DEVELOPMENT OF AN ARTIFICIAL INTELLIGENCE MODEL TO SUPPORT TEACHING IN DYNAMIC EDUCATIONAL ENVIRONMENTS
DOI:
https://doi.org/10.66104/fkfg6q38Keywords:
AI in education, Learning Analytics, educational recommendation, governance and ethicsAbstract
This article proposes an Artificial Intelligence model to support teaching in dynamic educational environments, characterized by student heterogeneity, curricular changes, and multiple modalities. The research addresses the gap in solutions that coherently integrate dynamic learning profiles, continuous progress monitoring, useful recommendations, and governance coupled with the teaching workflow. The study designs a modular, data-driven artifact evaluated in a hybrid scenario using LMS. The architecture operationalizes the cycle “data → inference → intervention → monitoring → replanning,” with layers of data (logs, assessments, and metadata), intelligence (inferences and profiles), intervention (recommendations to students and support for teacher decision-making), experience (dashboards/feedback), and trust (auditing, privacy, and bias mitigation). The core of the model combines risk/proficiency prediction, a recommendation engine based on behavioral signals, and pedagogical rules. To preserve teaching autonomy and reduce socio-ethical risks, it incorporates explainability and a human-in-the-loop module to parameterize, approve, and audit recommendations. The proposed evaluation integrates technical metrics (F1, AUC, Recall@K, NDCG@K, and calibration), pedagogical impact indicators (learning gains, engagement, and teaching load), and equity audits by subgroups, aiming at responsible and sustainable adoption.
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AGUILAR YUSTE, M.; ROJAS-SÁNCHEZ, E. The Teacher and his or her role in the use of Artificial Intelligence: the conflict of AI in the Educational System. International Journal of Research Publications, v. 154, n. 1, 2024. DOI: 10.47119/ijrp1001541820247037. Available at: https://doi.org/10.47119/ijrp1001541820247037. DOI: https://doi.org/10.47119/IJRP1001541820247037
AKBAR, K. F. et al. Inclusive Education Practices: Fostering an Accessible Learning Environment for Diverse Learners, 2023. DOI: 10.59613/global.v1i3.35. Available at: https://doi.org/10.59613/global.v1i3.35. DOI: https://doi.org/10.59613/global.v1i3.35
APETORGBOR, M. et al. Leveraging Artificial Intelligence for Effective Assessment and Evaluation in Education: A Comprehensive Review. [S.l.]: IEEE, 2024. p. 1–6. DOI: 10.1109/idicaiei61867.2024.10842940. Available at: https://doi.org/10.1109/idicaiei61867.2024.10842940. DOI: https://doi.org/10.1109/IDICAIEI61867.2024.10842940
ARMAS, L. Inteligencia artificial en la educación: personalización del aprendizaje y adaptación educativa. CID – Centro de Investigación y Desarrollo, 2023. DOI: 10.37811/cli_w965-41. Available at: https://doi.org/10.37811/cli_w965-41. DOI: https://doi.org/10.37811/cli_w965-41
BAETA, P.; PEDRO, N. Innovative Educational Environments vs Regular Classrooms: Analysis of pedagogical dynamics and learning activities. In: IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI), 2019. [S.l.]: IEEE, 2019. DOI: 10.23919/CISTI.2019.8760765. Available at: https://doi.org/10.23919/CISTI.2019.8760765. DOI: https://doi.org/10.23919/CISTI.2019.8760765
BAYAGA, A. Leveraging AI-enhanced and emerging technologies for pedagogical innovations in higher education. Education and Information Technologies, 2024. DOI: 10.1007/s10639-024-13122-y. Available at: https://doi.org/10.1007/s10639-024-13122-y. DOI: https://doi.org/10.1007/s10639-024-13122-y
