Abstract
Contemporary educational research has increasingly pointed to socioemotional dimensions of learning as important in promoting academic progress and sociocognitive developments. Epistemic Network Analysis, a methodology for producing quantitative ethnographies based on complex learning environments, has only begun to examine socioemotional facets of learning in classrooms. The aim of this research is to investigate what and how Epistemic Network Analysis can contribute to qualitative, socioemotionally-focused ethnographies of classroom learning communities. To do this, we employed Epistemic Network Analysis to analyze data collected during a semester of studies, in parallel to a stage developmental analysis of the same community using qualitative methods. The results of this study specifically show the importance of prior experience and how this interacts with participants' connectedness to the community, as well as how group dynamics are a vital aspect of community discourse and that the socioemotional dimensions that people attach to it may be the determinants of stage advancement. More generally, this study shows how Epistemic Network Analysis can be used to better understand complex socioemotional phenomena in learning communities by combining it with deep, qualitative ethnographies.
Original language | English |
---|---|
Article number | 103943 |
Journal | Computers and Education |
Volume | 156 |
DOIs | |
State | Published - Oct 2020 |
Bibliographical note
Funding Information:This research was supported by the I-CORE Program of the Planning and Budgeting Committee and The Israel Science Foundation grant 1716/12. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sk?odowska-Curie grant agreement No 796045. We would like to thank Michal Dvir and Chen Ya'ari for their help with the data analysis.
Funding Information:
This research was supported by the I-CORE Program of the Planning and Budgeting Committee and The Israel Science Foundation grant 1716/12. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 796045 . We would like to thank Michal Dvir and Chen Ya'ari for their help with the data analysis.
Publisher Copyright:
© 2020
Keywords
- Cooperative/collaborative learning
- Data science applications in education
- Learning communities
- Pedagogical issues
- Post-secondary education
ASJC Scopus subject areas
- General Computer Science
- Education