Research to date on problem solving differences between novices and experts Essay Example
Research to date on problem solving differences between novices and experts Essay Example

Research to date on problem solving differences between novices and experts Essay Example

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  • Pages: 6 (1468 words)
  • Published: December 23, 2017
  • Type: Research Paper
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Green and Gilhoody (1992) summarised results of expertise research with a number of characteristics including experts remembering better, experts employing different strategies and experts becoming expert through extensive practice. Such results have significance in education where one educationalist view is to create experts.Studying expertise and differences in performance between novices and experts has offered information on the cognitive processes involved in problem solving. In determining how expertise is acquired from early learning experiences has helped Psychologists to focus on learning processes. Studies have also looked at how knowledge and skills develop from early declarative knowledge into actions where procedural knowledge must be established. Developing chess expertise from novice to grand-master for example can take many years of dedication and practice, but also requires very good strategic processing skills.<



Computer specialised chess games have been developed to mimic or offer a worthwhile chess opponent, but the success of these 'opponents' are not built upon practice, but rather upon knowledge and experience by the author who builds up a database of thousands of possible moves and permutations. The many possible moves and permutations are available to the computer's memory just like they are to the human memory. Studies by Dennis H Holding (? ) looked at how interference caused problems for chess players in terms of their success at planning or making their next move.Indeed experts had problems with their next moves when asked to count backwards between moves. Holding believed that working memory was interfered with and caused problems interfacing with the evaluation and strategic and tactical knowledge in long term memory. Such findings help highlight the complex workings of the human mind, including cognitive processes during

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thinking, planning and interference stages.

Problem solving studies of experts and novices have highlighted a difference in their respective approaches.There are also changes in how experts go about solving problems, which can be classified as tactical learning and strategic learning. Chi et al (1981) found that novices sorted problems on superficial features, whereas experts sorted according to Newton's laws - perhaps because of their deeper understanding of the subject Other evidence though by Charness (1976) indicated that experts could store more information in long term memory which in turn aided their capacity for solving problems.Other studies (Pirolli 1985; Ross, 1984) have gathered evidence showing that early problem solving is strongly influenced by analogy to similar examples where successful solutions have already been forthcoming. For successful solving of the 'Tower of Hanoi' puzzle one first has to build an understanding of the challenge and then formulate tactics for finding a solution.

The mind and memory can be used to picture moves before committing a solution to paper. Whether one is a novice or expert would make a difference in such an exercise, certainly in terms of the time taken to produce a solution.Such a puzzle offers a good opportunity for subgoaling or breaking down the actions or moves into smaller subgoals or tasks. Means-end analysis is another method used in problem solving whereby the end result and blocking objects are focused on. Another point to bear in mind is variability, where the same individual produces different solutions, or different solutions vary across replications of the same problem.

Certainly in more complex problem solving, variability is more likely as the possibilities of numerous solutions increases together with

the reduced likelihood of remembering a solution.In terms of 'practice makes perfect' certainly practice helps provide experience and knowledge and even confidence, but with certain set tasks, novices may struggle and indeed not have the required skillset or aptitude. Early behavioral research on problem solving by Thorndike (1898) looked at placing hungry cats in closed cages with their food outside the cages. The goal of the cat was to locate a pole inside the cage, which thus caused the cage to open and therefore allow the cat to reach the food.Thorndike was not impressed by the performance of the cats and referred to their success rates as trial-and-error learning. However a group of German psychologists known as Gestaltists argued that animal problem solving was more than trial and error, and for them thinking and problem solving were matters of 'seeing' things in the right way, where discovery of a solution was an insight.

Gestaltists looked at the distinction between productive and reproductive problem solving, where productive involves a novel restructuring of the problem and reproductive involves the re-use of previous experiences.The Gestaltists believing that productive was more complex and a higher level form of problem solving - and that several species of animals were capable of it. However the Gestaltist approach has attracted criticism in terms of clarification and the difficulty sometimes in replication of their findings. Studies and research in domains such as chess and computer programming indicate high organised domain specific knowledge is required for skilled performance.

Experts hold a store of solutions and operations for applying, whereas novices simply would not have such a wealth of strategies and knowledge.Novices and experts approach

problem solving differently, with experts spending time reformulating problems and focusing on underlying principles. Experts also formulate different strategies and tend to work forward towards the goal while novices tend to work backwards or use means-end analysis. It is difficult to say whether this explains the term 'practice makes perfect' or whether it just emphasises that tactics and short term practice are no substitute for knowledge and experience.Gobet & Simon (1996) put forward the template theory whereby they believed that outstanding chess players owe much of their success to their knowledge about specific board positions and relevant knowledge stored in memory, which are semantic structures in the form of templates.

Many other studies have looked at chess expertise including chess-playing computers with varying results and theories but all highlighting the different capacities and strategies between experts and novices.A theory of learning called ACT* has been developed by John Anderson, and attempts to account for cognitive functioning in problem solving. The theory attempts to explain learning and altering long-term production memory through different stages until the necessary processes are refined to aid strengthening. Anderson also believed that the strength of the application of production rules increased through further use, but rules applied infrequently lose strength.

This theory therefore supports the idea that practice makes perfect. Investigations into students learning methods have highlighted that most students only learn how to solve domain-related problems efficiently by devoting many hours to such problem solving, and it is often only a small percentage of students who benefit from such practice. Fortunately though such research has helped identify useful strategies applied by experts, which has now turned Psychologists attention towards teaching the

strategies to novices.The top-down processing used by experts is seen as an aid and enhances their perception of relationships and principles involved to then work towards a solution. Novices, in contrast, lack perspective and work bottom-up, starting with gathering enough data to gain an overview. Indeed studies by Paul E.

Johnson et al (University of Minnesota) summarized that experts, unlike novices, have their knowledge organized and arranged in schemas, which involve special shortcuts based on their experience.A persons perception of a problem may also differ from person to person. Studies by Rock (1957) concluded that perception also calls for problem solving of one sort or another, showing that we seek a hypothesis to account for what we see, and then weigh that hypothesis against other possibilities to make sense of what we see and solve the problem. Experts are able to rely on memorised solutions to many problems in their domain, while novices do not have a very large store of answers to problems presented to them.By the same token though practice in one domain such as chess would help enable a novice to build up expertise over time, but in other more complex domains such as physics or geometry for example, practice would not necessary help as much as aptitude and skillset which are far more likely to produce greater problem-solving results. Many studies have attempted to understand how complex problem-solving skills are learned.

Ideas and theories from both learning and problem-solving theories have been combined to understand structures and performance, and to help determine how problem-solving skill acquisition and strengthening occurs.One interesting point to consider is just how does an expert become such?

Skill acquisition in certain domains requires more than just practice and is perhaps more to do with an innate ability. Learning and understanding both play a major part in acquiring relevant problem-solving skills, as does creativity. In terms of building upon current understanding of learning and problem solving, it is believed that improved models of memory organization and retrieval processes would aid further studies. Evidence gathered and presented is aimed at convincing the reader that there is more to problem solving than simply 'practice makes perfect'.

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