My main interest this year’s EDUCAUSE conference is to learn about how new technologies may impact higher education, whether that is through providing new features for students, or by making our services more efficient and reliable.  The sessions I chose on the first day covered AI-driven learning technologies, cloud-based infrastructure, and how to make best use of predictive analytics.

In the first session, four vendors gave short presentations about their adoption of artificial intelligence techniques.  The most interesting, but perhaps least immediately useful, was from Alfred Essa of McGraw Hill, who referred to Learning Science as well as Data Science, and how AI techniques can tailor learning to the individual student.   The other vendors all explained how they were augmenting their products with features such as automatic audio transcription, topic extraction and classification of documents, image tagging and search, handwriting detection, tagging of people in videos, and so forth. It seems these will be standard features soon, if they aren’t already.

Artificial Intelligence & Machine Learning – The Art of the Possible

April SIim, a database administrator from Southern Utah University, gave a more down-to-earth presentation about moving her IT infrastructure to the cloud, using Amazon Web Services and Docker.  Her short talk was full of practical guidance.  She was very clear on the benefits, which include better performance, disaster recovery, freedom from patching, and increased security.  Our institution, as a much larger and more diverse University than SUU, may or may not see the same benefits, but we can take notice of the lessons learned, including careful evaluation of the available options.

Moving an Entire Infrastructure to the Cloud – AWS and Docker

Predictive analytics are all the rage in higher education at the moment, especially among colleges that need to reduce their student drop-out rate.  As with any technology, buying the system or service is not enough; the challenge is how to make best use of it.  Presenters from Montgomery Community College explained how they made it work for them.  The key is a cross-disciplinary team, empowered to make interventions.  The team includes the Chief Digital Officer, the Director of Marketing, the VP of Student Services, Academic Advisors, and others.  They meet for two hours every fortnight, actively investigating the data and iteratively testing interventions.

A Researcher, an Advisor and a Marketer Walk Into a Predictive Analytics Tool

The future, as William Gibson said, is already here, it’s just unevenly distributed.  It’s quite possible that we will adopt some or all of these technologies over the next few years.  So we need to understand what benefits they might offer and what we would need to do to make best use of them.  Sessions such as these are

Artificial Intelligence, Clouds, and Prediction: Day 1 of EDUCAUSE 2017 / Information Services Applications Directorate Blog by is licensed under a