Details
Original language | English |
---|---|
Pages (from-to) | 401-406 |
Number of pages | 6 |
Journal | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Volume | 7563 LNCS |
Publication status | Published - 2012 |
Event | 7th European Conference on Technology Enhanced Learning, EC-TEL 2012 - Saarbrucken, Germany Duration: 18 Sept 2012 → 21 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.
Keywords
- Automatic Competence Classification, Competences, E-Learning, Metadata Generation
ASJC Scopus subject areas
- Mathematics(all)
- Theoretical Computer Science
- Computer Science(all)
- General Computer Science
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In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 7563 LNCS, 2012, p. 401-406.
Research output: Contribution to journal › Conference article › Research › peer review
}
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
Y1 - 2012
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
KW - Competences
KW - E-Learning
KW - Metadata Generation
UR - http://www.scopus.com/inward/record.url?scp=84885237010&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-33263-0_34
DO - 10.1007/978-3-642-33263-0_34
M3 - Conference article
AN - SCOPUS:84885237010
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
Y2 - 18 September 2012 through 21 September 2012
ER -