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Two Recommending Strategies to Enhance Online Presence in Personal Learning Environments

Identifieur interne : 000D27 ( Main/Exploration ); précédent : 000D26; suivant : 000D28

Two Recommending Strategies to Enhance Online Presence in Personal Learning Environments

Auteurs : Samuel Nowakowski [France] ; Ivana Ognjanovi [Serbie] ; Monique Grandbastien [France] ; Jelena Jovanovic [Serbie] ; Ramo Šendelj [Serbie]

Source :

RBID : Hal:hal-01102265

Abstract

Aiming to facilitate and support online learning practices, TEL researchers and practitioners have been increasingly focused on the design and use of Web-based Personal Learning Environments (PLE). A PLE is a set of services selected and cus-tomized by students. Among these services, resource (either digital or human) rec-ommendation is a crucial one. Accordingly, this chapter describes a novel approach to supporting PLEs through recommendation services. The proposed approach makes extensive use of ontologies to formally represent learning context that, among other components, includes students' presence in the online world, i.e., their online pres-ence. This approach has been implemented in and evaluated with the OP4L (Online Presence for Learning) prototype. In this chapter, we expose recommendation strate-gies devised for OP4L. One is already implemented in OP4L, it is based on the well-known Analytical Hierarchical Process (AHP) method. The other one which has been tested on data coming from the prototype is based on the active user's navigation stream and used a Kalman filter approach.

Url:
DOI: 10.1007/978-1-4939-0530-0_11


Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

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<orgName>University of Belgrade</orgName>
<desc>
<address>
<country key="FR"></country>
</address>
</desc>
</org>
</tutelle>
</tutelles>
</hal:affiliation>
<country>Serbie</country>
</affiliation>
</author>
<author>
<name sortKey="Sendelj, Ramo" sort="Sendelj, Ramo" uniqKey="Sendelj R" first="Ramo" last="Šendelj">Ramo Šendelj</name>
<affiliation wicri:level="1">
<hal:affiliation type="laboratory" xml:id="struct-212737" status="VALID">
<orgName>Faculty of Organizational Sciences</orgName>
<orgName type="acronym">FOS</orgName>
<desc>
<address>
<addrLine>154 Jove Ilića Str., 11000 Belgrade</addrLine>
<country key="RS"></country>
</address>
</desc>
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<relation active="#struct-308477" type="direct"></relation>
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<tutelle active="#struct-308477" type="direct">
<org type="institution" xml:id="struct-308477" status="INCOMING">
<orgName>University of Belgrade</orgName>
<desc>
<address>
<country key="FR"></country>
</address>
</desc>
</org>
</tutelle>
</tutelles>
</hal:affiliation>
<country>Serbie</country>
</affiliation>
</author>
</analytic>
<idno type="DOI">10.1007/978-1-4939-0530-0_11</idno>
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<front>
<div type="abstract" xml:lang="en">Aiming to facilitate and support online learning practices, TEL researchers and practitioners have been increasingly focused on the design and use of Web-based Personal Learning Environments (PLE). A PLE is a set of services selected and cus-tomized by students. Among these services, resource (either digital or human) rec-ommendation is a crucial one. Accordingly, this chapter describes a novel approach to supporting PLEs through recommendation services. The proposed approach makes extensive use of ontologies to formally represent learning context that, among other components, includes students' presence in the online world, i.e., their online pres-ence. This approach has been implemented in and evaluated with the OP4L (Online Presence for Learning) prototype. In this chapter, we expose recommendation strate-gies devised for OP4L. One is already implemented in OP4L, it is based on the well-known Analytical Hierarchical Process (AHP) method. The other one which has been tested on data coming from the prototype is based on the active user's navigation stream and used a Kalman filter approach.</div>
</front>
</TEI>
<affiliations>
<list>
<country>
<li>France</li>
<li>Serbie</li>
</country>
<region>
<li>Grand Est</li>
<li>Lorraine (région)</li>
</region>
<settlement>
<li>Metz</li>
<li>Nancy</li>
</settlement>
<orgName>
<li>Université de Lorraine</li>
</orgName>
</list>
<tree>
<country name="France">
<region name="Grand Est">
<name sortKey="Nowakowski, Samuel" sort="Nowakowski, Samuel" uniqKey="Nowakowski S" first="Samuel" last="Nowakowski">Samuel Nowakowski</name>
</region>
<name sortKey="Grandbastien, Monique" sort="Grandbastien, Monique" uniqKey="Grandbastien M" first="Monique" last="Grandbastien">Monique Grandbastien</name>
</country>
<country name="Serbie">
<noRegion>
<name sortKey="Ognjanovi, Ivana" sort="Ognjanovi, Ivana" uniqKey="Ognjanovi I" first="Ivana" last="Ognjanovi">Ivana Ognjanovi</name>
</noRegion>
<name sortKey="Jovanovic, Jelena" sort="Jovanovic, Jelena" uniqKey="Jovanovic J" first="Jelena" last="Jovanovic">Jelena Jovanovic</name>
<name sortKey="Sendelj, Ramo" sort="Sendelj, Ramo" uniqKey="Sendelj R" first="Ramo" last="Šendelj">Ramo Šendelj</name>
</country>
</tree>
</affiliations>
</record>

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