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Adaptable educational tools created using Machine Learning (or Artificial Intelligence more broadly) can adapt their behavior in real-time according to the needs of individuals or to support collaborative learning. This is important to improve access to educational opportunities, help personalize the teaching process, and to step in when teachers have limited time. Key considerations for creating these tools include adapting to local technological and cultural needs, addressing barriers such as access toelectricity and internet, and taking into account students’ computing skills, language, and culture.
Background Readings[edit | edit source]
- Advances In Intelligent Tutoring Systems (2010): the textbook on creating adaptable learning agents, with chapters dedicated to different approaches and theories. Available here.
- Another 25 Years of AIED? Challenges and Opportunities for Intelligent Educational Technologies Of The Future (2016): a thorough analysis of the promise of Artificial Intelligence in education and the challenges that it entails. Available here.
Community[edit | edit source]
Libraries and Tools[edit | edit source]
Data[edit | edit source]
Future Directions[edit | edit source]
References[edit | edit source]
- Nkambou, Roger; Bourdeau, Jacqueline; Mizoguchi, Riichiro, eds. (2010). "Advances in Intelligent Tutoring Systems". Studies in Computational Intelligence. doi:10.1007/978-3-642-14363-2. ISSN 1860-949X.
- Pinkwart, Niels (2016-06). "Another 25 Years of AIED? Challenges and Opportunities for Intelligent Educational Technologies of the Future". International Journal of Artificial Intelligence in Education. 26 (2): 771–783. doi:10.1007/s40593-016-0099-7. ISSN 1560-4292. Check date values in: