Using analytics to track academic performance

By Tableau

How Ngee Ann Polytechnic in Singapore visualises data to understand its student population better.

Image: Ngee Ann Polytechnic/Facebook

Will the best students really continue to excel when they leave their secondary schools for the polytechnic? With analytics, it is possible for their lecturers to find out.

Ngee Ann Polytechnic in Singapore has been exploring Tableau’s visual analytics platform to model data on their students’ academic performance and learning profiles from across its schools and gain insights. “From looking at those data, we are able to better understand how our students perform,” says Lim Shee Chee, Course Chair (Business Information Technology) and Senior Lecturer, School of Business & Accountancy.

This becomes particularly important as the Ministry of Education is encouraging more Institute of Technical Education (ITE) students to further their training through the polytechnic system, he said. In recent years, as more students are admitted into the polytechnic via the Early Admissions Exercise, it would also be interesting to gain insights into their performance vis-à-vis those who are admitted via the Joint Admissions Exercise, Lim adds.

Data skills in demand

Schools in Ngee Ann Polytechnic are using Tableau’s visual analytics tools to track its students’ performance over time and across groups. By using predictive analysis, issues can be detected early and preemptive measures put in place. It aims to ensure that standards are maintained, and students’ learning experience enhanced. Resources are channeled to areas where weaker students need more help and to programmes which may stretch the academically stronger students.

The school began collecting and feeding data into dashboards that reveals insights and trends. Course Chairs such as Lim can then understand the learning dynamics among their students across different levels, different modules and even different courses.

Lecturers and Course Chairs will be able to explore questions such as: Is it necessarily true that students with less ideal ‘O’ level results are more likely to struggle and perform below average? Or is it necessarily true that students who come in with very good results will continue to be just as good? Does it differ across courses?”
“It’s a plus point for students who know analytics.”
As industries go through digital transformation, there is a need for the students themselves to prep for future jobs by learning data skills. Students with such skills have an edge when they begin internships, Lim says. “Increasingly what I am seeing is that the companies are asking them, ‘Can you do analytics for me?’ It's a plus point for students who know analytics.”

Lifelong learning

The polytechnic has also observed a fascinating trend with their adult students, says Lim. “Even highly-educated people enroll into our specialist and advanced diplomas in business to learn how they can see and understand data on their own and in an interactive manner without the need to be trained in IT,” he notes.

This has become more common as various professions become exposed to data analytics in various ways. “The technology has become very accessible to people. Not just the programmers, not just the analysts; it can now be the person who runs the HR department,” Lim says.

The polytechnic is expanding the use of data analytics in student administration, finance and human resource, amongst others. More end users besides teaching staff are being trained to use data analytics in their day-to-day work. Slowly but surely, the polytechnic is moving towards a more data-driven culture of learning and doing.

With data analytics, it is possible to track students throughout their entire academic journey and uncover powerful insights that can help shape their education and learning. This means that educators are able to sharpen their focus on the most important thing: teaching and nurturing future talents.