Difference between revisions of "Adaptive Electronic Textbooks"
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| − | This work focused on social navigation as an alternative socially-driven mechanism to guide readers of online textbooks to the right content. Bringing analogy with recommender systems, traditional knowledge-based approach was more like content-based filtering, while social navigation is more like collaborative filtering. | + | This work focused on social navigation as an alternative socially-driven mechanism to guide readers of online textbooks to the right content. Bringing analogy with recommender systems, the traditional knowledge-based approach was more like content-based filtering, while social navigation is more like collaborative filtering. |
Learn more about: | Learn more about: | ||
| − | * [[ | + | * [[Knowledge Sea II]] |
| − | * [[ | + | * [[ReadingCircle]] |
* [[Reading Mirror]] | * [[Reading Mirror]] | ||
Revision as of 16:24, 24 May 2021
Adaptive Electronic Textbooks were a topic of interests of Home members for many years. While the majority of works on electronic books is concerned with just coping the old format in the new media, we believe that moving textbooks to electronic form brings a number of interesting opportunities that go well beyond the functionality of traditional printed textbooks. In our work we primarily explored the opportunities to make an electronic book adaptive (i.e., personalized), interactive, and social. This paper presents different ideas in the area of adaptive electronic textbooks explored by Home members.
Contents
Subtopics
This work focused on constructing the first adaptive textbooks. The personalization was based on advanced manual indexing of textbooks with concepts and relatively simple student modeling and personalization approaches.
Learn more about:
Sample papers:
- Schwarz, E., Brusilovsky, P., and Weber, G. (1996) World-wide intelligent textbooks. In: Proceedings of ED-TELECOM'96 - World Conference on Educational Telecommunications, Boston, MA, June 17-22, 1996, AACE, pp. 302-307.
- Brusilovsky, P., Schwarz, E., and Weber, G. (1997) Electronic textbooks on WWW: from static hypertext to interactivity and adaptivity. In: B. H. Khan (ed.) Web Based Instruction. Englewood Cliffs, New Jersey: Educational Technology Publications, pp. 255-261.
- Weber, G. and Brusilovsky, P. (2001) ELM-ART: An adaptive versatile system for Web-based instruction. International Journal of Artificial Intelligence in Education 12 (4), 351-384.
- Brusilovsky, P., Eklund, J., and Schwarz, E. (1998) Web-based education for all: A tool for developing adaptive courseware. In: H. Ashman and P. Thistewaite (eds.) Proceedings of Seventh International World Wide Web Conference, Brisbane, Australia, 14-18 April 1998, Elsevier Science B. V., pp. 291-300.
Automating the Construction of Adaptive Textbook
This work focused on automating several critical processes of adaptive book development that were done manually in the first generation research. This direction engages ontologies, advanced text processing and modeling, and machine learning.
Sample papers:
- Sosnovsky, S., Brusilovsky, P., and Hsiao, I.-H. (2012) Adaptation "in the Wild": Ontology-based Personalization of Open-Corpus Learning Material. In: Proceedings of 7th European Conference on Technology Enhanced Learning (EC-TEL 2012), Saarbrücken, Germany, pp. 425-431.
- Guerra, J., Sosnovsky, S., and Brusilovsky, P. (2013) When One Textbook is not Enough: Linking Multiple Textbooks Using Probabilistic Topic Models. In: D. Hernández-Leo, T. Ley, R. Klamma and A. Harrer (eds.) Proceedings of 8th European Conference on Technology Enhanced Learning (EC-TEL 2013), Paphos, Cypres, September 17-21, 2013, pp. 125-138.
- Labutov, I., Huang, Y., Brusilovsky, P., and He, D. (2017) Semi-Supervised Techniques for Mining Learning Outcomes and Prerequisites. In: Proceedings of Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, ACM, pp. 907-915.
- Thaker, K. M., Brusilovsky, P., and He, D. (2018) Concept Enhanced Content Representation for Linking Educational Resources. In: Proceedings of 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI), Santiago, Chile, December 3-6, 2018, IEEE, pp. 413-420.
- Chau, H., Labutov, I., Thaker, K., He, D., and Brusilovsky, P. (2020) Automatic Concept Extraction for Domain and Student Modeling in Adaptive Textbooks. International Journal of Artificial Intelligence in Education 30.
This work focused on social navigation as an alternative socially-driven mechanism to guide readers of online textbooks to the right content. Bringing analogy with recommender systems, the traditional knowledge-based approach was more like content-based filtering, while social navigation is more like collaborative filtering.
Learn more about:
Sample papers:
- Brusilovsky, P., Chavan, G., and Farzan, R. (2004) Social adaptive navigation support for open corpus electronic textbooks. In: P. De Bra and W. Nejdl (eds.) Proceedings of Third International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems (AH'2004), Eindhoven, the Netherlands, August 23-26, 2004, Springer-Verlag, pp. 24-33.
- Farzan, R. and Brusilovsky, P. (2005) Social navigation support through annotation-based group modeling. In: L. Ardissono, P. Brna and A. Mitrovic (eds.) Proceedings of 10th International User Modeling Conference, Berlin, July 24-29, 2005, Springer Verlag, pp. 463-472.
- Guerra, J., Parra, D., and Brusilovsky, P. (2013) Encouraging Online Student Reading with Social Visualization. In: Proceedings of 2nd Workshop on Intelligent Support for Learning in Groups at the 16th Annual Conference on Artificial Intelligence in Education, AIED 2013, Memphis, TN, USA, pp. 47-50.
- Barria-Pineda, J., Brusilovsky, P., and He, D. (2019) Reading Mirror: Social Navigation and Social Comparison for Electronic Textbooks. In: Proceedings of First Workshop on Intelligent Textbooks at 20th International Conference on Artificial Intelligence in Education (AIED 2019), Chicago, USA, June 25, 2019, CEUR, pp. 30-37.
Enhanced Structure Visualization for Electronic textbooks
Systems
ELM-ART - Adaptive and Interactive Electronic Textbook for LISP
About ELM-ART
InterBook - A framework to author and deliver adaptive electronic textbooks
About InterBook
Knowledge Sea
About Knowledge Sea
Systems
* Knowledge Sea * Knowledge Sea II
