Towards Automatic Competence Assignment of Learning Objects

Publikation: Beitrag in FachzeitschriftKonferenzaufsatz in FachzeitschriftForschungPeer-Review

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  • Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio)
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Details

OriginalspracheEnglisch
Seiten (von - bis)401-406
Seitenumfang6
FachzeitschriftLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Jahrgang7563 LNCS
PublikationsstatusVeröffentlicht - 2012
Veranstaltung7th European Conference on Technology Enhanced Learning, EC-TEL 2012 - Saarbrucken, Deutschland
Dauer: 18 Sept. 201221 Sept. 2012

Abstract

Competence-annotations assist learners to retrieve and better understand the level of skills required to comprehend learning objects. However, the process of annotating learning objects with competence levels is a very time consuming task; ideally, this task should be performed by experts on the subjects of the educational resources. Due to this, most educational resources available online do not enclose competence information. In this paper, we present a method to tackle the problem of automatically assigning an educational resource with competence topics. To solve this problem, we exploit information extracted from external repositories available on the Web, which lead us to a domain independent approach. Results show that automatically assigned competences are coherent and may be applied to automatically enhance learning objects metadata.

ASJC Scopus Sachgebiete

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Towards Automatic Competence Assignment of Learning Objects. / Kawase, Ricardo; Siehndel, Patrick; Nunes, Bernardo Pereira et al.
in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Jahrgang 7563 LNCS, 2012, S. 401-406.

Publikation: Beitrag in FachzeitschriftKonferenzaufsatz in FachzeitschriftForschungPeer-Review

Kawase, R, Siehndel, P, Nunes, BP, Fisichella, M & Nejdl, W 2012, 'Towards Automatic Competence Assignment of Learning Objects', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Jg. 7563 LNCS, S. 401-406. https://doi.org/10.1007/978-3-642-33263-0_34
Kawase, R., Siehndel, P., Nunes, B. P., Fisichella, M., & Nejdl, W. (2012). Towards Automatic Competence Assignment of Learning Objects. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7563 LNCS, 401-406. https://doi.org/10.1007/978-3-642-33263-0_34
Kawase R, Siehndel P, Nunes BP, Fisichella M, Nejdl W. Towards Automatic Competence Assignment of Learning Objects. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2012;7563 LNCS:401-406. doi: 10.1007/978-3-642-33263-0_34
Kawase, Ricardo ; Siehndel, Patrick ; Nunes, Bernardo Pereira et al. / Towards Automatic Competence Assignment of Learning Objects. in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2012 ; Jahrgang 7563 LNCS. S. 401-406.
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abstract = "Competence-annotations assist learners to retrieve and better understand the level of skills required to comprehend learning objects. However, the process of annotating learning objects with competence levels is a very time consuming task; ideally, this task should be performed by experts on the subjects of the educational resources. Due to this, most educational resources available online do not enclose competence information. In this paper, we present a method to tackle the problem of automatically assigning an educational resource with competence topics. To solve this problem, we exploit information extracted from external repositories available on the Web, which lead us to a domain independent approach. Results show that automatically assigned competences are coherent and may be applied to automatically enhance learning objects metadata.",
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note = "Funding information: Acknowledgement. This research has been co-funded by the European Commission within the eContentplus targeted project OpenScout, grant ECP 2008 EDU 428016 (cf. http://www.openscout.net) and by CAPES (Process no 9404-11-2).; 7th European Conference on Technology Enhanced Learning, EC-TEL 2012 ; Conference date: 18-09-2012 Through 21-09-2012",
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Download

TY - JOUR

T1 - Towards Automatic Competence Assignment of Learning Objects

AU - Kawase, Ricardo

AU - Siehndel, Patrick

AU - Nunes, Bernardo Pereira

AU - Fisichella, Marco

AU - Nejdl, Wolfgang

N1 - Funding information: Acknowledgement. This research has been co-funded by the European Commission within the eContentplus targeted project OpenScout, grant ECP 2008 EDU 428016 (cf. http://www.openscout.net) and by CAPES (Process no 9404-11-2).

PY - 2012

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N2 - Competence-annotations assist learners to retrieve and better understand the level of skills required to comprehend learning objects. However, the process of annotating learning objects with competence levels is a very time consuming task; ideally, this task should be performed by experts on the subjects of the educational resources. Due to this, most educational resources available online do not enclose competence information. In this paper, we present a method to tackle the problem of automatically assigning an educational resource with competence topics. To solve this problem, we exploit information extracted from external repositories available on the Web, which lead us to a domain independent approach. Results show that automatically assigned competences are coherent and may be applied to automatically enhance learning objects metadata.

AB - Competence-annotations assist learners to retrieve and better understand the level of skills required to comprehend learning objects. However, the process of annotating learning objects with competence levels is a very time consuming task; ideally, this task should be performed by experts on the subjects of the educational resources. Due to this, most educational resources available online do not enclose competence information. In this paper, we present a method to tackle the problem of automatically assigning an educational resource with competence topics. To solve this problem, we exploit information extracted from external repositories available on the Web, which lead us to a domain independent approach. Results show that automatically assigned competences are coherent and may be applied to automatically enhance learning objects metadata.

KW - Automatic Competence Classification

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KW - E-Learning

KW - Metadata Generation

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VL - 7563 LNCS

SP - 401

EP - 406

JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SN - 0302-9743

T2 - 7th European Conference on Technology Enhanced Learning, EC-TEL 2012

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ER -

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