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  • Little Big Data

    The Group Informatics Lab examines the emergence, development, leadership and structure of technologically mediated small groups. More

  • CSCL at Work

    When organizations do not have the necessary knowledge to address a changing market, CSCL@Work becomes a key to sustained competitiveness.More

  • Math Forum

    NSF Funded grant looking at Accountable Talk in math discourse using VMT. New research on increasing student interest in math using social sensors.More

  • Social Media

    I have NSF and Office of Naval Research grants focused on virtual organizations and leadership emergence.More

The Zeitgeist of Google Search Phrase Trends I thought or Cared About Today

I'm teaching a course on data science this quarter, and was looking through some tools that a number of my colleagues have shared with me over the past few months. One especially interesting, starter tool for helping students think about and experiment with their own curiosities is "Google Trends". In this trend block below, I contrast google interest in "Taxes", "Health Care" and "Gun Control":

I'm teaching a course on data science this quarter, and was looking through some tools that a number of my colleagues have shared with me over the past few months. One especially interesting, starter tool for helping students think about and experiment with their own curiosities is "Google Trends". In this trend block below, I contrast google interest in "Taxes", "Health Care" and "Gun Control":

Making Sense of Big Social Data

Big Social Data

Peppo Valetto and I have been working together on what is now called Big Social Data for four years at Drexel; exploring software engineering and technology mediated learning environments. My students, Christopher Mascaro and Alan Black have been focused on the study of Big Social Data in political discourse and culture. Nora McDonald, a new student I am working with, has studied both cultural phenomena on Twitter and virtual organizations on Github with Peppo, Kelly Blincoe and I. Together, we have begun to understand and articulate the ontological, methodological, and theoretical challenges of making sense of Big Social Data. Computation is a critical element of our work; but it is secondary to the theories related to learning, coordination, discourse, information and knowledge construction that we use to frame *how* we make sense of "big social data".

My long standing passion is to have the empirical studies I do inform design. My work with Gerry Stahl, Carolyn Rose and others at the Math Forum at Drexel inform this way of thinking about "Big Social Data" as informing both pedagogical and learning technology design. Principally through Virtual Math Teams and more recently through new collaborations I am beginning with the Math Forum, focused on identifying levels of interest in mathematics as defined by Renninger.

Big Social Data for Design and Learning

From a design perspective, "big social data" is a way to frame how we make sense of the rich electronic trace data (logs) that are left behind in various learning environments; and then to use those logs to provide useful feedback to people about the learning that is taking place. Partly this is a social theory of learning framing, which is what my 2009 dissertation examines. In the four years since that once in a lifetime (for me) project, the scope of my inquiry has expanded to fields of software engineering, social media, computational linguistics, "big data" and virtual organizations. Furthermore, I have taken up projects focused on workplace learning and rural outsourcing firms that train their own workers. Why? Simply put, there is not enough signal solely in the study of how people learn in traditional, school focused contexts to identify the design ideas that are likely to push learning technology design forward to a breakthrough.

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