User Modeling in a Distributed E-Learning Architecture

Brusilovsky, Peter; Sosnovsky, Sergey; Shcherbinina, Olena

doi:10.1007/11527886_50

Cited by 61 publications

(42 citation statements)

References 5 publications

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“…As a central system we used QuizJET -the system serving parameterized exercises for Java programming language [7]. Both OOPS and QuizJET have been integrated with the CUMULATE user modeling server [8]. As an open-corpus collection of instructional material we used the electronic version of an introductory Java textbook.…”

Section: The Ontology-based Open-corpus Personalization Servicementioning

confidence: 99%

Adaptation “in the Wild”: Ontology-Based Personalization of Open-Corpus Learning Material

Sosnovsky

Hsiao

Brusilovsky

2012

Lecture Notes in Computer Science

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Abstract.Teacher and students can use WWW as a limitless source of learning material for nearly any subject. Yet, such abundance of content comes with the problem of finding the right piece at the right time. Conventional adaptive educational systems cannot support personalized access to open-corpus learning material as they rely on manually constructed content models. This paper presents an approach to this problem that does not require intervention from a human expert. The approach has been implemented in an adaptive system that recommends students supplementary reading material and adaptively annotates it. The results of the evaluation experiment have demonstrated several significant effects of using the system on students' learning.

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Section: The Ontology-based Open-corpus Personalization Servicementioning

confidence: 99%

Adaptation “in the Wild”: Ontology-Based Personalization of Open-Corpus Learning Material

Sosnovsky

Hsiao

Brusilovsky

2012

Lecture Notes in Computer Science

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“…In early systems, the completely centralized approach was the most common implementation in the form of the user model server [11] [23]. However, its inability to support self-contained systems led to variations on these designs that were more flexible [12] [20] [17].…”

Section: Related Workmentioning

confidence: 99%

“…These languages provide more explicit semantics and can be used for additional benefits such as reasoning. However, the most common format to represent and extract user information from existing applications is XML [11] [16] [25]. For the transfer protocol, the most popular method is certainly the common adoption of web service technologies such as REST and SOAP [12] [8] [14].…”

Section: Related Workmentioning

confidence: 99%

Evaluation of a domain-aware approach to user model interoperability

Walsh

O’Connor

Wade

2012

Proceedings of the 23rd ACM Conference on Hypertext and Social Media

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It is becoming increasingly important to facilitate the integrated management of user information. Exchanging user information across heterogeneous systems has many benefits, particularly in enhancing the quality and quantity of user information available for personalization. One common approach to user model interoperability is the use of mapping tools to manually build rich executable mappings between user models. A key problem with existing approaches is that the mapping tools are often too generic for these specialized tasks and do not provide any support to an administrator mapping in a specific domain such as user models. This paper presents a novel approach to user model interoperability which lowers the complexity and provides support to administrators in completing user model mappings. The domain-aware approach to user model interoperability incorporates interchangeable domain knowledge directly into the integration tools. This approach was implemented in a system called FUMES which is a mapping creation and execution environment that includes two domain-aware mechanisms; a canonical user model and user model mapping types. FUMES was deployed in an integration of existing user models and the domain-aware approach was then evaluated in a user study. The evaluation consisted of a direct comparison with a generic approach to user model interoperability which was applied using the commercial mapping tool, Altova Mapforce. The results of this evaluation demonstrate improvements in mapping accuracy and usability when using the domain-aware approach compared to the generic mapping approach.

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“…Today, most of such researches take advantage of existing network system by performing distributed parallel computing, which achieves similar results as high-performance computing. Because of the widespread availability of network, there are many applications of distributed parallel computing in a variety of end-use situations [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Intelligent Cloud Learning Model for Online Overseas Chinese Education

Chen¹,

Huang

Shi³

2015

Int. J. Emerg. Technol. Learn.

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Abstract-With the development of Chinese economy, oversea Chinese education has been paid more and more attention. However, the overseas Chinese education resource is relatively lack because of historical reasons, which hindered further development . How to better share the Chinese education resources and provide intelligent personalized information service for overseas student is a key problem to be solved. In recent years, the rise of cloud computing provides us an opportunity to realize intelligent learning mode. Cloud computing offers some advantages by allowing users to use infrastructure, platforms and software . In this paper we proposed an intelligent cloud learning model based on cloud computing. The learning model can utilize network resources sufficiently to implement resource sharing according to the personal needs of students, and provide a good practicability for online overseas Chinese education.

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User Modeling in a Distributed E-Learning Architecture

Cited by 61 publications

References 5 publications

Adaptation “in the Wild”: Ontology-Based Personalization of Open-Corpus Learning Material

Adaptation “in the Wild”: Ontology-Based Personalization of Open-Corpus Learning Material

Evaluation of a domain-aware approach to user model interoperability

Intelligent Cloud Learning Model for Online Overseas Chinese Education

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