The words ‘analytics’ and ‘data’ might seem alien or even intimidating to most of us – unless you are a number-cruncher or a market analyst, why would they be of any use, right? However, Professor of Learning Analytics at The Open University, Bart Rienties, has spent much of his career researching how data can improve teaching methods and have a positive impact on how students learn.
Making sense of data through context
“We rely on data in many aspects of our lives to develop our society and understand the world we live in. However, any data is difficult to understand without contextual knowledge. For example, knowing the speed of a racing car on a track is only part of the full picture; the speed requires context – what is the terrain of the circuit; what is the weather? Furthermore, without a map of the circuit it would be difficult to predict the substantial drops in speed when turning around sharp corners. So contextual knowledge is essential to make sense of data.
For distance learning providers, such as The Open University, the challenge is to understand what our students want and, equally important, what we can develop to improve the learner experience.
Improving learning and teaching based on what students (and teachers) say they want
“We wanted to understand the needs of our students, so we developed a large scale study amongst 111,000 of our students focusing on what students said they wanted when they had completed a module. In line with principles of learning analytics, we integrated a range of data from various sources to understand what determined students’ happiness on courses.
“We analysed over 200 characteristics of over 400 modules, the students themselves, and their study history. We also reviewed what each of the 111,000 students responded in their end-of- module survey.
“We wanted to know what distinguishes ‘excellent’ from ‘good’; was it the support received by tutors; was it links to professional practice; links to qualifications; the quality of teaching materials; or a specific combination?”
‘Quality of teaching materials’ most important element
“The data provided an answer; the number one distinguishing factor between ‘excellent’ modules and other modules was the quality of the teaching materials. Similarly, the quality of the assessment was the second most important factor for new and continuing students starting in 2013/14 and the overall qualification aim in 2014/15. In other words, students’ perceptions of what is important in modules has shifted slightly, with a clear link to qualifications and career relevance, which makes intuitive sense given the national increase in student fees.”
Learning from data analytics?
“Perhaps we should improve our advice to students on achieving their goals. For some students, actually progressing through a module is already an amazing achievement, while for others, providing the opportunity to work with peers, or having a mentor, might be more useful.
“In the near future, perhaps we should start to give students personalised dashboards to help them to achieve their goals. For some students, it is extremely motivating to know how well they are doing. For other students, this competitive profiling might be extremely counter-productive.
“Finally, there are students who just want to know the options available to them. Whether that be the route that leads them quickest to their qualification, or perhaps the route that is the most intellectual challenging.”