Adaptive Electronic Textbooks - Revision history

Peterb: /* Supporting Projects */

2021-05-24T16:50:19Z

‎Supporting Projects

Peterb at 16:49, 24 May 2021

2021-05-24T16:49:01Z

Peterb: /* Advanced Student Modeling and Knowlege-Driven Recommendation for Adaptive Textbooks */

2021-05-24T16:41:21Z

‎Advanced Student Modeling and Knowlege-Driven Recommendation for Adaptive Textbooks

Peterb: /* Subtopics */

2021-05-24T16:40:49Z

‎Subtopics

Peterb: /* Concept-based Textbooks with Adaptive Navigation support */

2021-05-24T16:26:16Z

‎Concept-based Textbooks with Adaptive Navigation support

Peterb: /* Social navigation for online textbooks - */

2021-05-24T16:26:01Z

‎Social navigation for online textbooks -

Peterb: /* Enhanced Structure Visualization for Electronic textbooks */

2021-05-24T16:24:58Z

‎Enhanced Structure Visualization for Electronic textbooks

Peterb: /* Social navigation for online textbooks - */

2021-05-24T16:24:25Z

‎Social navigation for online textbooks -

Peterb: /* Enhanced Structure Visualization for Electronic textbooks */

2021-05-24T16:24:01Z

‎Enhanced Structure Visualization for Electronic textbooks

Peterb: /* Subtopics */

2021-05-24T16:23:21Z

‎Subtopics

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 * [[Personalized Access to Open Corpus Educational Resources through Adaptive Navigation Support and Adaptive Visualization]]
-* [[]]
+* [[Open Corpus Personalized Learning]]
 = Subtopics =

← Older revision		Revision as of 16:49, 24 May 2021
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	Adaptive Electronic Textbooks were a topic of interests of [[our lab\| 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 [[PAWS Lab\| Home]] members.		Adaptive Electronic Textbooks were a topic of interests of [[our lab\| 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 [[PAWS Lab\| Home]] members.
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		+	= Supporting Projects =
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		+	* [[Personalized Access to Open Corpus Educational Resources through Adaptive Navigation Support and Adaptive Visualization]]
		+	* [[]]

	= Subtopics =		= Subtopics =

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 Sample papers:
-* Thaker, K., Huang, Y., Brusilovsky, P., and He, D. (2018) Dynamic Knowledge Modeling with Heterogeneous Activities for Adaptive Textbooks�. In:  Proceedings of the 11th International Conference on Educational Data Mining, Buffalo, USA, July 15-18, 2018, pp. 592-595.
+* Thaker, K., Huang, Y., Brusilovsky, P., and He, D. (2018) Dynamic Knowledge Modeling with Heterogeneous Activities for Adaptive Textbooks. In:  Proceedings of the 11th International Conference on Educational Data Mining, Buffalo, USA, July 15-18, 2018, pp. 592-595.
 * Thaker, K., Carvalho, P., and Koedinger, K. (2019) Comprehension Factor Analysis: Modeling student’s reading behaviour: Accounting for reading practice in predicting students’ learning in MOOCs. In:  Proceedings of 9th International Conference on Learning Analytics & Knowledge (LAK’19), Tempe, AZ, USA, March 4-8, 2019, pp. 111-115.
 * Thaker, K., Brusilovsky, P., and He, D. (2019) Student Modeling with Automatic Knowledge Component Extraction for Adaptive 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. 95-102.
 * Thaker, K., Zhang, L., He, D., and Brusilovsky, P. (2020) Recommending Remedial Readings Using Student’s Knowledge State. In:  Proceedings of 13th International Conference on Educational Data Mining, July 10-13, 2020, pp. 233-244.
 * Rahdari, B., Brusilovsky, P., Thaker, K., and Barria-Pineda, J. (2020) Using Knowledge Graph for Explainable Recommendation of External Content in Electronic Textbooks. In:  Proceedings of Second Workshop on Intelligent Textbooks at 21st International Conference on Artificial Intelligence in Education (AIED 2020), July 6, 2020, CEUR, pp. 50-61.
 == Enhanced Structure Visualization for Electronic textbooks ==

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 * 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 ==
 * [[Knowledge Sea]]
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 * [[ReadingCircle]]
 * [[ReadingMirror]]
 = Systems =

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 = Subtopics =
-== Concept-based Textbooks with Adaptive Navigation support ==
+== Concept-based Textbooks with Adaptive Navigation Support ==
 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.
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 * 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 ==

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 * 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.
-== Social navigation for online textbooks -==
+== Social Navigation for Online Textbooks ==
 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.

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 * [[Knowledge Sea]]
-* [[Knowledge Sea 2]]
+* [[Knowledge Sea II]]
 * [[BookTreeMap]]
 * [[ReadingCircle]]
 = Systems =

@@ Line 35: / Line 35: @@
 == Social navigation for online textbooks -==
-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:
-* [[KnowledgeSea]]
+* [[Knowledge Sea II]]
-* [[Reading Circle]]
+* [[ReadingCircle]]
 * [[Reading Mirror]]