CASALINO, G. et al. Incremental and Interpretable Learning Analytics Through Fuzzy Hoeffding Decision Trees. In: [S.l.]: Springer, 2023. p. 674–690. DOI: 10.1007/978-3-031-29800-4_51. Available at: https://doi.org/10.1007/978-3-031-29800-4_51. DOI: https://doi.org/10.1007/978-3-031-29800-4_51
CORTEZ, J. L. Tecnologías emergentes en la educación del siglo XXI. MCJ, v. 1, n. 4, p. 40–55, 2023. DOI: 10.70881/mcj/v1/n4/25. Available at: https://doi.org/10.70881/mcj/v1/n4/25. DOI: https://doi.org/10.70881/mcj/v1/n4/25
DA SILVA, L. C. A. et al. Active methodologies and digital technologies in learning: A systematic literature review. In: IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI), 2022. [S.l.]: IEEE, 2022. p. 1–5. DOI: 10.23919/cisti54924.2022.9820582. Available at: https://doi.org/10.23919/cisti54924.2022.9820582. DOI: https://doi.org/10.23919/CISTI54924.2022.9820582
DWI, M.; HIDAYATULLAH, A. N. A. Machine Learning in Multicultural Education. Pakistan Journal of Life and Social Sciences, v. 22, n. 1, 2024. DOI: 10.57239/pjlss-2024-22.1.0084. Available at: https://doi.org/10.57239/pjlss-2024-22.1.0084. DOI: https://doi.org/10.57239/PJLSS-2024-22.1.0084
EMBARAK, O. Towards an Adaptive Education through a Machine Learning Recommendation System. In: INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2021. [S.l.]: IEEE, 2021. p. 187–192. DOI: 10.1109/ICAIIC51459.2021.9415211. Available at: https://doi.org/10.1109/ICAIIC51459.2021.9415211. DOI: https://doi.org/10.1109/ICAIIC51459.2021.9415211
IGNJATOVIĆ, G. AI technologies in education: Regulatory frameworks at the international, regional, and national level. Zbornik Radova Pravnog Fakulteta u Nišu, v. 63, n. 103, p. 235–260, 2024. DOI: 10.5937/zrpfn1-55374. Available at: https://doi.org/10.5937/zrpfn1-55374. DOI: https://doi.org/10.5937/zrpfn1-55374
IMAN, M. Z.; ASIS, A. A.; RAHMA, A. U. Z. Enhancing Personalized Learning: The Impact of Artificial Intelligence in Education. Edu Spectrum, v. 1, n. 2, p. 101–112, 2024. DOI: 10.70063/eduspectrum.v1i2.55. Available at: https://doi.org/10.70063/eduspectrum.v1i2.55. DOI: https://doi.org/10.70063/eduspectrum.v1i2.55
JAIN, L. R.; MENON, V. AI Algorithmic Bias: Understanding its Causes, Ethical and Social Implications. In: ICTAI, 2023. [S.l.]: IEEE, 2023. p. 460–467. DOI: 10.1109/ictai59109.2023.00073. Available at: https://doi.org/10.1109/ictai59109.2023.00073. DOI: https://doi.org/10.1109/ICTAI59109.2023.00073
JOSE, D. Data Privacy and Security Concerns in AI-Integrated Educational Platforms. RMC, v. 5, n. 2, p. 87–91, 2024. DOI: 10.46632/rmc/5/2/19. Available at: https://doi.org/10.46632/rmc/5/2/19. DOI: https://doi.org/10.46632/rmc/5/2/19
KALYUGA, S. Rapid Dynamic Assessment for Learning. In: [S.l.]: Springer Netherlands, 2012. p. 43–60. DOI: 10.1007/978-94-007-4507-0_3. Available at: https://doi.org/10.1007/978-94-007-4507-0_3. DOI: https://doi.org/10.1007/978-94-007-4507-0_3
KHAN, M. I. Role of AI in Enhancing Accessibility for People with Disabilities. Deleted Journal, v. 3, n. 1, p. 281–291, 2024. DOI: 10.60087/jaigs.v3i1.120. Available at: https://doi.org/10.60087/jaigs.v3i1.120. DOI: https://doi.org/10.60087/jaigs.v3i1.120
KHAZANCHI, P.; KHAZANCHI, R. Pedagogical Practices in Teaching Students With Disabilities in Inclusive Education. In: [S.l.]: IGI Global, 2021. p. 66–86. DOI: 10.4018/978-1-7998-7630-4.CH004. Available at: https://doi.org/10.4018/978-1-7998-7630-4.CH004. DOI: https://doi.org/10.4018/978-1-7998-7630-4.ch004
