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Wednesday, October 17 • 11:20am - 12:05pm
Visualizing Learning Data

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The Open Learning Initiative (OLI) has been collecting learning data for a decade. The learning activities in our online courses record data on how students use the activities as well as their performance on them. Each question is mapped to a student-centered measurable learning objective in addition to individual skills to create an overall view, which can be used to answer any range of questions about student knowledge state to content mistakes. As we have learned to utilize this data, we have created tools for instructors to see at a glance how their classrooms are performing based on learning outcomes. However, we have not produced integrated ways of visualizing this data for course authors and learning scientists to use as they assess and improve courses.  Currently, the large amounts of data that courses generate can be cumbersome and difficult to interpret. These difficulties mean that learning data is not used as often as it could be and that course authors may need a long orientation period to understand how to effectively use the data.
Improving accessibility of data and speed with which it can be interpreted is essential. Data analysis plays a critical role in iterative course improvement, but it cannot reach its full potential and range of use at OLI or in the OER community without visualization tools that are easy to understand and available at the right time and context.
Over the last six months, we have been working on new visualization tools to support content authors so that they can use our data effectively and efficiently to target areas of their courses for improvement without having to run their own statistical analysis. During this presentation, OLI will discuss the discovery process we used to understand the workflow and needs of content authors. We will describe not only the vision OLI has for moving forward with data visualization, but also the process by which we arrived at our designs. Issues of granularity and context in particular will be addressed, along with ways for users to move seamlessly between appropriate visualizations.
We anticipate that these visualizations, and in particular how they are integrated into development tools, will help revolutionize the way iterative improvement is done at OLI in the future and look forward to sharing this process and findings with the OER community.


Speakers
avatar for Norman Bier

Norman Bier

Director, Open Learning Initiative, Carnegie Mellon University


Wednesday October 17, 2012 11:20am - 12:05pm
C680 - HSBC Hall

Attendees (22)