”Change the way you look at things and the
things you look at change.” (W. Dyer)
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This page contains project related data.
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The general idea of Problem Solving is to provide solutions to specified problems. This is a very broad definition and as this field has been widely researched through many disciplines (most notably psychology, medicine, engineering, computer science, artificial intelligence and mathematics) finer details of Problem Solving have been discovered. There is a wide area of problems, some of which are well- or ill- defined, they differ in complexity, transparency, dynamics and multiplicity of goals [1]. The process in which one tackles a given problem (problem-solving process) can differ a lot as well, depending on the strategy use and optimization [2]. These are one of the most researched aspects of Problem Solving. Unfortunately, one of the most important aspects is often considered intuitive and hereby very neglected: Shape of the problem and problem-solving process.
Given a complete problem description, the problem solving process is far from uniquely determined. The subject’s internal representation of the problem (partially depending on prior knowledge and problem’s description) then fully shapes the problem (and solution) spaces and consequently the problem-solving process as well. This problem and problem-solving-process’ general shape determines how problem-solving will occur, which optimizations are feasible and which strategies can be applied. Herbert A. Simon and his associates Kotovsky and Fallside (1988), argue that the effectiveness of problem-solving process lies in the mental representation of the problem, which is strongly determined by problem description information and prior knowledge. It was shown that, although initial mental representation may not always be the best and can even block production of a successful solution, subjects are often unable to change it and avoid the knowledge transfer (effect of solving a task on solving subsequent tasks).
It is not clear if all problems are able to partake in multiple mental representations, as at the moment we do not know what properties enable a specific problem to do so. But in case at least two mental representations of a problem have been identified, it is easy to imagine the differences they cause among the problem-solving processes; the time and resource consumption may wary as well as solution’s quality or optimality (presuming the solution is achieved in both cases). Unfortunately, even if a problem has multiple mental representations, it can be very difficult to identify them.
This project has great potential to provide insight on the world of mental representations. Each representation has its own quirks, side effects, solution features and other features, that are yet to be discovered, and to understand them can provide a crucial help in selecting the optimal one for each problem. The general aim of our study is to examine to what extend people tend to transfer previous mental representation into subsequent isomorphic problem solving tasks. More specifically, we will examine the effect of prior learned knowledge (experiment 1) and also the effect of problem description manipulation (experiment 2) on creation and transfer of mental representation. Using a matchsticks problem solving tasks in the first experiment we will investigate whether creating a mental representation and learning effective strategies leads to a negative (unwanted) transfer in an isomorphic task, so that other representations and strategies are overlooked. The second experiment will examine the effect of transfer in a more specific field of programming. Here, we will investigate whether manipulating the structure of information about the problem task induces creation of a certain mental representation and choosing of a particular strategy. We will also investigate whether the transfer of strategy used also occurs in neutrally introduced isomorphic task that does not induce creation of a particular mental representation. Hopefully, our research will provide new findings about how prior knowledge and information structure affect the occurrence of transfer, which could create some base-ground for further interdisciplinary research in psychology and computer science.
Less relevant references for this page:
[1] Dietrich Dörner and A Wearing. Complex problem solving: Toward a (computer-simulated) theory. Complex problem solving: The European perspective, pages 65–99, 1995.
[2] Yingxu Wang and Vincent Chiew. On the cognitive process of human problem solving. Cognitive Systems Research, 11(1):81–92, 2010.