KONADE, S. et al. Implementation of an Automated Answer Evaluation System. [S.l.]: IEEE, 2024. p. 457–462. DOI: 10.1109/ic2pct60090.2024.10486693. Available at: https://doi.org/10.1109/ic2pct60090.2024.10486693. DOI: https://doi.org/10.1109/IC2PCT60090.2024.10486693
KUMAR, A. et al. A Comprehensive Survey on AI in Learning Management System. Preprints, 2025. DOI: 10.20944/preprints202501.0697.v1. Available at: https://doi.org/10.20944/preprints202501.0697.v1. DOI: https://doi.org/10.20944/preprints202501.0697.v1
LEONG, W. Y.; LEONG, Y. Z.; LEONG, W. S. Artificial Intelligence in education. IET Conference Proceedings, v. 2024, n. 22, p. 183–184, 2025. DOI: 10.1049/icp.2024.4341. Available at: https://doi.org/10.1049/icp.2024.4341. DOI: https://doi.org/10.1049/icp.2024.4341
LIU, L. Research on Personalized Education Recommendation Algorithm Based on Artificial Intelligence. [S.l.]: IEEE, 2023. p. 531–535. DOI: 10.1109/icapc61546.2023.00104. Available at: https://doi.org/10.1109/icapc61546.2023.00104. DOI: https://doi.org/10.1109/ICAPC61546.2023.00104
MAROUF, M. et al. AI in Real-Time Student Performance Monitoring Using IoE. In: Advances in Computational Intelligence and Robotics Book Series. [S.l.]: IGI Global, 2024. p. 275–288. DOI: 10.4018/979-8-3693-7367-5.ch019. Available at: https://doi.org/10.4018/979-8-3693-7367-5.ch019. DOI: https://doi.org/10.4018/979-8-3693-7367-5.ch019
MESSAOUDI, A. Les défis de l’IA dans l’éducation: de la protection des données aux biais algorithmiques. Médiations & Médiatisations, n. 18, p. 148–160, 2024. DOI: 10.52358/mm.vi18.409. Available at: https://doi.org/10.52358/mm.vi18.409. DOI: https://doi.org/10.52358/mm.vi18.409
MORALES-CHAN, M. et al. Personalized Feedback in Massive Open Online Courses: Harnessing the Power of LangChain and OpenAI API. Electronics, 2024. DOI: 10.3390/electronics13101960. Available at: https://doi.org/10.3390/electronics13101960. DOI: https://doi.org/10.3390/electronics13101960
NODZYŃSKA-MOROŃ, M. Artificial intelligence in the teacher’s work. In: [S.l.]: [s.n.], 2024. p. 29–54. DOI: 10.24917/9788368020403.3. Available at: https://doi.org/10.24917/9788368020403.3. DOI: https://doi.org/10.24917/9788368020403.3
OTU, G. A. et al. Prediction accuracy analysis of machine learning classifiers on student course assessment methods. Fudma Journal of Sciences, v. 8, n. 6, p. 288–298, 2024. DOI: 10.33003/fjs-2024-0806-2927. Available at: https://doi.org/10.33003/fjs-2024-0806-2927. DOI: https://doi.org/10.33003/fjs-2024-0806-2927
PATIL, J. M.; GUPTA, S. R. Analytical Review on Various Aspects of Educational Data Mining and Learning Analytics. [S.l.]: IEEE, 2019. DOI: 10.1109/ICITAET47105.2019.9170143. Available at: https://doi.org/10.1109/ICITAET47105.2019.9170143. DOI: https://doi.org/10.1109/ICITAET47105.2019.9170143
REKHA, K. et al. Ai-Powered Personalized Learning System Design: Student Engagement And Performance Tracking System. [S.l.]: IEEE, 2024. p. 1125–1130. DOI: 10.1109/icacite60783.2024.10617155. Available at: https://doi.org/10.1109/icacite60783.2024.10617155. DOI: https://doi.org/10.1109/ICACITE60783.2024.10617155
SAYARI, K. Infrastructure, and Investment Needs for AI Implementation in Education. In: Advances in Educational Technologies and Instructional Design Book Series. [S.l.]: IGI Global, 2024. p. 141–162. DOI: 10.4018/979-8-3373-1017-6.ch005. Available at: https://doi.org/10.4018/979-8-3373-1017-6.ch005. DOI: https://doi.org/10.4018/979-8-3373-1017-6.ch005
