| Referências: |
Doroudi, S. (2022). The intertwined histories of artificial intelligence and education.
International Journal of Artificial Intelligence in Education, 1-44.
https://doi.org/10.1007/s40593-022-00313-2
• Cao, L., & Dede, C. (2023). Navigating A World of Generative AI: Suggestions for
Educators. The Next Level Lab at Harvard Graduate School of Education. President and
Fellows of Harvard College: Cambridge, MA
https://nextlevellab.gse.harvard.edu/files/2023/08/Cao_Dede_final_8.4.23.pdf
• Miao, F. & Holmes, W. (2023) Guidance for generative AI in education and research.
UNESCO Publishing. https://unesdoc.unesco.org/ark:/48223/pf0000386693
• Baker, R. S. (2021). Artificial intelligence in education: Bringing it all together. OECD
Digital Education Outlook 2021 Pushing the Frontiers with Artificial Intelligence,
Blockchain and Robots. https://doi.org/10.1787/f54ea644-en
• Isotani, S., Bittencourt, I. I., Challco, G. C., Dermeval, D., & Mello, R. F. (2023, June).
AIED Unplugged: Leapfrogging the Digital Divide to Reach the Underserved. In
International Conference on Artificial Intelligence in Education (pp. 772-779). Cham:
Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-36336-8_118
• Aleven, V., McLaughlin, E. A., Glenn, R. A., & Koedinger, K. R. (2017). Chapter 24: Instruction based on adaptive learning technologies. In R. E. Mayer & P. Alexander (Eds.),
Handbook of research on learning and instruction (2nd ed., pp. 522-560). New York:
Routledge. https://doi.org/10.4324/9781315736419
• Chapter 3: Personalisation of learning: Towards hybrid human-AI learning technologies.
OECD Digital Education Outlook 2021 : Pushing the Frontiers with Artificial Intelligence,
Blockchain and Robots. https://doi.org/10.1787/2cc25e37-en
• Li, S., & Gu, X. (2023). A Risk Framework for Human-centered Artificial Intelligence in
Education: Based on Literature Review and Delphi–AHP Method. Educational Technology
& Society, 26(1), 187-202. https://doi.org/10.30191/ETS.202301_26(1).0014
• Baker, R. S., & Hawn, A. (2022). Algorithmic bias in education. International Journal of
Artificial Intelligence in Education, 1052–1092. https://doi.org/10.1007/s40593-021-00285-
9
• Pammer-Schindler, V., & Rosé, C. (2022). Data-related ethics issues in technologies for
informal professional learning. International Journal of Artificial Intelligence in Education,
609–635. https://link.springer.com/article/10.1007/s40593-021-00259-x
• VanLehn, K. (2006). The behavior of tutoring systems. International Journal of Artificial
Intelligence in Education, 16(3), 227-265
https://learnlab.org/opportunities/summer/readings/06IJAIED.pdf
• Luckin, R; Holmes, W; (2016) Intelligence Unleashed: An argument for AI in Education.
UCL Knowledge Lab: London, Uk. https://discovery.ucl.ac.uk/id/eprint/1475756/
• Nye, B. D. (2015). Intelligent tutoring systems by and for the developing world: A review
of trends and approaches for educational technology in a global context. International
Journal of Artificial Intelligence in Education, 25(2), 177-203.
https://doi.org/10.1007/s40593-014-0028-6
• Romero, C., Ventura, S., & García, E. (2008). Data mining in course management systems:
Moodle case study and tutorial. Computers & Education, 51(1), 368-384.
https://doi.org/10.1016/j.compedu.2007.05.016
• Bittencourt, I. I., Chalco, G., Santos, J., Fernandes, S., Silva, J., Batista, N., ... & Isotani, S.
(2023). Positive Artificial Intelligence in Education (P-AIED): A Roadmap. International
Journal of Artificial Intelligence in Education, 1-61.
https://link.springer.com/article/10.1007/s40593-023-00357-y
• Ifenthaler, D. (2021). Learning analytics for school and system management. OECD Digital
Education Outlook 2021 Pushing the Frontiers with Artificial Intelligence, Blockchain and
Robots: Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots, 161.
https://doi.org/10.1787/d535b828-en
• Unicef. (2018). Early warning systems for students at risk of dropping out. Unicef Series on
Education Participation and Dropout Prevention, 2. Chapter 1: Frontiers of smart education technology: Opportunities and challenges. OECD
Digital Education Outlook 2021 : Pushing the Frontiers with Artificial Intelligence,
Blockchain and Robots
• Miao, F., Holmes, W., Huang, R., & Zhang, H. (2021). AI and education: A guidance for
policymakers. UNESCO Publishing.
• Koedinger, K. R., Booth, J. L., & Klahr, D. (2013). Instructional complexity and the
science to constrain it. Science, 342(6161), 935-937.
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