Criar, inovar, partilhar: um fluxo de trabalho em torno da inteligência artificial para criar recursos educacionais abertos acessíveis a todos
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Resumo
A educação é uma alavanca estratégica para alcançar vários objetivos de desenvolvimento sustentável (ODS) estabelecidos pela ONU. No entanto, ela se desenvolve num contexto demográfico duplamente tenso: uma demanda crescente por educação em muitas regiões do mundo, diante da falta de recursos, tanto materiais (infraestruturas, instalações) quanto humanos (escassez de professores). Neste contexto, os recursos educacionais abertos (REA) surgem como um dispositivo pedagógico indicado para promover o acesso e a difusão do conhecimento em grande escala. A inteligência artificial generativa (IAg) vem hoje reforçar este potencial. Muitas EdTech oferecem soluções que permitem gerar automaticamente conteúdos pedagógicos integráveis em ambientes digitais (LMS). No entanto, criar REA de qualidade exige mais do que o uso da tecnologia: pressupõe uma abordagem rigorosa, guiada por princípios pedagógicos e éticos. Este artigo propõe um fluxo de trabalho em dez etapas para integrar a IAg na concepção de REA. Cada etapa especifica as possíveis contribuições da IAg, exemplos de prompts e ferramentas que podem ser utilizadas, com o apoio de um quadro de síntese recapitulativo.
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Referências
Avraamidou, L. (2024). Can we disrupt the momentum of the AI colonization of science education? Journal of Research in Science Teaching, 61(10), 2570-2574. https://doi.org/10.1002/tea.21961 DOI: https://doi.org/10.1002/tea.21961
Bender, E. M., Gebru, T., McMillan Major, A., et Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? Dans Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT) (p. 610-623). https://doi.org/10.1145/3442188.3445922 DOI: https://doi.org/10.1145/3442188.3445922
Bloom, B. S., Engelhart, M. D., Furst, E. J., Hill, W. H., et Krathwohl, D. R. (1956). Taxonomy of educational objectives: The classification of educational goals. Handbook I: Cognitive domain. Longmans, Green.
Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D., Wu, J., Winter, C., … Amodei, D. (2020). Language Models are Few-Shot Learners. Dans H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, et H. Lin (dir.), Advances in Neural Information Processing Systems (Vol. 33, p. 1877‑1901). Curran Associates Inc. https://proceedings.neurips.cc/
Bulathwela, S., Pérez-Ortiz, M., Holloway, C., Cukurova, M., et Shawe-Taylor, J. (2024). Artificial intelligence alone will not democratise education: On educational inequality, techno-solutionism and inclusive tools. Sustainability. 16(2), 781. https://doi.org/10.3390/su16020781 DOI: https://doi.org/10.3390/su16020781
Celik, I., Dindar, M., Muukkonen, H., et Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: A systematic review of research. TechTrends, 66, 616-630. https://doi.org/10.1007/s11528-022-00715-y DOI: https://doi.org/10.1007/s11528-022-00715-y
Chan, C. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20, article 38. https://doi.org/10.1186/s41239-023-00408-3 DOI: https://doi.org/10.1186/s41239-023-00408-3
Compilatio (2023, 17 juillet). Les menaces et les limites des IA dans l’enseignement. https://www.compilatio.net/blog/limites-ia-enseignement
Dublin Core Metadata Initiative (2022). Dublin Core metadata element set, version 1.1. https://www.dublincore.org/documents/dces/
E Skilled AI Course Creator. (2025, 1er juillet). Avantages et utilisations de l’IA dans l’éducation : statistiques clés sur l’IA. https://aicoursecreator.eskilled.io/fr/blog/avantages-et-utilisations-de-lia-dans-leducation-statistiques-cles-sur-lia/
European Commission (2022). Ethical guidelines for educators on using artificial intelligence and big data in teaching and learning. Directorate General for Education, Youth, Sport and Culture. https://education.ec.europa.eu/news/ethical-guidelines-on-the-use-of-artificial-intelligence-and-data-in-teaching-and-learning-for-educators
fabriqueREL (s.d.). Le parcours de création en 6 étapes. https://fabriquerel.org/processus-de-creation
Fournier, C., Laroussi, M. (2023). Les ressources éducatives libres pour tous et tout au long de la vie en réponse à l’objectif de développement durable n°4. Dans F. Chevalier et M. Kalika (dir.), Recherches sur la sustainability. Éditions EMS.
