Open Michigan Blogs February 2017

A pie chart and a line graphs on a tablet computer screen next to a cup of coffee
February 13, 2017
By Author:
Marissa Gomez

    As we have more ways to collect data about how people use web-based content, analytics has become the buzzword in many spheres, including academia. Determining important metrics, looking for patterns and relationships in big data sets, and telling a story behind the numbers are all crucial components of analytics that hopefully lead to actionable insights. The abundance of information that exists today can provide great value. Faculty frequently use tools like impact factor when monitoring their scholarly publications. However, in the case of Open Educational Resources (OER) the criteria to measure return on investment is murkier.

    Since working for Open Michigan, I have had the opportunity to investigate and create a reporting system that provides faculty contributors  with data about their course. To develop the best possible tool for our users, we are interviewing faculty to gauge their expectations for a system like this, trying different reporting tools, and focused on creating value through these reports.


The Process:

    Our data lives in Google Analytics, and a very fundamental piece of our reporting involves understanding how faculty contributors  are looking to measure success of their courses on Open Michigan in terms of audience, traffic, and engagement metrics. Our goal is to provide insights that tell us who is using Open Michigan and how, which can be beneficial in the growth of Open Michigan as a platform and as a service. It has been a great opportunity to learn from faculty and their history with Open Michigan, and it will be interesting to synthesize the information we receive from our interviews. Given the disparate backgrounds of faculty members and their prior experiences reviewing analytics reports, it is important to create a valuable and insightful tool that encompasses these diverse needs. Lastly, it is essential to find a tool that will allow for customization without a steep learning curve, to support future curation of reports by any Open Michigan team member.

     We hope to achieve better communication and service between Open Michigan and faculty contributors  by creating these reports, and we hope that these reports may provide insights to faculty that they can use to improve the way they use services like Open Michigan as educational tools. It is also my hope that by using analytics for our platform, the Open Michigan community can get a better understanding of our audience and learner behaviors with OER with quantifiable results.