Analytics ‘helps engage students’

Universities have always tracked data through the analysis of grades. The trouble is by the time the student has taken the exam and received the grade it is too late to utilise the data and make an intervention if they have been struggling.

When used well, student data can improve the student experience and boost retention. Using analytics, a student who is not attending classes or accessing university resources can be readily identified and action taken to address these issues. A student who attends lectures and is provided with regular feedback is more likely to be engaged and to complete the course.

Such data can also be used to identify elements of the course that work well and to build on these for future year groups. Similarly, library services can also benefit from identifying their most popular resources so that they can allocate their budget to best effect.

Interpreting data

Investing in analytics is the easy part, but what do you do with the data when you have it? Universities need to understand the data before they can use it to predict the future.

Questions of ethics should also be considered. For example, when making decisions based on data, should a university pool its resources for students who are performing badly at the expense of those who are doing well?

Decisions will vary, but the most important thing is to have an institutional policy in place to advise on the best course to take.

Personal touch

It is, however, important to remember the value of the personal touch. What data cannot do is replace interaction between the lecturer and the student. One-on-one meetings can uncover details that data analysis is unable to provide.

For example, lecturers can recommend a particular learning resource based on their experience and personal interaction with a student – something that cannot be gleaned from data alone.

It is also important to remember that student analytics typically draws on data that is easy to measure and capture, and ignores information that is intangible. We can check to see if a student takes a book out, but not if they have read it.

Lecturers should take care to focus on a broad range of data. For example, try not to react to a single missed lecture, but consider overall attendance.

Student feedback and data security

Using and sharing data invariably raises concerns about privacy. Universities must be transparent about who is using the data, how it is used, stored and analysed and what actions will be taken.

Students should also be made aware of their rights with regard to data access – that is, in the United Kingdom, provisions under the Data Protection Act 1998 and Freedom of Information Act 2000.

Case studies

At Plymouth University, the Student Support System – S3 – is helping academics to manage personal tutoring, attendance monitoring and basic analytics to support almost 15,000 students, including overseas partnerships.

The system collects assessment submissions, attendance records, tutoring records and academic attainment to present a wide-lens on a student’s academic life.

This enables tutors to gather a range of information (in a single system) to view the student’s engagement with their learning and assessment, as well as reviewing performance and notes from previous interactions with tutors, module leaders etc.

Even simple tools can help – for example, showing a student their marks in a visual manner:

Commercial technologies that store and analyse data include Oracle, SAS and Newton – with custom or in-house systems found in many universities.

For example, Cengage Learning's Mindtap integrates with the university’s VLE and combines all of its digital assets – readings, multimedia, activities and assessments and feeds back on how well students are performing compared to their peers.

What next?

Student analytics is here to stay. Universities in the United States, the United Kingdom and some parts of Europe are already using it to improve the student experience.

It is particularly suited to large institutions with a high teacher to student ratio looking to quickly identify specific students who are having problems and require extra help.

In an increasingly competitive market the potential for using data to improve services, student retention and student success is clearly evident.

As academics, it is important to consider that the increased usage of student analytics comes at a time where ‘surveillance’ is a hot topic and one which can provoke a strong personal view from those perceived to be under the constant watch of ‘Big Brother’.

The primary motivation behind the S3 system is to facilitate information sharing for the benefit of the students, and as such, students are reassured about the purpose of the collection, storage and processing of data relating to them.

Academic staff are encouraged to show their students the nature of the data available and to reinforce the ethos of student support after which the system itself is named.

There is, however, a danger of collecting too much data irrespective of its relevance – this must be resisted as there would be a risk of permanently damaging the relationship between tutor and student.

* Dr Paul Dowland is a senior lecturer in information systems security in the school of computing and mathematics at Plymouth University in the United Kingdom.