October 28 2016

Educause 2016 Day 2: Highlights and Takeaways

Written by Stewart Rogers

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annual conference logo.pngLambda is at Educause this week! Since the launch of our LMS reporting and analytics solution, Zoola Analytics, we have been active members of the learning and analytics community. We are excited to learn what our peers have to say, and contribute to the existing discussion around analytics in education. Day two was very insightful, and it reinforced many of the ideas that supported the development of Zoola. Here's our recap. 

The first session of the day was delivered by the Director of Technology and Analytics at JISC, Michael Webb. His presentation, “Deploying Open Learning Analytics at National Scale: Lessons from the Real World,” summarized JISC’s Effective Learning Analytics Initiative. This initiative, still in its research phase, is something we at Lambda have been watching very closely. Our key takeaway was a reminder that learning analytics shouldn’t be the responsibility of just the LMS Administrator, or just one person at an organization. Ideally, there should be a cross-functional committee that has executive buy-in. The best practice for higher education is to ensure that students are part of the committee, so there is transparency in how you’ll be using their data.

“Innovation to Drive Student Success through the LMS and Beyond”, came next, reinforcing the fact that having data, analytics, and reports to segment and understand the relationship between LMS activity (such as logins, resource views, contributions, forum activity), and course completion/achieved grades is critical. This hit home for us, as this is something we help our Zoola Analytics customers with every day.

After lunch, we visited a few of the poster sessions, including “Mining the LMS” Identifying Transactional Elements for Prescriptive Analytics” and “Personalizing Learning with Real-Time Analytics.” For anyone who is unfamiliar with what a poster session is, it’s a simple presentation of organized research that is still in the “brainstorming” phase. It’s a great way to get some early insight on some future thinking for the concept. For Lambda, the poster sessions reinforced that you need data from multiple systems to get the big picture.

“Founding a Data Democracy”, presented by Lige Hensley and Brenden Aldrich outlined three important attributes of your learning analytics programs:

  1. You should have access to ALL data.
  2. Make data easy to interact with.
  3. Speed counts.

People should not have to wait for data - reports should be generated in seconds, not minutes or hours. If it takes too long to load the initial set, there will be little patience to interact with the data and get true insight. Hensley and Aldrich also shared a short story, about how different departments had seemingly asked for the same data. However, each individual nuance of the requirement led to different results creating a communication challenge between stakeholders of those departments who were arguing about the same, but ultimately different perspectives on the same data. This poses the question - Does your enrollment, completion, or grades report mean the same thing to all your stakeholders?

The last two sessions of the day both touched on “Big Data” and “Predictive Analytics,” and both used data to drive decision and improve academic and administrative operations. A common notion in both presentations was that full control over your data is critical. Your data and the questions you ask of that data is specific to your organization. To effectively visualize your data, whether with charts or tables, you need to control the definition of your data, and you need to have control to create the interactions and visualizations of your data.

What Lambda took away from day two, is that higher education is diving head first into data analysis. Every learning analytics session was well-attended, with engaged attendees asking lots of question. During one of the presentations today, someone showed a statistic that in 2011, the Education sector was least prepared to dive into data analysis - with dashboards, big data, or predictive analytics. If what we’ve seen in these last two days is reflective of the new norm, then higher education has made up a lot of ground, and might even be leading the way for other sectors. Higher education institutes are changing the way they engage with students - an action that is being driven by data and learning analytics.

 

 

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