Karolinska Institutet prize awarded to innovative clinical educational researcher
”Professor Norman is awarded the prize for his highly original and innovative research within the field of medical education,” says Professor Peter Aspelin, chair of the Karolinska Institutet prize committee. ”His research has had a significant impact on our understanding of the practice of medicine, as well as our knowledge of complex issues such as pattern recognition, clinical reasoning and clinical problem solving.”
Professor Norman’s primary research is in the area of expert diagnostic reasoning – how clinicians arrive at a diagnosis. His research has revealed that experts use two kinds of knowledge to come to a diagnosis – one is the formal analytical knowledge of signs and symptoms, physiologic mechanisms, and another is experiential knowledge based on the hundreds or thousands of patients they have encountered. Further, experimental studies have shown that these individual experiences remain in memory and are accessible to solve new problems, although the clinician is likely unaware of this retrieval process.
Following from this research is an interest in various aspects of how medical students learn. Professor Norman has contributed to the theoretical foundation of problem-based learning. He has also conducted experimental research in many areas related to education, including anatomy learning from computers, use of simulations in clinical learning, and the role of basic science in medical education. He is currently exploring the use of high ?delity simulation in clinical learning.
”His research is characterised by theoretical rigour and methodical skill. He has been able to contribute considerably to developing the subject area of quantitative analysis. In this subject area, Professor Norman has made good use of his solid background as a physicist and has been able to provide the readers with a clear explanation of statistical methods and how they are used in research,” Aspelin adds.
Professor Norman’s research has showed that transfer, using a previously learned concept to solve a new, apparently different problem, is difficult. Students are typically only able to access a previously learned concept to solve new problems 10% to 30% of the time. However, having students work through parallel, apparently different, problems can have positive effects. Active learning with multiple examples can have large effects on a student's ability to apply concepts to solve new problems.
Professor Norman – who in his own words ”stumbled into the field of medical education” – has demonstrated that conventional approaches to education can sometimes be more effective than cutting-edge technology. He claims that researchers need to understand more about the strengths and limitations of the way people think, so the advantages of technology can be used better. For example, his research has found that attempting to learn anatomy from dynamic virtual reality can actually impede learning if a person has a low spatial ability.
”Sometimes it is important to look at what computers can do that a book can’t, but we must also take into account how our brains process information,” says Geoffrey Norman. ”Computers can help us gain 3D views of the human anatomy, for example, but this does not always produce the best learning results. Our brains find it easier to process information where only two views, such as the front and the back of an object, are displayed.”
”The challenge,” says Professor Norman, ”is to develop new ways of delivering knowledge, based on technology, but derived from an understanding of the way we think and learn.”
”Delivering new information is not enough if it isn't put into practice. We need to understand the psychology that guides the way people assimilate and apply new information,” he says.
Professor Norman’s contributions have been of enormous value for medical practice and subject areas such as knowledge measuring, clinical skills, visual perception, and the development of curricula for health and nursing training programmes all over the world.
Reflecting on his work, Professor Norman says: ”I think my contribution to the world of medical education has been to question everything in order to find interesting things. I never had a great desire to change the world; I just figured that if I find enough interesting or important points during my research, something good will come out of it in the end. If something is interesting enough, the impact will follow. In my case, I am part of a small number of people who have helped to change the world of clinical reasoning through my research.”
Professor Norman played a central role in developing the new ’concept-based’ curriculum at McMaster University in Canada. The curriculum is an evolution of McMaster’s emphasis on problem-based learning (PBL), which has been adopted by over 100 medical schools worldwide. Concept-based learning attempts to combine the best of PBL, with its emphasis on active learning around problems, and traditional learning, which highlight the importance of systematic scientific knowledge of how the body works.
Norman is also a popular lecturer at universities across the world, and a mentor to graduate and undergraduate students. Numerous junior researchers – including the likes of Kevin Eva – working with Professor Norman have since developed into prominent scholars in their own right.
Commenting on his prize win, Professor Norman says: ”It’s an astonishing recognition. The prize, and Karolinska Institutet in particular, are so well known in my field of work so it’s a feather in the cap for both myself personally and for McMaster University. And although I plan to work for another few years yet, this prize is a nice culmination to a long career.”
Media Contact
All latest news from the category: Awards Funding
Newest articles
First-of-its-kind study uses remote sensing to monitor plastic debris in rivers and lakes
Remote sensing creates a cost-effective solution to monitoring plastic pollution. A first-of-its-kind study from researchers at the University of Minnesota Twin Cities shows how remote sensing can help monitor and…
Laser-based artificial neuron mimics nerve cell functions at lightning speed
With a processing speed a billion times faster than nature, chip-based laser neuron could help advance AI tasks such as pattern recognition and sequence prediction. Researchers have developed a laser-based…
Optimising the processing of plastic waste
Just one look in the yellow bin reveals a colourful jumble of different types of plastic. However, the purer and more uniform plastic waste is, the easier it is to…