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April 11, 2012 / dlitgroup

Sensemaking: Beyond Analytics as a Technical Activity

EDUCAUSE Learning Initiative Online Spring Focus Session 2012

  • Introduction by Malcolm Brown…
  • Learning Analytics is widely used term.  For this session “analytics” is the collection of data, use of explanatory and predictive models, and creates actionable information.  Learning is the data that learners generate and the data created provides information about the learner and other related demographics from other systems.  The goal of analysis is to enable decision making – discover trajectory and to engage in predictive modeling that contribute to student success.
  • Focus session web site: http://www.educause.edu/ELI124
  • There are more than 140 participants on the call.

Sensemaking: Beyond Analytics as a Technical Activity

Analytics, big data, and cloud computing have infiltrated the conference circuit, publications, and consultancies. The refrain is clear: data is an asset, organizations need to do a better job of managing and analyzing this asset, and new [technology, tool, method, company] will help *your* university deploy analytics as a competitive strategy. A step back is needed. Analytics are not new. And a technical-only strategy will doom any analytics project to failure. This presentation will explore learning analytics from the perspective of sensemaking – social cognitive processes people use to understand the world and the data they encounter. Emphasis will be on how researchers/educators/administrators can used technical (or big data) analysis to interpret patterns and plan for change strategies that incorporate social aspects of sensemaking. The intent of learning analytics is not only to evaluate what learners have done or what they might do; analytics should help educators make sense of the meaning of the technical analysis of learner activity so they [the institution or educator] can respond and act with consideration of the social dimensions of learning.

Associate Director, Technology Enhanced Knowledge Research Institute
Athabasca University
Notes:
  • Slides available here: http://www.slideshare.net/gsiemens/eli-2012-sensemaking-analytics
  • Analytics is the intent is to give us a better understanding of the issues we face and a way to tackle them.
  • “Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs.”
  • Analytics model and data loop.

    • Collection & Acquisition
    • Storage
    • Cleaning
    • Integration
    • Analysis
    • Representation & Visualization
    • Action
  • “There is a gold mine of student activity data in LMS’s.”  Also there are addition connections within the SIS and classroom sensors for attendance, etc.
  • http://www.snappvis.org/ is a tool that maps out LMS discussion forum activity.
  • “Analytics should lead to new ways of thinking and acting.”
  • Key areas of LA = Educator intervention, learner self-regulation, rethinking teaching, evaluating learning design.
  • Why sensemaking?  Because there are multiple data sets and sources, learning is complex, and integrated social and technical systems provide diverse and varied approaches.
  • “Hmmm that is odd” what does the data mean?  We need to have a bit of a healthy distrust or at least an understanding of the complexity of learning and varied factors.
  • “Sensemaking is a motivated, continuous effort to understand connections … in order to anticipate their trajectories and act effectively” – Klein et. al. 2006
  • Feedback mechanisms that are timely can be the most important, rather than the end of course feedback structure, so that action can be taken midstream.  Intervene in a meaningful way.
  • Ethics with Learning Analytics is available here.  [Google Doc]
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