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Dynamic Knowledge Modeling with Heterogeneous Activities for Adaptive Textbooks

Brusilovsky, PL and Thaker, KHUSHBOO and Huang, Yun and He, Daqing (2018) Dynamic Knowledge Modeling with Heterogeneous Activities for Adaptive Textbooks. In: 11th International Conference on Educational Data Mining, 15 July 2018 - 18 July 2018, Buffalo, USA.

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Abstract

Adaptive textbooks use student interaction data to infer the current state of student knowledge and recommend most relevant learning materials. A challenge of student mod- eling for adaptive textbooks is that conventional student models are constructed based on performance data (quiz or problem-solving), however, students' interactions with on- line textbooks may produce a large volume of student read- ing data but a limited amount of performance data. In this work, we propose a dynamic student knowledge modeling framework for online adaptive textbooks, which utilizes stu- dent reading data combined with few available quiz activi- ties to infer the students' current state of knowledge. The evaluation shows that proposed model learns more accurate students' knowledge state than Knowledge Tracing.

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Details

Item Type: Conference or Workshop Item (Paper)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Brusilovsky, PLpeterb@pitt.eduPETERB0000-0002-1902-1464
Thaker, KHUSHBOO
Huang, Yun
He, Daqing
Date: 15 July 2018
Date Type: Publication
Journal or Publication Title: http://educationaldatamining.org/files/conferences/EDM2018/papers/EDM2018_paper_199.pdf
Publisher: EDM Society
Place of Publication: USA
Page Range: 592 - 592
Event Title: 11th International Conference on Educational Data Mining
Event Dates: 15 July 2018 - 18 July 2018
Event Type: Conference
Schools and Programs: School of Computing and Information > Computer Science
Official URL: http://educationaldatamining.org/
Date Deposited: 01 Jul 2019 13:03
Last Modified: 01 Jul 2019 14:01
URI: http://d-scholarship.pitt.edu/id/eprint/37011

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