Details
| Original language | English |
|---|---|
| Title of host publication | CSEDU 2020 - Proceedings of the 12th International Conference on Computer Supported Education |
| Editors | H. Chad Lane, Susan Zvacek, James Uhomoibhi |
| Pages | 344-351 |
| Number of pages | 8 |
| ISBN (electronic) | 9789897584176 |
| Publication status | Published - 2020 |
| Externally published | Yes |
| Event | 12th International Conference on Computer Supported Education, CSEDU 2020 - Virtual, Online Duration: 2 May 2020 → 4 May 2020 |
Publication series
| Name | CSEDU 2020 - Proceedings of the 12th International Conference on Computer Supported Education |
|---|---|
| Volume | 2 |
Abstract
We describe XEL-Group Learning, a socio-technical framework for socially oriented e-learning. The aim of the presented framework is to address the lack of holistic pedagogical solutions that take into account motivational theories, socio–technical factors, and cultural elements in social learning networks. The presented framework provides initiatives for collaboration by providing a dynamic psycho-pedagogical recommendation mechanism with validation properties. In this paper, we begin by highlighting the socio-technical concept associated with socially-oriented e-learning. Next, we describe XEL-GL’s main mechanisms such as group formation and the semantic matching framework. Moreover, through semantic similarity measurements, we show how cultural elements, such as the learning subject, can enhance the quality of recommendations by allowing for more accurate predictions of friends networks.
Keywords
- E-Learning, Recommendation Systems, Social Learning, Social Media Networks, Socio-technical
ASJC Scopus subject areas
- Computer Science(all)
- Information Systems
- Computer Science(all)
- Computer Science Applications
- Social Sciences(all)
- Education
Cite this
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- BibTeX
- RIS
CSEDU 2020 - Proceedings of the 12th International Conference on Computer Supported Education. ed. / H. Chad Lane; Susan Zvacek; James Uhomoibhi. 2020. p. 344-351 (CSEDU 2020 - Proceedings of the 12th International Conference on Computer Supported Education; Vol. 2).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - XEL group learning – A socio-technical framework for self-regulated learning
AU - Eid, Shereif
AU - Kismihók, Gábor
PY - 2020
Y1 - 2020
N2 - We describe XEL-Group Learning, a socio-technical framework for socially oriented e-learning. The aim of the presented framework is to address the lack of holistic pedagogical solutions that take into account motivational theories, socio–technical factors, and cultural elements in social learning networks. The presented framework provides initiatives for collaboration by providing a dynamic psycho-pedagogical recommendation mechanism with validation properties. In this paper, we begin by highlighting the socio-technical concept associated with socially-oriented e-learning. Next, we describe XEL-GL’s main mechanisms such as group formation and the semantic matching framework. Moreover, through semantic similarity measurements, we show how cultural elements, such as the learning subject, can enhance the quality of recommendations by allowing for more accurate predictions of friends networks.
AB - We describe XEL-Group Learning, a socio-technical framework for socially oriented e-learning. The aim of the presented framework is to address the lack of holistic pedagogical solutions that take into account motivational theories, socio–technical factors, and cultural elements in social learning networks. The presented framework provides initiatives for collaboration by providing a dynamic psycho-pedagogical recommendation mechanism with validation properties. In this paper, we begin by highlighting the socio-technical concept associated with socially-oriented e-learning. Next, we describe XEL-GL’s main mechanisms such as group formation and the semantic matching framework. Moreover, through semantic similarity measurements, we show how cultural elements, such as the learning subject, can enhance the quality of recommendations by allowing for more accurate predictions of friends networks.
KW - E-Learning
KW - Recommendation Systems
KW - Social Learning
KW - Social Media Networks
KW - Socio-technical
UR - http://www.scopus.com/inward/record.url?scp=85091744569&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85091744569
T3 - CSEDU 2020 - Proceedings of the 12th International Conference on Computer Supported Education
SP - 344
EP - 351
BT - CSEDU 2020 - Proceedings of the 12th International Conference on Computer Supported Education
A2 - Lane, H. Chad
A2 - Zvacek, Susan
A2 - Uhomoibhi, James
T2 - 12th International Conference on Computer Supported Education, CSEDU 2020
Y2 - 2 May 2020 through 4 May 2020
ER -