Personalization in distributed e-learning environments

Dolog, Peter; Henze, Nicola; Nejdl, Wolfgang; Sintek, Michael

doi:10.1145/1010432.1010460

Cited by 87 publications

(90 citation statements)

References 6 publications

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“…In e-learning domain, semantic web technology can guide and support developers, instructors, and learners to organize, personalize, and publish learning content and even to discover, generate, and compose learning content [5]. A conceptual content development and deployment architecture allows us to distinguish and locate the different applications and to discuss and assess the potential of the underlying technologies.…”

Section: Semantic Web Servicesmentioning

confidence: 99%

“…The knowledge space which gets created due to the interactions of instructors, developers and learners has the implicit relations between knowledge units and behavioral preferences of learners that can be made understood to the machines with the help of semantic web technology [5].…”

Section: Semantic Web Servicesmentioning

confidence: 99%

“…Ontologies applied to the Web are creating the Semantic Web. Ontologies provide the necessary armature around which knowledge bases should be built and set grounds for developing reusable Web-contents, Web-services and applications [5] [6] [7]. Ontologies facilitate knowledge sharing and reuse, i.e.…”

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confidence: 99%

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Personalization of e-Learning Services using Web Mining and Semantic Web

Jain¹,

Jain²,

Bhojak³

et al. 2012

IJMLC

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Abstract-The e-Learning has become matured learning paradigm with the advent of web based learning and content management tools, and shifted the focus of entire world from instructor centric learning paradigm to learner centric approach. Now for making the learning process more streamlined and standardized, the implementing agencies are emphasizing on moving towards service oriented architectural design approach to create, deploy and manage reusable e-Learning services, thus benefiting education sector. For providing the intelligence to evaluation system and other e-Learning services, various domains like data mining, web mining, semantic web etc. can be utilized intelligently. In this paper, we will describe an approach aiming to achieve personalization in e-Learning services using web mining and semantic web.Index Terms-Semantic web, web mining, service oriented architecture (SOA), learning object (LO), knowledge space, knowledge domain I. INTRODUCTIONE-Learning is a general term used to refer to a form of learning in which the instructor and learner are separated by space or time where the gap between the two is bridged through the use of online technologies. With web-based learning, it is possible for the learners to learn from anywhere, anytime, at their pace. Web-based learning brings unprecedented level of accessibility to courses in remote area, courses prohibited by budget constraints, courses updated to recently discovered knowledge, qualified instructors, and instruction at any time. Taking in view the difficulty in maintaining centralized online learning systems for the whole country and geo-graphically distributed administrative domains of educational bodies in the country, a service oriented architecture based learning system is the need of the hour. The strength of this approach is reusability and interoperability. Developing the learning platform based on this approach will involve assembling the required web services. The learning platform can be developed and run on different hardware and software platform as a middleware. Above all the major benefit of this approach is enhancements in quality of e-Learning services on the fly without affecting the underlying architecture of subscribers of services. II. PERSONALIZATION IN E-LEARNINGThe relationship between learner characteristics, tasks assigned and effectiveness is very crucial for defining the environment towards building a personalized online educational system. The target audience are be categorized into four groups viz., Individualist, Result-Oriented, Pragmatic and Avant-Gardes. Based on the main characteristics associated with these groups it is mentioned that the target groups differ in their demands for communication and tutor support as well as group activities and social contacts in an online course.Personalization in e-learning can be understood as education related technology which is capable of individualizing the interaction between system and learner, based on the personal needs and preferences of learner, and help them to shape...

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Section: Semantic Web Servicesmentioning

confidence: 99%

Section: Semantic Web Servicesmentioning

confidence: 99%

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Personalization of e-Learning Services using Web Mining and Semantic Web

Jain¹,

Jain²,

Bhojak³

et al. 2012

IJMLC

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show abstract

“…Each system maintains a user model for its own purposes of adaptation, and may interact with other systems to collect information about the user at a particular time and with specific purposes, in a peer-to-peer way. Similar decentralized solutions for user model interoperability are the ones of Lorenz (2005), Heckmann (2005), Dolog et al (2004). A different approach proposed in the literature is the 'centralized solution' (Kobsa 2007), where the aim is to gather as many data about a user as possible in a central shared space.…”

Section: Related Workmentioning

confidence: 99%

Integrating web service and semantic dialogue model for user models interoperability on the web

Cena

2010

J Intell Inf Syst

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Nowadays there is a great number of Web information systems that build a model of the user and adapt their services according to the needs and preferences maintained by the user model (UM). One of the most challenging issues of this scenario is the possibility to enable different systems to cooperate in order to exchange the available information about a user. Our aim is to create rich (and scalable) communication protocols and infrastructures to enable consumers and providers of UM data to interact. Our solution for dealing with such an issue is to exploit Web standards for interoperability (i.e. Semantic Web and Web Services) for implementing simple atomic communication, and a dialogue model for implementing enhanced communication capabilities. In particular, two systems can start a semantics-enhanced Dialogue Game as a form of negotiation to clarify the meaning of the requested concepts when a shared knowledge model does not exist, and to approximate the response when the exact one is not available. We propose a distributed semantic conversation framework based on the Sesame semantic environment for the exchange of user model knowledge on the Web. Systems have to expose their user model data as a Web Service, and to exploit a public dialogue knowledge base to start the dialogue. The main advantage of the approach is to allow systems to deal with difficult situations by starting an appropriate dialogue game instead of stopping the communication as in the traditional "all-or-nothing" Web Service approach. On the basis of a preliminary evaluation, the approach has shown an improvement of the adaptation results provided by the systems we tested.

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“…Through this continuing process new network phenomena occurs, such as distributed learning repositories [12], virtual learning communities and digital networks, such as the European School Net (www.eun.org/portal/index.htm) and the PROLEARN Virtual Competence Center (www.prolearn-online.com), offering services for education in general or to businesses. As there are many pedagogical innovations in technology enhanced learning and a growing number of technical infrastructures, the demand for technology enhanced learning services is growing, too.…”

Section: Technology Enhanced Learning In Europementioning

confidence: 99%

Pattern-Based Cross Media Social Network Analysis for Technology Enhanced Learning in Europe

Klamma

Spaniol

Cao

et al. 2006

Innovative Approaches for Learning and Knowledge Sharing

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Abstract. It is extremely challenging to get an overview of the current state-of-the-art in technology enhanced learning in Europe. Rapid technological and pedagogical innovations, constantly changing markets, a vivid number of small and medium enterprises, complex policy processes, ongoing political and societal debates on the pros and cons of technology enhanced leaning, combined with many languages and different cultures, make it almost impossible for people to be informed. We want to introduce the media base and the measure tools for pattern-based cross media social network analysis, created by the PROLEARN network of excellence in professional learning. The main goal of this endeavour is the reduction of complexity for actors in digital social networks by applying ideas from social software and already successful methods for complexity reduction, such as information visualization, social network analysis and pattern languages.

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Personalization in distributed e-learning environments

Cited by 87 publications

References 6 publications

Personalization of e-Learning Services using Web Mining and Semantic Web

Personalization of e-Learning Services using Web Mining and Semantic Web

Integrating web service and semantic dialogue model for user models interoperability on the web

Pattern-Based Cross Media Social Network Analysis for Technology Enhanced Learning in Europe

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