Making waves in education

The seeds for this new way of thinking were sown when a young working-class boy, the first in his family to university, arrived at Cambridge in the late 1980s. After struggling to understand this strange new world, (now Professor) Karl Maton became determined to enable anyone to understand the basis of success in education, regardless of their field. During the years of research that followed it became clear that this required a new way of thinking, because education often ignores the very thing it is all about: knowledge.

“For decades, education has been dominated by approaches that focus on either who is learning or how they’re learning,” Professor Maton says. “The result is that what students are learning, the knowledge itself, is often ignored.” This matters because whether the knowledge is simple or complex, concrete or abstract affects how best to teach and learn that knowledge. So Professor Maton set about developing ways of making explicit the forms of knowledge required to succeed in education.

The result is a sophisticated framework called Legitimation Code Theory (LCT) that is recasting the way scholars and educators think about education by putting knowledge at the centre of educational practice.

Making ‘semantic waves’

One example of how LCT is reimagining learning is the notion of “semantic waves”. A growing number of educational studies around the world show that students are assessed on their ability to “wave” between concrete and abstract, complex and simpler forms of knowledge. This is rarely, if ever, made explicit by teachers or assessment bodies, but it is a distinct attribute of the world of high-achieving students across the curriculum.

Using LCT, teachers are making this explicit to students. For example, in school classrooms in NSW, teachers draw images like the one below to teach students that their writing needs to move between theory and evidence or between abstract ideas and concrete experiences. Students then use the waves to plan their writing.

In science, for example, students plan how to bring together scientific knowledge about Earth’s tilt, rotation and distance from the sun with the lived experience of seasonal change. This relatively simple idea is proving remarkably valuable in all kinds of subjects, including teaching ballet, jazz technique and computing skills.

One theory, many applications

By bringing knowledge into the picture, LCT is rethinking all kinds of longstanding educational problems. For example, some of us value first-hand experience, while others value more objective procedures. Teachers and students use LCT to “code” these different ways of thinking, to show the strengths and limitations of each code, and to avoid clashes between different codes.

This offers a new way of thinking about interdisciplinary learning. Where previous approaches emphasised that students should be open-minded, generous and respectful, LCT is showing the forms of knowledge they should be open-minded, generous and respectful about and why. This power to support teamwork is why LCT forms a key part of innovative new courses across the University of Sydney in which students from different disciplines work on real-world problems.

Though its heart is at the University of Sydney, LCT is reaching around the world. In South Africa, lecturers are advancing social justice by coding the ways of thinking that first-in-family students are bringing to university to figure out the best ways of teaching those students what they need to learn in their chosen subject areas. Beyond education, Professor Chuanyou Yuan and Dr Jie Zhang at Guangdong University of Foreign Studies in China are coding prisoners’ ways of thinking to identify the most appropriate forms of counselling to support their rehabilitation.

Artificial intelligence

At the LCT Centre for Knowledge-Building at the University of Sydney, work is progressing on using artificial intelligence (AI) to analyse the knowledge expressed by students in language and images, and to provide feedback in real time on how they can build knowledge more productively. The centre is developing a “proof of concept” – the next step is working with development partners such as Google and Deloitte. “We aim to put educational success within everyone’s reach,” Professor Maton says. “AI that helps you learn and create knowledge wherever you are will be a game-changer.”