Learning Analytics is the Next Frontier in Higher Ed | 7SIGNAL | Blog

At the Campus Technology Forum that recently took place in Long Beach, CA we met both educators and IT professionals who were interested in learning more about how technology could help both students and professors in the classroom.  There was a keynote that I found to be extremely interesting, which was the last one of the conference. It was delivered by Dr. Ellen D. Wagner, the Chief Research and Strategy Officer for the PAR (Predictive Analytics Reporting) Framework.  The PAR Framework is a collaborative, non-profit, multi-institutional data mining project that aims to analyze and understand the factors, behaviors, policies and conditions that promote student momentum leading to successful student outcomes. Institutions are encouraged to submit their data and become a part of the collaborative effort so as to contribute to the data pool and the quality of the learning analytics generated, which everyone can benefit from.

As Wagner pointed out in her presentation, the "Big Data" obsession has yet to grip higher education in the same way that it has other market sectors, which is ironic considering that academic-types love collecting and analyzing data...why not use it to assist in the business of teaching students.   As a result of arriving late to the party, many institutions lack the information,  actionable business intelligence and processes that are required to stay competitive in a market experiencing widespread disruption.

Retailers examine demographics, shopping patterns and spending habits to understand their customers in a way that facilitates the buying process and creates a positive, more personalized experience.  Shouldn't universities approach their customers (the students) the same way?  Yet, many institutions are, well…institutionalized.  Please don't mistake the intentions, the devotion to students by faculty and administrators has not diminished by any means. However, entrenched in tradition and reluctant to change (like in any business), many are not prepared to embrace analytics nor agile enough to roll out advanced technologies and processes that may positively affect student outcomes.

However, the PAR Framework is ready, willing and able to help. The reasons to get your institution plugged into the PAR Framework are compelling and threefold:

• First, you will be able to benchmark your institution against others.  This is a great place to start because knowing how you stack up against your peers is pivotal to growing your awareness on issues relating to student outcomes at your college or university.  In addition to your own key performance indicators, measuring against other institutions with similar profiles is another effective way to measure performance improvement.

•  Second is that you will be able to take advantage of the predictive models that have already been developed. These models provide the actionable intelligence you need to make policy decisions. For example, you may want to know if there a correlation between drop outs and text book purchases.  If so, then this may affect policy with regard to how can we help students obtain the tools they need for success.  Or perhaps there is a correction between Wi-Fi classroom coverage and positive learning outcomes.  You may also develop your own models based upon your institution's data and unique profile.

•  This leads to the final reason to get involved with the PAR Framework, the creation of an Intervention Matrix, which triggers actions based on a cross section of criteria. We want the data  to notify us when particular students or groups of students are at risk based on a confluence of events or activities. This is where learning analytics can have the most positive impact.

The charter for most institutions is to prepare students for the real world.  We can do that when we are data driven and when we understand how policies affect behaviors and student outcomes. Take a serious look at becoming a contributing institution to the PAR Framework and start down the path of using analytics, like other businesses do, in order to serve and satisfy customers.

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