How Can Higher Education Benefit from Big Data?

With higher education institutions increasingly connecting with their students via the internet, opportunities for the collection and utilisation of big data in university recruitment and pedagogical innovation are growing. The Guardian held an online forum in July which discussed the need for big data in higher education and what limits, if any, should be placed on its collection. It revealed some contrasting points of view from higher education professionals, with many singing the praises of data collection, as long as it’s done with caution.

The belief is still held strongly that big data can help to improve student performance, enhance teacher effectiveness and reduce the administrative workload for university staff, if used correctly.

How can meaningful big data be collected?

Student performance data is increasingly being captured through measuring interactions on online resources and virtual learning environments (VLEs). This has allowed universities to compare the level of engagement against previous years and against other universities. Information such as hours logged in VLEs, amount of resources accessed and number of submissions will give a representation of the student experience that is still, despite its limitations, very measurable and comparable.

When combined with other information such as behaviour on social media, notes from professors, blogs and surveys, it’s possible to paint a fairly clear picture of student behaviour and the overall performance of the university. However a lot of data is still being tracked for no real reason.

How can universities use big data?

The big topic for debate comes when deciding how best to use the data that you collect. Data analysis used for the benefit of students and the improvement of university services is generally considered to be acceptable. The line is generally drawn at marketing products and services that are more about profit than progress. Big data still has the ability to provide prospective students with more information and better options, thus enabling universities to improve both student performance and student recruitment in several key ways:

1 – Student recruitment

Big data from current and former students such as historical performance and demographics could be used to create student profiles. HE institutions could then incorporate information of behaviour of past and current students on social media in order to more effectively target their ideal candidates for student recruitment.

2 – Improve student performance

It can usually be agreed that using data to help current students stay on course towards a good final grade is a good idea. Test results and academic performance can easily be tracked and compared to previous performance as well as those of similar students. Other data such as teacher notes and social media data can give more of an insight to a student’s behaviour and flag up any significant changes in performance.

3 – Teacher effectiveness

Sometimes students fall behind due to stress, family issues or other factors that are beyond your control; one factor that you can control, or at least monitor is the effectiveness of your teaching staff. This is not necessarily a method of holding the teaching staff accountable for how their students perform, but as a metric to help them be their most effective. Which courses do they teach that have the highest engagement from students? What methods and tools do they use (such as VLEs and online lectures) and how effective are they?

Let us know your thoughts on Twitter on how big data should be used in higher education:

Tweet: @QS_Digital #BigData #HigherEd | http://ctt.ec/OiRE4+

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