France Éducation International (2022). « Université sans les murs » : vers un enseignement hybride au Togo. https://www.france-education-international.fr/actualites/lettre-fei/2022-02/universite-sans-les-murs
IMS Global Learning Consortium. (2022). Learning Tools Interoperability (LTI) 1.3: Core specification. IMS Global Learning Consortium. https://www.imsglobal.org/spec/lti/v1p3
Krathwohl, D. R. (2002). A Revision of Bloom’s Taxonomy: An Overview. Theory Into Practice, 41(4), 212-218. https://doi.org/10.1207/s15430421tip4104_2 DOI: https://doi.org/10.1207/s15430421tip4104_2
Laroussi, M. (2012). Scénarios d’apprentissage flexibles. Dans C. Depover et B. De Lièvre (dir.), Industries de la connaissance, éducation, formation et technologies. Bruxelles : De Boeck.
Mulyani, H., Istiaq, M. A., Shauki, E. R., Kurniati, F., & Arlinda, H. (2025). Transforming education: exploring the influence of generative AI on teaching performance. Cogent Education, 12(1). https://doi.org/10.1080/2331186X.2024.2448066 DOI: https://doi.org/10.1080/2331186X.2024.2448066
OECD (2024) OECD Digital Economy Outlook 2024 (Volume 1) Embracing the Technology Frontier. OECD Publishing. https://doi.org/10.1787/a1689dc5-en DOI: https://doi.org/10.1787/a1689dc5-en
Popenici, S. A. D., et Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12, article 22. https://doi.org/10.1186/s41039-017-0062-8 DOI: https://doi.org/10.1186/s41039-017-0062-8
Saklani, S., et Singh, D. (2024). Minimizing carbon emissions by improving water and energy use efficiencies in AI servers: A green cloud computing strategy for sustainable artificial intelligence systems. International Journal of Innovative Science and Research Technology, 9(9). https://doi.org/10.38124/ijisrt/IJISRT24SEP1195 DOI: https://doi.org/10.38124/ijisrt/IJISRT24SEP1195
Smith, B., Schatz, S., et Tuner, J. (2021). Total learning architecture data model for analytics and interoperability. ADL Initiative. IITSEC 2021 Paper No. 21358 https://www.adlnet.gov/assets/uploads/2021 --- (IITSEC) Total Learning Architecture Data Model for Analytics and Adaptation.pdf
UNESCO (2019). La Recommandation 2019 de l’UNESCO sur les ressources éducatives libres (REL) : soutenir l’accès universel à l’information grâce à des matériels d’apprentissage ouverts de qualité. https://unesdoc.unesco.org/ark:/48223/pf0000383205_fre.locale=en
UNESCO (2020). AI and education: Guidance for policy makers. https://unesdoc.unesco.org/ark:/48223/pf0000376709
UNESCO (2021) Repenser nos futurs ensemble : un nouveau contrat social pour l’éducation. https://unesdoc.unesco.org/ark:/48223/pf0000388310.locale=en
UNESCO (2023). Guidance for generative artificial intelligence (GenAI) in education and research. https://www.unesco.org/en/articles/guidance-generative-ai-education-and-research
Van den Berg, G., et du Plessis, E. (2023). ChatGPT and generative AI: Possibilities for its contribution to lesson planning, critical thinking and openness in teacher education. Education Sciences, 13(10), 998. https://doi.org/10.3390/educsci13100998 DOI: https://doi.org/10.3390/educsci13100998
Wiley, C. (2014). Metadata use in research data management. Bulletin of the Association for Information Science and Technology, 40(6), 40-43. DOI: https://doi.org/10.1002/bult.2014.1720400612
World Bank (2023). Primary school enrolment in Nigeria has increased over two decades, with more male enrolments annually. Intelpoint. https://intelpoint.co/insights/primary-school-enrolment-in-nigeria-has-increased-over-two-decades-with-more-male-enrolments-annually/
Zawacki Richter, O., Marín, V. I., Bond, M., et Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – Where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0171-0 DOI: https://doi.org/10.1186/s41239-019-0171-0
Zou, D., Xie, H., et Kohnke, L. (2025). Navigating the future: Establishing a framework for educators’ pedagogic artificial intelligence competence. European Journal of Education, 60. https://doi.org/10.1111/ejed.70117 DOI: https://doi.org/10.1111/ejed.70117