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Ontology-Based Open-Corpus Personalization for E-Learning

Sosnovsky, Sergey (2011) Ontology-Based Open-Corpus Personalization for E-Learning. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Conventional closed-corpus adaptive information systems control limited sets of documents in predefined domains and cannot provide access to the external content. Such restrictions contradict the requirements of today, when most of the information systems are implemented in the open document space of the World Wide Web and are expected to operate on the open-corpus content. In order to provide personalized access to open-corpus documents, an adaptive system should be able to maintain modeling of new documents in terms of domain knowledge automatically and dynamically. This dissertation explores the problem of open-corpus personalization and semantic modeling of open-corpus content in the context of e-Learning.
Information on the World Wide Web is not without structure. Many collections of online instructional material (tutorials, electronic books, digital libraries, etc.) have been provided with implicit knowledge models encoded in form of tables of content, indexes, headers of chapters, links between pages, and different styles of text fragments. The main dissertation approach tries to leverage this layer of hidden semantics by extracting and representing it as coarse-grained models of content collections. A central domain ontology is used to maintain overlay modeling of students’ knowledge and serves as a reference point for multiple collections of external instructional material. In order to establish the link between the ontology and the open-corpus content models a special ontology mapping algorithm has been developed.
The proposed approach has been applied in the Ontology-based Open-corpus Personalization Service that recommends and adaptively annotates online reading material. The domain of Java programming has been chosen for the proof-of-concept implementation. A controlled experiment has been organized to evaluate the developed adaptive system and the proposed approach overall. The results of the evaluation have demonstrated several significant learning effects of the implemented open-corpus personalization. The analysis of log-based data has also shown that the open-corpus version of the system is capable of providing personalization of similar quality to the close-corpus one. Such results indicate that the proposed approach successfully supports open-corpus personalization for e-Learning. Further research is required to verify if the approach remains effective in other subject domains and with other types of instructional content.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairBrusilovsky, Peterpeterb@pitt.eduPETERB
Committee MemberDicheva,
Committee MemberHe, Daqingdah44@pitt.eduDAH44
Committee MemberLane, H.
Committee MemberSpring, Michaelspring@pitt.eduSPRING
Date: 22 December 2011
Date Type: Publication
Defense Date: 30 November 2011
Approval Date: 22 December 2011
Submission Date: 21 December 2011
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 304
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Open-corpus personalization, Information Extraction, e-Learning, Ontology Mapping, Ontologies, Student Modeling, Adaptive Systems, Adaptation, Adaptive Hypermedia
Related URLs:
Date Deposited: 22 Dec 2011 13:35
Last Modified: 15 Nov 2016 13:55


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