OPINION: Have we been teaching backwards for years?

This is an opinion piece; the views expressed in the column are the writer’s own.

University teaching is based on a fundamental assumption about how scientific understanding develops. Students first learn the concepts, theories and methods of their discipline. They are then expected to gradually develop, through increasing specialisation, the ability to formulate their own research questions, assess evidence and generate new knowledge. The scientific way of thinking is often regarded as the outcome of a lengthy educational process rather than its starting point.

But what if this order is wrong?

Does university teaching place too much emphasis on the results of science before teaching the way of thinking that made those results possible?

Does university teaching place too much emphasis on the results of science before teaching the way of thinking that made those results possible? Perhaps our most important task should not, first and foremost, be to communicate the latest knowledge. Perhaps it should be teaching people to understand how knowledge is created in the first place. How questions are formulated, concepts are defined, methods are chosen, observations are interpreted, arguments are constructed, and conclusions remain open to criticism and revision.

The way researchers think

This question has been central to the development of several interdisciplinary summer schools, the Summer School Cluster in Integrative Neuroscience, which I helped create. But my ambitions go considerably further than that. I want to explore whether research-based teaching can be organised in a way that introduces students from the outset to how researchers actually think, and where the discipline does not necessarily constitute the natural starting point for learning. 

Part of the inspiration comes from my meetings with very talented junior researchers and PhD students. Some were far more skilled than I was in specific analyses and techniques, and had an impressive knowledge of the literature and traditions within their field of research. At the same time, they may have given remarkably little thought to when what they were doing actually amounted to a scientific argument, namely why their chosen method should offer insight into the particular aspect of the world they wished to study, and what alternative ways there might have been of approaching the same question.

This is not a criticism of the students. On the contrary, I see it as a possible consequence of the way most degree programmes operate today. 

This is not a criticism of the students. On the contrary, I see it as a possible consequence of the way most degree programmes operate today. We create students who are good at working within an existing scientific practice without necessarily teaching them to make this practice, and its basic assumptions, the subject of systematic reflection. In my field of research, cognitive neuroscience, research is not naturally organised around one discipline or one level of explanation. For example, when I try to understand consciousness or other mental phenomena, I continuously have to move between descriptions of subjective experience, cognitive functions, behaviour, neural processes, and physiological mechanisms. Each level has its own concepts, methods, and criteria for evidence, yet none of them alone can answer the questions that interest me. Scientific work therefore consists of navigating between and attempting to integrate different perspectives rather than operating within one pre-defined professional territory.

Different ways to attack problems

I would argue that a great deal of research operates in this way, with multiple perspectives and levels of description present simultaneously. This naturally raises the question of why teaching does not better mirror the same process of navigating between and integrating different perspectives.

It is the research question that should determine which concepts, methods and theories are relevant – not the other way around.

The traditional educational model is largely based on disciplines. Students may, for example, learn psychology, physiology, statistics or philosophy separately, while opportunities to integrate these perspectives in addressing real research questions typically arise only at a later stage. Yet the integration of different perspectives, and the questioning of what we think we know, is rarely something that emerges only at the end of a research project. It is there from the very beginning. It is the research question that should determine which concepts, methods and theories are relevant – not the other way around.

For example: What does it mean to explain a phenomenon? How does a concept become something that can be studied empirically? How are operationalisation, observation, interpretation and theory related? When does an empirical result constitute evidence for a particular claim? And how is it possible that two researchers can work with the same data and yet reach different conclusions?

The disciplines do not disappear in this model, of course. But they can be introduced as different ways of attacking problems – as historically developed collections of concepts, theories, methods and tools – rather than as isolated areas of knowledge that must first be acquired and later connected.

Mistakes, compromises and uncertainty 

In many university degree programmes, students primarily encounter the products of research: the theories, models, and published results. Far less often do they encounter the process that led to these results. The methodological compromises, the failed experiments, the analyses that didn't work, the competing interpretations, and the uncertainty that is an inevitable part of any real research process.

But it is precisely these elements that show what science is. Science is defined not by the absence of uncertainty, but by a systematic, critical and, as far as possible, transparent engagement with uncertainty. Therefore, understanding research does not only involve knowing its conclusions. It also involves understanding the argumentation, assumptions and choices that make the conclusions possible – and thus also understanding when other conclusions could have been possible.

Vulnerable to being misled

If we focus solely on what “the research shows” without understanding how the research arrived at those conclusions, we paradoxically risk making ourselves more vulnerable to being misled. This can arise unintentionally when certain assumptions or traditions are taken for granted within a field of research. But it can also be deliberate and systematic, as we see in a public sphere where isolated research findings, statistics and seemingly authoritative claims can be used to support very different narratives. 

How do we know? 

The growing use of artificial intelligence is increasingly recognised as a new challenge for university education. That is not the starting point for the reflections set out above, but it does reinforce my argument. When information, explanations, summaries, and arguments can be generated almost instantly, the ability to reproduce existing knowledge gradually becomes less crucial. Instead, it is becoming increasingly important to be able to assess and understand how a claim has come about, the assumptions on which it rests, the evidence that supports it, the alternative interpretations that exist, and the limits of its validity. 

We are constantly confronted with claims that we cannot possibly verify in detail ourselves, yet must nevertheless take a position on. And this need extends far beyond research. Clinicians, engineers, psychologists, teachers, journalists, and policymakers all have to navigate a society characterised by explosive knowledge production, complex technologies, competing expert opinions, and increasingly sophisticated algorithms. 

Perhaps our most important task is to help people understand how knowledge is created.

Here, I see a potential role for the university that extends beyond producing research and educating specialists. Perhaps the university's most important teaching task will no longer be to convey the latest knowledge. Perhaps our most important task is to help people understand how knowledge is created.

This does not mean that existing knowledge becomes less important, or that every established conclusion must be constantly questioned. On the contrary. The point is that scientific knowledge deserves its status precisely because it is the result of specific processes of argumentation, investigation, criticism and revision. At the same time, the strength of science lies in the fact that no conclusion is exempt from the question of how we know it, ensuring that the process by which knowledge is produced remains transparent.

This text is machine translated and post-edited by Mie Skov Jeppesen.