SCALISE, K.; MALCOM, C.; KAYLOR, E. A tale of two worlds: Machine learning approaches at the intersection with educational measurement. [S.l.]: OECD, 2023. DOI: 10.1787/d01eb8a4-en. Available at: https://doi.org/10.1787/d01eb8a4-en. DOI: https://doi.org/10.1787/d01eb8a4-en
SCHÖNBERGER, M. et al. An AI-based lesson planning software to support competence-based learning. In: INTERNATIONAL CONFERENCE ON HIGHER EDUCATION ADVANCES (HEAd’22), 2022. [S.l.]: [s.n.], 2022. DOI: 10.4995/head22.2022.14599. Available at: https://doi.org/10.4995/head22.2022.14599. DOI: https://doi.org/10.4995/HEAd22.2022.14599
SEPTIANI, R. A.; RAMADANI, A. N. AI: Apakah Guru Masih Punya Peran di Masa Depan. Inspirasi Dunia, v. 4, n. 1, p. 263–272, 2025. DOI: 10.58192/insdun.v4i1.2947. Available at: https://doi.org/10.58192/insdun.v4i1.2947. DOI: https://doi.org/10.58192/insdun.v4i1.2947
SHIELDS, J. A. E. Classroom assessment. In: [S.l.]: Elsevier, 2023. p. 519–528. DOI: 10.1016/b978-0-12-818630-5.10064-8. Available at: https://doi.org/10.1016/b978-0-12-818630-5.10064-8. DOI: https://doi.org/10.1016/B978-0-12-818630-5.10064-8
SILVA, A. de O.; JANES, D. dos S. Editorial: Artificial Intelligence in Education – Navigating Ethical, Legal, and Technological Frontiers. Review of Artificial Intelligence in Education, v. 4, n. 00, e034, 2023. DOI: 10.37497/rev.artif.intell.educ.v4i00.34. Available at: https://doi.org/10.37497/rev.artif.intell.educ.v4i00.34. DOI: https://doi.org/10.37497/rev.artif.intell.educ.v4i00.34
SONG, X. et al. A Comprehensive Guide to Explainable AI: From Classical Models to LLMs, 2024. DOI: 10.31219/osf.io/wbk36. Available at: https://doi.org/10.31219/osf.io/wbk36. DOI: https://doi.org/10.31219/osf.io/wbk36
TANG, K. H. D. Implications of Artificial Intelligence for Teaching and Learning. Acta Pedagogia Asiana, v. 3, n. 2, p. 65–79, 2024. DOI: 10.53623/apga.v3i2.404. Available at: https://doi.org/10.53623/apga.v3i2.404. DOI: https://doi.org/10.53623/apga.v3i2.404
TAUFIKIN, M. S. I. et al. The Impact of AI on Teacher Roles and Pedagogy in the 21st Century Classroom. [S.l.]: IEEE, 2024. p. 1–5. DOI: 10.1109/ickecs61492.2024.10617236. Available at: https://doi.org/10.1109/ickecs61492.2024.10617236. DOI: https://doi.org/10.1109/ICKECS61492.2024.10617236
TRIVEDI, N. B. AI in Education – A Transformative Force. [S.l.]: IEEE, 2023. p. 1–4. DOI: 10.1109/idicaiei58380.2023.10406541. Available at: https://doi.org/10.1109/idicaiei58380.2023.10406541. DOI: https://doi.org/10.1109/IDICAIEI58380.2023.10406541
VIGENTINI, L. et al. Overcoming the MOOC Data Deluge with Learning Analytic Dashboards. In: [S.l.]: Springer, 2017. p. 171–198. DOI: 10.1007/978-3-319-52977-6_6. Available at: https://doi.org/10.1007/978-3-319-52977-6_6. DOI: https://doi.org/10.1007/978-3-319-52977-6_6
ZHANG, J.; KAMSIN, A. Personalized learning model based on machine learning algorithms. International Journal of Informatics and Communication Technology, v. 13, n. 3, p. 470–475, 2024. DOI: 10.11591/ijict.v13i3.pp470-475. Available at: https://doi.org/10.11591/ijict.v13i3.pp470-475. DOI: https://doi.org/10.11591/ijict.v13i3.pp470-475
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Copyright (c) 2026 Rômulo Ferreira dos Santos, Jaime de Melo Gama Da Silva, Matheus Henrique de Souza , Paulo Cesar Rodrigues Borges
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