In 2023 I began a degree in Information Systems, focused on data analytics and machine learning. This page is an overview of a project I did in 2023-2024 applying the skills I’ve picked up to the new field of learning analytics.

“Learning analytics” both as a term and as a field is relatively new — most date it to 2011 — and the state of the discipline reflects that, with formal academic programs and conferences remaining relatively sparse. That said, several excellent books on the subject have been published in the last few years. Megan Torrance’s Data Analytics for Instructional Designers is a good intro to the field, though it doesn’t really dive into technical methodologies. For that, I’d really recommend a recent publication by Mohammed Saqr and Sonsoles Lopez-Pernas, Learning Analytics Methods and Tutorials: A Practical Guide Using R.

My interest in applying data analytics to technical training was sparked by years as a curriculum developer and instructional designer working for OF Course and Tech Elevator. Basically, in both cases I was working with a proprietary LMS built by software engineers that captured a huge amount of student data — but how could this data be leveraged to make meaningful contributions to learning outcomes?

SCORM-compliant training and e-learning courses remain the standard across the ID industry, largely because the vast majority of corporate and academic institutions committed to the standard decades ago. The rise of mobile devices and IOT has made the newer xAPI standard a tantalizing possibility for educational development, but the difficulty of implementing it and effectively filtering the big data it produces has prevented it from quickly supplanting SCORM.

The dataset I decided to use for this project is relatively small, and is drawn from a few classes run online on the Shanghai-based OF Course platform.