Polarisation gains ground when we fail to understand science

In a democracy, citizens need to think critically about complex issues such as nuclear energy, sustainability and artificial intelligence. Scientific literacy is essential for this: understanding how science works and being able to critically assess information so that public debate remains substantive and society becomes more resilient to misinformation. However, Ralph Meulenbroeks, who was appointed professor last year, sees worrying signs. Young people are becoming less able to assess scientific information critically. In his inaugural lecture on 11 March, he outlined what is needed to reverse this trend.

Polarising messages about scientific topics are increasingly common. Whether the issue is climate change, nitrogen emissions, vaccines or energy policy, politicians and influencers often rely on simplistic explanations to support their arguments. Labels quickly follow: one side is called a climate alarmist, the other a climate denier. Such framing rarely leaves room for nuance.

Critical citizens

For society to have meaningful public debate, it needs scientifically literate citizens. That was the central message of Meulenbroeks’ inaugural lecture. Science and society are closely intertwined. Citizens therefore need a basic understanding of how science works to assess claims, weigh evidence and participate in informed discussions. Only then can complex societal debates be conducted at a high level.

Meulenbroeks is concerned that scientific literacy among Dutch fifteen-year-olds has declined over the past decades. Results from the international Programme for International Student Assessment (PISA) show that the Netherlands has fallen from well above the international average to only slightly above it.

Autonomous motivation is key to both good education and the development of scientific literacy

Developing scientific literacy

If schools want to strengthen scientific literacy, good science teachers are crucial, Meulenbroeks argues. Yet shortages of qualified teachers remain a major challenge. The professor therefore proposes several measures.

Step one: spark enthusiasm for teaching. Introduce science students to the classroom early by offering them a paid part-time job as teaching assistants. Last December, Meulenbroeks and colleagues published a report showing that this approach, tested in the StudentinzetopSchool project, indeed works. Students gain a realistic impression of teaching, pupils perform better and teachers experience less workload. The initiative even attracted attention in a parliamentary letter.

Step two: remove financial barriers to teacher training. Graduates with a scientific master’s degree should be able to follow teacher training through a paid work-study programme. In this model, trainees receive a salary while completing their qualification. The idea has been discussed for some time and is also mentioned in the current coalition agreement.

Step three: retain teachers. Teachers should have opportunities to continue developing professionally and to maintain their enthusiasm for the profession, for example through dedicated development grants.

Autonomous motivation

Besides good teachers, motivation among pupils is essential. Research consistently shows that students perform better when they feel autonomously motivated to learn rather than pressured to do so. “Autonomous motivation is key to both good education and the development of scientific literacy,” says Meulenbroeks. Teachers can foster this by supporting pupils’ basic psychological needs: providing autonomy, offering meaningful challenges and giving students the confidence that they can master a task.

If the objective is to analyse large amounts of data, AI is an appropriate tool for assessment

AI in education

Artificial intelligence is a recurring theme in Meulenbroeks’ lecture. AI illustrates how scientific developments increasingly shape society and therefore highlights the importance of scientific literacy.

At the same time, AI itself is an important focus within his chair. Together with colleagues, Meulenbroeks studies how generative AI can be integrated into science education. His conclusion: despite the transformative potential of AI, the core structure of education remains unchanged. Good education always consists of three elements: clear learning objectives, learning activities to achieve those objectives, and assessment of what students have learned Some objectives may now include AI-related skills, for example analysing large datasets, but the educational framework itself remains the same.

Whether students should be allowed to use AI during assessments depends on the learning goal. If the objective is to analyse large amounts of data, AI can be an appropriate tool. But if the goal is to learn how to improve a research proposal through peer feedback, alternative formats, such as a poster session, are more suitable.