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There are many different approaches to problem-solving that have been established in psychology. Firstly, there’s the Thorndike paradigm, which involves blind trial and error1. More purposeful approaches are the Gestalt approach, and the cognitive approach.

 The Gestalt approach involves solving problems as a whole2. You see the problem, you see what you have, and then you try to see how everything fits together. If the question is routine, it’s very easy to figure it out. If it isn’t, well, sometimes you gain insight, but sometimes you come up with an idea based on what you’ve encountered before and you get so stuck on trying to make the pieces fit into that idea that you don’t realise there may be a simpler pathway. In a test like the UMAT, you don’t have the time to sit there and hope for inspiration.

The cognitive approach is like programming a computer. There are many different pathways for solving a problem, and instead of just sitting there waiting for inspiration, you solve the problem bit by bit, taking the steps that lead you towards your answer3. This is very similar to trial and error, but using something called ‘heuristics’, you form an educated guess as to where to start.

There aren’t any hard and fast rules you can memorise to get a good score on UMAT. There are no simple algorithms to follow routinely like, “compare the exclamation marks to the question marks to score assertiveness”. Problems that can be solved like that could be answered by computers – and UMAT isn’t a test for computers.

UMAT is for humans. But what separates humans from computers? Computers are very good at storing data and making quick calculations, but not so good at complex problem solving like in UMAT.

The answer is: experience and learning. To create a human-like computer, you have to create a computer that learns, and then show it many, many examples so it can ‘instinctively’ find the patterns. In anatomy, it’s not enough for me to memorise the locations of muscles, vessels and nerves. I have to locate them on many specimens so that, given a new specimen, I can work out the most probable answer in a test. In UMAT, you need to practice with many different examples of questions to be able to instinctively answer quickly and correctly.

That’s what MedEntry is. Not a textbook to memorise answers from, or a rulebook, but a guide which, along with providing helpful ways to consider questions, will provide you with the many different examples you need.


1 Thorndike, E. (1911) Animal intelligence: experimental studies. New York: Macmillan.

2 Sternberg, R. (2011) Cognitive Psychology, sixth edition (pp. 454 – 459). Belmont: Wadsworth.

3 Newell, A., & Simon, H. (1972) Human Problem Solving. New Jersey: Prentice Hall.

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