Analyzing Online Teacher Networks: Cyber Networks Require Cyber Research Tools

By Schlager, Mark S.; Farooq, Umer et al. | Journal of Teacher Education, January-February 2009 | Go to article overview

Analyzing Online Teacher Networks: Cyber Networks Require Cyber Research Tools


Schlager, Mark S., Farooq, Umer, Fusco, Judith, Schank, Patricia, Dwyer, Nathan, Journal of Teacher Education


We are in a period of transition to a world in which all human networks will be mediated through cyber-enabled technologies (e.g., Web, Internet2, and mobile; Tapscott & Williams, 2006). (1) Information and communication technologies that power complex social systems are rapidly scaling up and becoming integral to daily life around the globe. The ubiquity of online social networking in popular culture and the business sector heralds the promise of online social networks for education (Leana & Pil, 2006; National School Boards Association, 2007; National Science Foundation, 2005; Penuel & Riel, 2007; Resnick, 2002). The popularity of cyber-enabled social networking among youth and teachers of the net generation is undeniable. The Pew Internet and American Life project (Lenhart, Madden, Macgill, & Smith, 2007) report that more than half of all of online American youth ages 12 through 17 use online social networking sites. A more focused study by the National School Boards Association (2007) reports that 96% of students with online access have used social networking technologies and more than 50% talk online specifically about schoolwork. Regarding teachers, the National School Boards Association reports that in districts where structured online professional communities exist, participation by teachers and administrators is quite high. These reports and others (e.g., Atkins et al., 2003; Computing Research Association, 2005; Fulton, Yoon, & Lee, 2005; Jenkins, Clinton, Purushotma, Robinson, & Weigel, 2006) envision a future in which cyber-enabled social networks become a central context for student and teacher learning and a catalyst for instructional improvement.

To harness the power of this societal transformation to serve teaching and learning, we need to understand the phenomenon and unlock the value it holds. The National School Boards Association study (2007) tells an optimistic but cautionary tale, reminding the research community that education administrators and policy makers will permit access to social networking only when the strong educational value and purpose of such networks can be demonstrated. Research must help education communities convert the current enthusiasm for online social networking into reliable evidence of how, when, and why online social networks do and do not advance learning, and we must develop scalable and replicable models that maximize the value and benefits of emerging social networking models and technologies.

This article presents a long-term research agenda aimed at meeting this challenge through the development of new analytical frameworks and more integrative and automated methods and tools that can rapidly mine and reliably analyze the massive amounts of data generated by cyber-enabled social networks. We begin our exploration with a basic question in social network analysis (SNA): What constitutes a meaningful relation or tie between individuals? Our goal is to answer this question using a combination of traditional SNA methods and new, more scalable methods that use automatically recorded interaction data.

Applying traditional SNA methods can be problematic in large-scale cyber-enabled social networks, which typically do not have a well-defined structure and are therefore difficult to put boundaries around. Moreover, SNA methods are limited in their ability to identify the precursors of and other enabling factors for social capital or trace how social capital is fostered and leveraged (Leana & Pil, 2006). Cyber-enabled social networks offer the ability to capture and analyze a more complete and objective record of peoples' actions and interactions automatically over time. However, digital interactions are not simple to mine or interpret. In addition, interaction data are missing a key ingredient of SNA: judgments about the strength of social ties.

Research Context: Professional Networks in Teaching

The context of our research is analysis of professional networks in teaching (Lieberman, 2000), such as professional learning communities (Dufour, 2004; Stoll, Bolam, McMahon, Wallace, & Thomas, 2006), teaching communities of practice (McLaughlin & Talbert, 2001), and networks with other labels.

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