYING AND SUPPORTING HIGHLY ABLE/GIFTED STUDENTS IN INCLUSIVE SCHOOLS: CRITICAL ANALYSIS AND INTERVENTION PROPOSALS

This research explores the use of Artificial Intelligence (AI) and Big Data to identify and support gifted students in inclusive contexts, promoting personalized educational practices. The investigation starts from the issue of how these technologies can be applied ethically and effectively to meet the educational needs of gifted students . The main objective is to analyze strategies that guarantee an adapted and inclusive education, respecting the diversity of abilities. The methodology adopted includes the neoperspectivist paradigm giftedean , aligned with the theories of Multiple Intelligence, Educational Inclusion, Inclusive Pedagogical Practices and Educational Artificial Intelligence. The research follows the hypothetical-deductive method and uses a Narrative Bibliographic and Documentary Review, with consultation of databases such as Scopus , Web of Science and ERIC, resulting in 62 analyzed papers. The main findings indicate that AI and Big Data are effective in identifying and personalizing pedagogical practices, although the need for continuous training for educators and ethical protocols are crucial. The gaps found highlight the lack of longitudinal empirical studies and consolidated ethical guidelines. As limitations, the research is limited to a narrative review, without direct empirical investigation. The contributions include theoretical and methodological advances that guide the inclusive use of AI and Big Data in education, adding value to the field, Science and society by promoting an education that values diversity and the potential of students.