What can higher education learn from child’s play?

DOES CHILDHOOD learning hold the key to helping higher education students grasp challenging concepts? LITE Teaching Enhancement Project leader, Nimesh Mistry, writes here about some of the findings from his project here and explores the concept further.

From the day we are born we learn about the world around us by interacting with our environment, trying to make sense of it all so that we can use this information to survive.

I have a three-month old son who is fascinated with the different textures of objects so my wife and I give him toys made of different materials to feel how they can be hard, soft, warm, cold, smooth and rough.

As we enter school, we learn how materials can be solid, liquid or gas by investigating the different properties of substances such as sand, water and air.

And we learn about gravity by dropping objects and seeing how they fall to the ground and about density by placing objects in water and seeing if they float or sink.

Abstract teaching

This method of experimenting with an idea or concept in science matches the natural way in which we learn about how the world works.

Its active nature is key for us to be able to grasp concepts such as states of matter and forces.

As children become older science lessons become more abstract. Concepts are taught mostly through words and diagrams, in books or on whiteboards.

They spend less time exploring and scaffolding their understanding of concepts but by the time students are in tertiary education, concepts are taught in lectures almost exclusively in an abstract manner.

Concept for learning

Alex Johnstone proposed a model that a scientific concept can be understood at 3 different levels, the macroscopic level, the submicroscopic level and the symbolic level.

For example, the properties of ice can be understood at the symbolic level with the symbol H2O(s).

At the submicroscopic level it can be understood by picturing molecules of water held rigidly by intermolecular forces.

Then at the macroscopic level the properties of ice are conceptualised with an ice cube.


In this context, it’s easy to see how the active learning methods in early education has children working across the 3 levels of the triangle.

At University-level however, teaching tends to focus at the symbolic level. Whilst experts are competent at translating between from the symbolic to the other levels, students find it more difficult.

This can lead to students coming away with a poor understanding of scientific principles, and some developing misconceptions instead.

Active learning

An alternative to the traditional didatic approach of lectures is to teach using active learning methods.

A comparison of active versus passive learning across STEM subjects found that active learning leads to improved performance.

This effect can be seen amongst all students, but is particularly prominent for students from the lower quartile, and students who traditionally wouldn’t have attended university 30 years ago.

Teaching Enhancement Project

For my LITE project, I will be developing active learning methods to help students gain a better understanding of scientific concepts.

After determining which concepts students struggle to understand, active learning tasks will be designed for students to interact and engage around the concept.

Like the methods for learning concepts as children, they will be designed to allow students to explore and experiment with the concept in question, challenge misconceptions and encourage students to translate across the 3 levels of Johnstone’s triangle.

For the duration of the project, I will focus on applying this strategy to concepts in chemistry, but it is also hoped that this targeted approach strategy will work across various disciplines.

Further reading

Johnstone, A. H., 1991, Why is science difficult to learn? Things are seldom what they seem. Journal of Computer Assisted Learning. 7, pp.75–83.

Freeman, S. et al., 2014. Active learning increases student performance in science, engineering and

mathematics. Proceedings of the National Academy of Sciences. 111 (23), pp.8410-8415.