Mining teacher informal online learning networks: Community commitment in unstructured learning environments
Hanxiang Du, Gaoxia Zhu, Wanli XingAbstract
Background
Social media provides new opportunities for teachers to learn, communicate and develop professional relationships. It has been proved to be a valid and helpful resource for teachers' professional learning purposes.
Objectives
While previous studies pursued questions like how participants feel, how to support interaction and why participants remain committed, we asked a more fundamental question: what is the structure of a massive informal online professional learning network and what dynamics can we expect regarding participants' commitment?
Methods
This work presents an empirical study of massive informal online professional networks to investigate the dynamics of learning communities and participants' commitment over time. We employed social network analysis and data mining techniques on a longitudinal data set of more than 400,000 tweets published with the hashtag “#edchat.”
Results and Conclusions
We found that around 30% of participants remained committed to the informal learning community over time. Meanwhile, as more and more people committed to the online learning community, participants tended to form smaller communities where the internal connection was stronger.
Takeaways
In informal online learning environments, participants can form stable connections. The 30% threshold can be used to measure massive informal online learning networks in terms of commitment or persistence.