23 SES 04 C, Politics of Knowledge
Social Media & Educational Policy Processes
Social media offers multiple parties the opportunity to start bottom-up initiatives and acquire social capital (Rehm, Cornelissen, Notten, & Daly, 2017). Moreover, influenced by developments in society, such as the observed increased influence of information technology and individualization, there has been a shift from government to governance in the past few decades (Ball & Junemann, 2012). In particular, the network governance approach focuses on the informal, horizontal nature and mutual dependency between the various actors in the development and implementation of policy (Klijn & Koppenjan, 2012). Within theses policy processes, the government assumes a role in which it does not provide direct steering, but mainly initiates, coordinates and facilitates discussions about policy processes (Ball & Junemann, 2012). In this context, the Dutch government adopted a network approach and involved an extensive network of stakeholders in a large-scale educational policy process on the topic of “onderwsijs2032”, which translates into "Education2032". This initiative was intended to organize and initiate a broad social dialogue about the future of Dutch education (www.onderwijs2032.nl). The national debate took place under the direction of the so-called Platform2032 through a mix of meetings in the country, letters sent in, regular media, and social media, such as Twitter.
In order to analyze underlying communication processes within these types of context, (educational) scientists have increasingly acknowledged that the concept of social capital can contribute to our understanding of how informal networks develop and evolve over time (Rehm & Notten, 2016). Yet, while previous research has already touched upon these topics and settings, these studies can be criticized on the basis of two main issues. First, while social capital in SNS has already been identified and analyzed in a number of SNS settings, considerable uncertainty remains about how social capital might shape (educational) policy processes. Second, teachers and educational professionals have largely been neglected from the analysis of policy processes and social capital formation within SNS. Consequently, this study addresses these shortcomings by investigating whether a Twitter conversation has the potential to contribute to and potentially have an impact on an (educational) policy process. It furthermore takes a deeper look at this process in order to investigate whether and to what extend participation in SNS contributes to social capital formation.
Incorporating all social capital dimensions (Nahapiet & Ghoshal, 1998) and building upon on the aforementioned considerations, we formulate our three main research questions as:
- Does participation in Twitter conversation contribute to individuals’ formation of structural social capital among teachers and other educational professionals?
- To what extend can we observe cognitive social capital in the context of a discussion about educational policy on Twitter?
- What are individuals’ motivations and strategies to contribute to a (educational) policy discussion on Twitter, adding to their relational capital?
Method We employed a mixed-method approach to analyze the #onderwijs2032 Twitter discussion. First, we used social network analyses (Rehm, et al., 2017; Supovitz, Daly, & del Fresno, 2015) to identify underlying activity patterns (structural dimension). Second, we employed topic modeling (Alsumait, Wang, Domeniconi, & Barbará, 2010), to investigate what teachers and educational professionals are talking about on Twitter, as well as whether individuals’ network position influence what is shared and how it spreads throughout the network (cognitive dimension). Finally, semi-structured interviews (Nahapiet & Ghoshal, 1998)were conducted, in order to investigate individuals’ underlying motivations and strategies for participating in a discussion about educational policy on Twitter (relational dimension). Data In the context of this study, we will focus on the hashtag #onderwijs2032, which was specifically started for the “Education2032” initiative. Using the software tool NodeXL, the data was collected over a period of four months, from the 1st of September 2015 through to the 20th of December, 2015. The collected data was then imported into the software packages R and Pajek to conduct all relevant analyses.
Findings & Implications Based on our findings, we argue that Twitter does contribute to all three dimensions of (individuals’) social capital. Employing a mixed-methods approach provided valuable insights on the underlying network structures, the types of information being shared and the motivations of and strategies for individuals’ contributions to the #onderwijs2032 discussion. Assessing these types of processes and structures not only enables us to be better understand how communication and discussions on (educational) policy processes develop and evolve within social media spaces, such Twitter. They also allow us to potentially profile SNS conversations and better understand what type of discussions draw what type of participants and how the dynamics might be influenced by this.
Alsumait, L., Wang, P., Domeniconi, C., & Barbará, D. (2010). Embedding Semantics in LDA Topic Models. In M. W. Berry & J. Kogan (Hrsg.), Text Mining (S. 183–204). John Wiley & Sons, Ltd. https://doi.org/10.1002/9780470689646.ch10 Ball, S. J., & Junemann, C. (2012). Networks, new governance and education. Policy Press. Klijn, E.-H., & Koppenjan, J. (2012). Governance network theory: past, present and future. Policy & Politics, 40(4), 587–606. Nahapiet, J., & Ghoshal, S. (1998). Social Capital, Intellectual Capital, and the Organizational Advantage. The Academy of Management Review, 23(2), 242–266. https://doi.org/10.2307/259373 Rehm, M., Cornelissen, F., Notten, A., & Daly, A. (2017). To Go Beyond ... New Frontiers for Analyzing Social Networking Sites for Educational Policy & Practice. Gehalten auf der American Educational Research Association (AERA), San Antonio, TX, USA. Rehm, M., & Notten, A. (2016). Twitter as an informal learning space for teachers!? The role of social capital in Twitter conversations among teachers. Teaching and Teacher Education, 60, 215–223. https://doi.org/10.1016/j.tate.2016.08.015 Ren, F., & Sohrab, M. G. (2013). Class-indexing-based term weighting for automatic text classification. Information Sciences, 236, 109–125. https://doi.org/10.1016/j.ins.2013.02.029 Rienties, B., Brouwer, N., & Lygo-Baker, S. (2013). The effects of online professional development on higher education teachers’ beliefs and intentions towards learning facilitation and technology. Teaching and Teacher Education, 29(0), 122–131. https://doi.org/10.1016/j.tate.2012.09.002 Supovitz, J. A., Daly, A. J., & del Fresno, M. (2015). # CommonCore: How social media is changing the politics of education. Abgerufen von http://repository.upenn.edu/hashtagcommoncore/1/
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