What are These Mysterious “Learning Analytics”?

In the 20^th installment of training tips for ships we broached the fascinating topic of big data and learning analytics. As was written in that article, big data is going to change everything. And it is certainly going to change how we train, and how successful we are at training. The article began by talking about big data and, most importantly, provided some ideas on how to start collecting this data. Learning analytics relies on data and therefore it is the quantity and quality of this data that will determine the success of any learning analytics program. Now that the previous article has laid the groundwork for how to begin collecting data, it is time to really understand what learning analytics is and how we can use these data to derive insights.

Learning analytics may be a new term for many. It is just a fancy way to refer to the insights that we can derive from data collected through our learning and operations platforms. For a proper definition I will resort to the cliche tactic of referring to Wikipedia:

Analytics is the systematic computational analysis of data or statistics. It is used for the discovery, interpretation, and communication of meaningful patterns in data.

It is the second half of this definition which is the interesting part. The “discovery, interpretation, and communication of meaningful patterns in data”. The data referenced in our case is the data referred to in the previous article of training tips for ships - that which is collected from our operations, learning, and assessment technologies. And in our case, we are talking about a specific kind of analytics, those which help us derive insights about learning. So specifically, according to Rebecca Ferguson of the Open University, “Learning analytics involve the measurement, collection, analysis, and reporting of data about learners and their contexts, in order to understand and optimize learning and the environments in which it occurs”.

Learning analytics can be retrospective or predictive. That is, we can look at past data to try to tell us what happened and why it happened. But perhaps more interestingly they can help us determine what is likely to happen in the future based on past events. Gartner has broken this down into four kinds of analytics. “Descriptive analytics” tell us what happened. “Diagnostic analytics” tell us why something happened. “Predictive analytics” inform us of what is likely to happen. And finally, “prescriptive analytics” help us understand how we can make a desired goal happen in the future. For instructors, training centers, or operators, there are many examples of learning analytics that can be tremendously valuable. For example, analytics can identify problems that students are having with learning material. They can identify at-risk trainees who are having difficulty learning the content or who are falling behind and are at risk of failing. Similarly, learning analytics can identify indicators of success and highlight those trainees who are likely to outperform in the future and could be considered for advanced training or leadership opportunities. They can even help us understand what experiences, training centers, or training personnel derive the best outcomes or are in need of improvement.

In a compliance-oriented and safety-critical environment like ours, it is also easy to imagine analytics that help sustain operations, reduce accidents, and even save lives. Considering diagnostic analytics, it may be possible for learning analytics to help us understand the patterns that have led to an incident or accident. If we have fallen out of compliance, similarly these analytics may identify the patterns that resulted in that lapse. Looking forward, the return of those same patterns may be an indicator of a future compliance lapse or impending safety incident. In this way, learning analytics are even more valuable and critical in the maritime industry than they are in most typical learning

There is clearly more to understand about learning analytics. Indeed, it is the life’s work of many researchers and practitioners. But the goal here is to raise awareness of the importance of big data and learning analytics as a tool so that we may take advantage of opportunities to improve performance, compliance, and safety, as they are available. All the best and until next time, sail safely.

WATCH Murray Goldberg discuss the importance of the 4^th Annual MarTID survey of Maritime Training Practices.