Learning analytics: student characteristics as predictors of study success

Not everyone can take an HBO education. Only with certain previous education is a student admitted to HBO. As a rule, a student is admitted to an HBO program if he or she has a Havo, Vwo or MBO-4 diploma, possibly supplemented with additional requirements (for example, certain subjects).

So although you can't go to HBO just like that, there is a lot of difference in prior education. A student with a Havo diploma is often slightly younger than a student with Vwo as a previous education. Moreover, the level of Vwo is higher and the education is more theoretical in nature. A student with an MBO-4 diploma has already completed a three- or four-year advanced education, is a bit older and has more experience studying. The dashboard shows that there are large differences in study success between students with different prior education. Students with a Vwo diploma graduate the fastest: of students who started an HBO program in 2008, forty six per cent graduated after four years. This is more than one and a half times as many as students with a Havo diploma (twenty-eight per cent) and also substantially more than students with an MBO-4 diploma (thirty-five per cent).

What is further striking is that after eight years, the percentage of students with a Havo diploma who graduated (sixty-seven per cent) is higher than the percentage of graduates with an MBO-4 diploma (sixty per cent). So, the Havists are catching up with the MBO graduates, so to speak.

Besides prior education, gender is an important characteristic that influences study success. Forty per cent of female students who started an HBO program in 2008 graduated after four years, compared to twenty-seven per cent of male students. So, there are one and a half times more female students who graduate nominal (that is, in four years) than male students: a big difference. Men also do not make up this deficit in the following years.

Knowledge about the effects that certain characteristics or collections of characteristics (so-called profiles) of students have on study success is of great importance to educational institutions. The aforementioned characteristics in relation to study success are generally well known in higher education. However, if we go a little deeper and relate more detailed information about students to study success, surprising insights often emerge. Insights that are not based on gut feeling, but on hard data. With this knowledge, an institution can tailor guidance and support for students as much as possible, such as with specific support packages and individual interventions. Recruitment, information and guidance can be adapted based on characteristics of the student population, so that new students have a realistic picture of programs and the workload involved.

Learning analytics is about using insights obtained from analysis of student data at various levels. To get started successfully with learning analytics, it is important to approach it not as an ICT project but as a change task. Not only technology is important, but also strategy, processes, people and issues such as privacy, ethics and data protection. Ultimately, for a successful application of learning analytics, the teacher is the key to success. The use of data and analytics must find a place in the professional image of the teacher. It requires a different way of working that teachers and students must feel sufficiently comfortable with. 

Analyses of open education data and a dashboard were used to show the relationship between scale of educational institutions and student characteristics and study success. Based on these relatively easily obtained insights, several possible generic interventions for HBOs were outlined. More detailed information and detailed analyses will lead to more detailed insights, allowing for customization and appropriate individual interventions ahead. In short: the promise of learning analytics is great