Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners' and Doctoral Consortium
23rd International Conference, AIED 2022, Durham, UK, July 27-31, 2022, Proceedings, Part II
(Sprache: Englisch)
This two-volume set LNAI 13355 and 13356 constitutes the refereed proceedings of the 23rd International Conference on Artificial Intelligence in Education, AIED 2022, held in Durham, UK, in July 2022.
The 40 full papers and 40 short papers...
The 40 full papers and 40 short papers...
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Klappentext zu „Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners' and Doctoral Consortium “
This two-volume set LNAI 13355 and 13356 constitutes the refereed proceedings of the 23rd International Conference on Artificial Intelligence in Education, AIED 2022, held in Durham, UK, in July 2022.The 40 full papers and 40 short papers presented together with 2 keynotes, 6 industry papers, 12 DC papers, 6 Workshop papers, 10 Practitioner papers, 97 Posters and Late-Breaking Results were carefully reviewed and selected from 243 submissions. The conference presents topics such as intelligent systems and the cognitive sciences for the improvement and advancement of education, the science and engineering of intelligent interactive learning systems. The theme for the AIED 2022 conference was "AI in Education: Bridging the gap between academia, business, and non-pro t in preparing future-proof generations towards ubiquitous AI."
Inhaltsverzeichnis zu „Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners' and Doctoral Consortium “
Interactive learning environments.- Computer-assisted instruction.- Collaborative learning.- e-learning.- Knowledge representation and reasoning.- Natural language processing.- Intelligent tutoring.- Semantic networks.- Probabilistic reasoning.- Machine learning.- Supervised learning.- Unsupervised learning.- Reinforcement learning.- Personalization. Data mining.
Bibliographische Angaben
- 2022, 1st ed. 2022, XXXVIII, 638 Seiten, 110 farbige Abbildungen, Maße: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Herausgegeben: Maria Mercedes Rodrigo, Noburu Matsuda, Alexandra I. Cristea, Vania Dimitrova
- Verlag: Springer, Berlin
- ISBN-10: 3031116461
- ISBN-13: 9783031116469
Sprache:
Englisch
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