Role of Generative Artificial Intelligence (GenAI) in Food and Nutrition Education: State of The Art Review.
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Date
2025-11-03
Authors
Luque Loor, Andy Hermógenes
Ocampo Bustos, Emilio Faraday
Espinosa Estrella, Wilson Javier
Pinoargote Roldán, Nilda Margarita
Cedeño Orejuela, José André
Melis Sosa, Ariel
Añazco Moreira, Paola Ceciliana
Vinces Sornoza, Tatiana Paola
Villavicencio Macías, Reina Yadira
Pino Andrade, Silvia Cristina
Journal Title
Journal ISSN
Volume Title
Publisher
Universidad de Murcia, Servicio de Publicaciones
Abstract
La inteligencia artificial generativa (IAG) está emergiendo en la educación alimentaria ynutricional, ofreciendo herramientas de aprendizaje adaptativo y apoyo al asesoramiento, aunquetambién generando inquietudes sobre su precisión, integridad y equidad. Esta revisión examinacríticamente el papel de la IAG a través de cuatro dimensiones: aplicaciones, beneficios, desafíos ycontribuciones al aprendizaje personalizado, para responder a la pregunta de cuál es su función enla educación alimentaria y nutricional. Se incluyeron estudios revisados por pares, publicados eninglés y español (enero de 2021 a agosto de 2025), que abordaban la IA generativa o conversacional(p. ej., modelos de lenguaje complejos, chatbots) en contextos educativos o de nutrición aplicada. Seexcluyeron los temas ajenos a la nutrición, los informes puramente técnicos, los artículos deopinión, las preimpresiones, los duplicados y la IA no generativa. Las búsquedas en PubMed,Scopus y Web of Science arrojaron nueve estudios tras una doble revisión. La síntesis narrativaidentificó aplicaciones de GenAI en la docencia universitaria, programas de nutrición familiar ydietética clínica para generar materiales accesibles, personalizar cuestionarios y retroalimentación, yapoyar el aprendizaje dietético. Entre los beneficios reportados se incluyeron una mejora en elconocimiento nutricional de los padres, una mayor participación estudiantil bajo supervisión y larelación entre la alfabetización nutricional digital y los comportamientos alimentarios sostenibles.Los desafíos abarcaron la adherencia inconsistente a las guías dietéticas en casos complejos, lasensibilidad al lenguaje y al enfoque de las preguntas, los riesgos para la integridad académica y laprivacidad, y las desigualdades digitales que requieren alfabetización en IA y supervisión. Engeneral, GenAI funciona de manera más efectiva como un complemento supervisado que mejora elacceso y la personalización, a la vez que salvaguarda la calidad. Garantizar la alineación con losestándares profesionales, la revisión por expertos, la transparencia y la adaptación contextual es esencial para promover responsablemente su valor educativo.
Generative artificial intelligence (GenAI) is emerging in food and nutrition education,offering adaptive learning tools and counseling support while raising concerns about accuracy,integrity, and equity. This review critically examines the role of GenAI through four dimensions—applications, benefits, challenges, and contributions to personalized learning—to answer thequestion of what is the role of GenAI in food and nutrition education. Peer-reviewed English- and Spanish-language studies (January 2021–August 2025) addressing generative or conversational AI(e.g., large language models, chatbots) in educational or applied nutrition contexts were included.Exclusions comprised non-nutrition topics, purely technical reports, opinion papers, preprints, duplicates, and non-generative AI. Searches in PubMed, Scopus, and Web of Science yielded ninestudies after dual screening. Narrative synthesis identified applications of GenAI in universityteaching, family nutrition programs, and clinical dietetics to generate readable materials, tailorquizzes and feedback, and support dietary learning. Reported benefits included improved parentalnutrition knowledge, enhanced student engagement under supervision, and associations between digital nutrition literacy and sustainable eating behaviors. Challenges encompassed inconsistentadherence to dietary guidelines in complex cases, sensitivity to language and prompt framing, risksto academic integrity and privacy, and digital inequities requiring AI literacy and oversight. Overall, GenAI functions most effectively as a supervised adjunct that enhances access andpersonalization while safeguarding quality. Ensuring alignment with professional standards, expertreview, transparency, and contextual adaptation is essential to responsibly advance its educational value.
Generative artificial intelligence (GenAI) is emerging in food and nutrition education,offering adaptive learning tools and counseling support while raising concerns about accuracy,integrity, and equity. This review critically examines the role of GenAI through four dimensions—applications, benefits, challenges, and contributions to personalized learning—to answer thequestion of what is the role of GenAI in food and nutrition education. Peer-reviewed English- and Spanish-language studies (January 2021–August 2025) addressing generative or conversational AI(e.g., large language models, chatbots) in educational or applied nutrition contexts were included.Exclusions comprised non-nutrition topics, purely technical reports, opinion papers, preprints, duplicates, and non-generative AI. Searches in PubMed, Scopus, and Web of Science yielded ninestudies after dual screening. Narrative synthesis identified applications of GenAI in universityteaching, family nutrition programs, and clinical dietetics to generate readable materials, tailorquizzes and feedback, and support dietary learning. Reported benefits included improved parentalnutrition knowledge, enhanced student engagement under supervision, and associations between digital nutrition literacy and sustainable eating behaviors. Challenges encompassed inconsistentadherence to dietary guidelines in complex cases, sensitivity to language and prompt framing, risksto academic integrity and privacy, and digital inequities requiring AI literacy and oversight. Overall, GenAI functions most effectively as a supervised adjunct that enhances access andpersonalization while safeguarding quality. Ensuring alignment with professional standards, expertreview, transparency, and contextual adaptation is essential to responsibly advance its educational value.
Description
Keywords
Chat GPT , Food and Nutrition Education , Nutrition Education , Inteligencia Artificial Generativa , Educación Alimentaria y Nutricional , Educación Nutricional , Generative Artificial Intelligence
Citation
Zambrano Zambrano, G. P., Luque Loor, A. H., Ocampo Bustos, E. F., Espinosa Estrella, W. J., Pinoargote Roldán, N. M., Cedeño Orejuela, J. A., … Pino Andrade, S. C. (2025). Papel de la Inteligencia Artificial Generativa (IAGen) en la Educación Alimentaria y Nutricional: Revisión del Estado del Arte. Revista Española De Educación Médica, 6(6).
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