Using Learning Analytics to improve the student experience

Can Learning Analytics help to improve the student experience?

Yesterday I was asked to speak at the Higher Education Show in London about how higher education can engage with students through improved ICT. This is obviously a broad area, and there are many areas of technology which are changing the way that students are engaging with their university.

I decided to focus on an area which I think has the potential to transform the way that institutions support students: Learning Analytics.

8 out of 10 cats

Ask 100 students what they think student experience is, and you’re likely to get 100 different answers. However, there is likely to be commonality between the answers, and top responses are likely to mention good student union, social opportunities, good academic and personal support and the quality of their course and teaching.

Never before have prospective students been able to find out so much about what past student’s have thought about their experience at university. In the UK, the Key Information Set (KIS) and the recently launched Unistats website have made available data collected from the National Student Survey and the university to allow student’s to compare institutions and courses.

Most students have always wanted to do well in their course – they want to be successful academically and be given the opportunity to be the best that they can be. However, the changes to tuition fees and funding have changed the game. Many students will invest significant amounts of money in their education which they will repay over many years. As a result, the expectations they have of their university are much higher– they have become customers and they expect the university to provide support and services to enable them to be successful academically.

What is Academic Success?

What does it mean to be successful academically? Its about about the university enabling each and every student to reach their potential. The institution helps them to recognise what they could achieve and help them to reach their aspirations. Its about the student getting the support they need to help them achieve success. Its about recognising when things could go wrong, when they have gone wrong and offering the student help and support to resolve problems. So the support, services and systems which help a student be successful academically are at the heart of the student experience.

So, identifying problems early which may mean that a student is not going to be successful is important. It means we need to find a way to measure how likely a student is going to be successful and understand how their likelihood of success is impacted by their learning style, patterns and interactions with the university.

Learning Analytics at its heart is about using data you collect about students and their interactions to help you understand the progress that a student is making and make predictions about where they might end up. By collecting data about the student such as who they are and how they interact with the university and applying analytics to that data we can use it to

  • Identify problems to help steer students toward academic success and ultimately help students reach their potential
  • Provide personalised support, by providing staff and students with the right information much earlier
  • Provide a more personalised experience for the student

Data, Data, everywhere…

I love this quote from Eric Schmidt (Google CEO):

“Every two days we create as much information as we did from the dawn of civilisation up until the end of 2003” (Eric Schmidt – Google CEO)

Users of web sites, social networks and systems generate huge amounts data about their interactions. Analytics is increasingly being used to help provide better services to customers and make predictions to help target limited resources more efficiently. An excellent example of this that I gave in my talk is PredPol, which uses crime data which has always been collected by police forces to make predictions about where, what and when crime may occur.

In the same way, students leave a trail of data from their interactions with university services. Interactions with the library and VLE, attendance at lectures and workshops, social interactions on forums and social media is being held separately in information silos by most universities. If this data is combined it can be used to understand how patterns of engagement, preparation for higher education and social interaction are likely to impact on the student’s likelihood of academic success.

The Student at the centre

By using data and Learning Analytics we can tailor support to the student by identifying issues much earlier before they become entrenched. We can also provide information to students and staff which enable them to understand in what areas the student may be struggling.

Using Learning Analytics is not about replacing existing support staff or advisors. As one speaker in the session noted, students should be partners in their learning with the university. To provide effective support to students, staff need to get to know the student and develop a relationship with them. Learning Analytics is NOT about replacing that relationship with cold hard facts about how often they have logged into the VLE. Its about providing both students and support staff with additional information which can enrich the relationship and prompt support staff to ask the right questions. Its about helping to uncover areas of need which might otherwise not have been apparent. Ultimately, this should help institutions to provide personalised support to students which enable students to be successful academically and reach their full potential.

Here’s the full presentation I gave during the session.

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