Learning Object Recommendations for Teachers Based On Elicited ICT Competence Profiles
Recommender systems (RS) offer personalized services for facilitating the process of appropriate item selection. To perform this task, user profiling mechanisms should be implemented to automatically construct and update meaningful user profiles. These profiles can drive the RS in providing informed...
| Main Authors: | , |
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| Format: | Journal Article |
| Published: |
Institute of Electrical and Electronics Engineers
2016
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| Online Access: | http://hdl.handle.net/20.500.11937/12820 |
| _version_ | 1848748182822977536 |
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| author | Sergis, S. Sampson, Demetrios |
| author_facet | Sergis, S. Sampson, Demetrios |
| author_sort | Sergis, S. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Recommender systems (RS) offer personalized services for facilitating the process of appropriate item selection. To perform this task, user profiling mechanisms should be implemented to automatically construct and update meaningful user profiles. These profiles can drive the RS in providing informed recommendations suited to the unique characteristics of each user. In the context of technology enhanced learning (TeL) Recommender Systems, the majority of research focus directly on learners' profiling and ignore the potential benefits of profiling teachers' professional capacities too. As a result, limited previous works exist on effectively capturing and utilizing individual teachers' particular professional characteristics, such as their Digital Competences (commonly referred to as ICT Competences) and exploiting these in systems that support their teaching preparation and practice, for example in the selection of appropriate educational resources. This paper proposes a RS which targets to support teachers in selecting learning objects (LO) from existing LO repositories (LORs) in a unified manner, namely by (a) automatically constructing their ICT Competence Profiles based on their actions within these LORs and (b) exploiting these profiles for more efficient LO selection. Experiments with data from three real-life LORs are presented and evaluation results are discussed to demonstrate the benefits of the proposed system. |
| first_indexed | 2025-11-14T07:00:59Z |
| format | Journal Article |
| id | curtin-20.500.11937-12820 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:00:59Z |
| publishDate | 2016 |
| publisher | Institute of Electrical and Electronics Engineers |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-128202018-03-29T09:06:08Z Learning Object Recommendations for Teachers Based On Elicited ICT Competence Profiles Sergis, S. Sampson, Demetrios Recommender systems (RS) offer personalized services for facilitating the process of appropriate item selection. To perform this task, user profiling mechanisms should be implemented to automatically construct and update meaningful user profiles. These profiles can drive the RS in providing informed recommendations suited to the unique characteristics of each user. In the context of technology enhanced learning (TeL) Recommender Systems, the majority of research focus directly on learners' profiling and ignore the potential benefits of profiling teachers' professional capacities too. As a result, limited previous works exist on effectively capturing and utilizing individual teachers' particular professional characteristics, such as their Digital Competences (commonly referred to as ICT Competences) and exploiting these in systems that support their teaching preparation and practice, for example in the selection of appropriate educational resources. This paper proposes a RS which targets to support teachers in selecting learning objects (LO) from existing LO repositories (LORs) in a unified manner, namely by (a) automatically constructing their ICT Competence Profiles based on their actions within these LORs and (b) exploiting these profiles for more efficient LO selection. Experiments with data from three real-life LORs are presented and evaluation results are discussed to demonstrate the benefits of the proposed system. 2016 Journal Article http://hdl.handle.net/20.500.11937/12820 10.1109/TLT.2015.2434824 Institute of Electrical and Electronics Engineers unknown |
| spellingShingle | Sergis, S. Sampson, Demetrios Learning Object Recommendations for Teachers Based On Elicited ICT Competence Profiles |
| title | Learning Object Recommendations for Teachers Based On Elicited ICT Competence Profiles |
| title_full | Learning Object Recommendations for Teachers Based On Elicited ICT Competence Profiles |
| title_fullStr | Learning Object Recommendations for Teachers Based On Elicited ICT Competence Profiles |
| title_full_unstemmed | Learning Object Recommendations for Teachers Based On Elicited ICT Competence Profiles |
| title_short | Learning Object Recommendations for Teachers Based On Elicited ICT Competence Profiles |
| title_sort | learning object recommendations for teachers based on elicited ict competence profiles |
| url | http://hdl.handle.net/20.500.11937/12820 |