What teachers can pull out from learning analytics

Evaluating student performances has always been a part of a teacher’s job, but the tools educators used to have at their disposal were insufficient: without the aid of technology, assessing students’ strengths and weaknesses used to be a long and tedious job and the grading system alone was often misrepresentative of the actual learning that was occurring.
Enter learning analytics. While its use is still in its infancy and not all studies agree on its effectiveness or even its basic definition, most attempts at describing what it is will at least state that at its core, learning analytics is the collection and interpretation of data about students and their learning process with the purpose of assessing the current situation, predicting future trends, and making corrections to the teaching methods in order to optimise retention and engagement.

Beyond the grading system

Whether your school system employs letters, numbers, or a different method entirely to assess academic results, students are much more than the average of their grades, they are first and foremost people—and in a world where everything we do leaves a tangible digital trace, people generate data wherever they go. Gone are the days when comparing test results was the only measurable way to verify the effectiveness of teaching: particularly in the case of online courses, where every minute of activity can be recorded and analysed, artificial intelligence can help teachers examine greater volumes of data and derive trends from heterogeneous, unstructured data sets that are much more telling than grades alone and can answer more meaningful questions.
Tracking how much time students have spent on a certain part of the material, for instance, can be an indicator of their ease of understanding: if most of the class breezed through chapter one, but seemed to hit a roadblock in chapter two, you might want to review it. If a large number of people had trouble with the same assignment, it may be a sign of a widespread misunderstanding of an important concept that needs clarifying. Checking how many times multimedia attachments have been downloaded or played from the course’s online platform may also reveal some red flags: have students been skipping some material or going over it again and again? Both extremes are worth investigating: they may be bored with that particular form of learning or struggling to keep up with it.
In short, thanks to the support of technology, learning analytics can track the quality of your teaching, not just the quantifiable results, and give you pointers as you go along so you can teach at your best.

Identifying outliers

Learning analytics can be great at keeping track of common trends, but naturally, every trend has a few people going against it. Teachers can use the data they collect to assess the general reaction of a class to the material being presented and implement changes for everyone, but learning analytics is also a valuable tool to help single students rather than entire classes. Identifying the outliers who do not appear to be engaging with the lessons in the same way as their peers can go a long way in tailoring the learning experience to their individual needs and interests and providing an adequate challenge level for each student. Outliers can be found at either end of the scale: exceptionally poor results can be indicative of a student who is falling behind and needs additional support in the form of extra tutoring or a simplified version of the material (a judicious application of learning analytics may even catch the early signs of an as yet undiagnosed learning disability and prompt the teacher to refer the student’s family to a specialist), but anomalous data can also result from a student who is too advanced for the class and needs a specialised curriculum to keep engaged.
Thanks to learning analytics, test results become only a small fraction of how a student’s learning can be measured, and it is up to teachers to make the most of the huge amounts of data that can be gleaned from their activities: with the help of EdTech, there is no excuse for the obsolete one-size-fits-all model that used to dominate schools back in the day.