Using student analytics to improve the student experience and underpin success at university
“Presented in a manageable way, data can be used to predict attainment, readily identify issues and implement the appropriate early intervention strategies”
Dr Paul Dowland, Senior Lecturer at Plymouth University and the architect of the S3 data system, discusses how data collected by systems such as Cengage Learning’s MindTap on the online activity of students, is being used effectively to identify top resources, improve the student experience and underpin success at university.
Student data in the form of exam results has been used in the past to evaluate the performance of individual departments within universities and student outcomes. Today universities are taking this one step further, using real-time data on student attendance, frequency of access to the university’s virtual learning environment (VLE) and level of contact with tutors. This is helping to improve student retention and results, as well as ensuring courses are better run.
Student analytics is defined by the Society for Learning Analytics Research (SoLAR) as the measurement, collection, analysis and reporting of data about learners and their contexts, for the purposes of understanding and optimising learning and the environments in which it occurs.
All universities have access to student data through their record systems and learning environments. Presented in a manageable way, this data can be used to predict attainment, to readily identify issues and to implement the appropriate early intervention strategies.
“It is important to remember that while data can be very useful, human skills are still required to interpret and apply the information in a useful way”
Data vs. human
It is important to remember that while data can be very useful, human skills are still required to interpret and apply the information in a useful way. One-to-one meetings between a lecturer and a student can uncover details that data analysis alone would be unable to provide.
A clear institution-wide policy on the role of data drawn from student analytics should be agreed at the onset. Data typically draws on information that is easy to measure, for example, it can confirm that a student has taken a book, but not if they have read it.
Universities should ensure that students understand exactly why their personal data is being collected, processed and stored. It is also important that universities resist collecting too much data, irrespective of its relevance – the motivation for any system should be to facilitate information sharing for the benefit of the students.
“Universities should ensure that students understand exactly why their personal data is being collected, processed and stored”
At Plymouth University, we use the Student Support System (S3) to collect assessment submissions, monitor academic attainment, tutoring and attendance records. This helps lecturers to better manage and support over 15,000 students.
Commercial companies that store and analyse data include Oracle, SAS, Newton and Cengage Learning’s MindTap. MindTap is a new personal learning experience that combines all of the university’s digital assets – readings, multimedia, activities, and assessments,integrates with the university’s VLE and allows tutors to set mock exams using the assessment feature to track student progress and to identify areas where further tuition is required.
Student analytics is an important development in higher education as, in an increasingly competitive market, the potential for using data to improve services, student retention and student success is clearly evident.