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

able to store more information in their long term memory and utilize analogies from similar examples to solve problems successfully. In order to succeed in solving puzzles, such as the 'Tower of Hanoi', it is important to first understand the challenge and then develop tactics for finding a resolution.

One can use their mind and memory to visualize moves before writing down a solution, regardless of their level of expertise. This exercise may take longer for novices. If one chooses to solve a puzzle in this manner, it presents an opportunity to break down moves into smaller goals. Another problem-solving method is means-end analysis, which focuses on the end result and potential obstacles. It is important to note that individuals may produce different solutions and even different solutions may arise when solving the same problem more than once.

The likelihood of variability increases in complex problem solving due to the numerous possibilities of solutions and the reduced chance of remembering a solution. While practice can provide experience, knowledge, and confidence, novices may struggle with certain tasks if they lack the required skillset or aptitude. Thorndike's early behavioral research on problem solving involved hungry cats in closed cages with their food outside. The goal was for the cat to locate a pole inside the cage to open the door and reach the food. Thorndike referred to the cats' success rates as trial-and-error learning, but Gestaltists argued that animal problem solving involved more than that. They believed that thinking and problem solving required 'seeing' things in the right way, leading to an insight for discovering a solution.

According to the Gestaltists, problem solving can be categorized into two

types: productive and reproductive. Productive problem solving entails original restructuring of the issue, while reproductive involves utilizing past experiences. The Gestaltists deemed productive problem solving to be a more challenging and advanced process, which multiple animal species could achieve. Nevertheless, the Gestaltist methodology has faced objections due to ambiguousness and the problems encountered while reproducing their results. Results from investigations on topics such as chess and computer programming demonstrate the necessity of highly organized specific knowledge in domain for skilled performance.

According to Gobet & Simon (1996), experts possess a vast collection of solutions and techniques for application, while novices lack such a considerable amount of strategies and understanding. Problem-solving differs between experts and novices, as experts take the time to reformulate problems and focus on fundamental principles. They also develop and utilize varied strategies, working towards the goal, whereas novices often resort to working backward or through means-end analysis. The popular phrase 'practice makes perfect' may be explained by these factors, emphasizing that short-term practice without knowledge and experience does not suffice. Gobet & Simon (1996) suggest that exceptional chess players rely on stored semantic structures in the form of templates, with relevant knowledge about specific board positions, contributing significantly to their success.

Numerous studies have examined chess expertise, including chess-playing computers. These studies produce varying results and theories, all of which emphasize the distinctive abilities and strategies between experts and novices. John Anderson developed a theory of learning called ACT*, which aims to elucidate cognitive functioning in problem solving. The theory explains how long-term production memory is learned and modified through various stages until the necessary processes are refined to aid strengthening. Anderson also

posits that frequently applied production rules become stronger, while rules infrequently employed lose strength.

This theory emphasizes the importance of practice in achieving proficiency. Studies examining how students learn have shown that effective problem-solving skills are typically acquired through extensive practice, with only a small minority of students benefiting from such training. Fortunately, expert strategies have been identified, prompting psychologists to focus on teaching these strategies to novices. Experts employ top-down processing to perceive relationships and principles necessary to solve problems. In contrast, novices use a bottom-up approach, gathering data to form a comprehensive view. Research by Paul E. has confirmed this contrast.

Johnson et al (University of Minnesota) explained that experts possess schemas, which are organized systems of knowledge shortcuts based on their experience, unlike novices. Perception also plays a crucial role in problem-solving, as a person's perception of a problem may differ from another person's. Rock's (1957) studies showed that individuals seek a hypothesis to explain what they see and weigh it against other possibilities to solve the problem. Experts can rely on memorized solutions within their domain, while novices lack a large store of problem-solving answers. However, practice in certain domains such as chess can help novices build expertise over time, whereas aptitude and skillset are more effective for complex domains like physics or geometry. Many studies aim to comprehend the learning process of complex problem-solving skills.

By combining ideas and theories from learning and problem-solving, a deeper understanding of structures and performance can be achieved. The acquisition and strengthening of problem-solving skills have been closely examined to determine how experts develop their abilities. It has been suggested that skill acquisition may depend on

an innate ability as well as practice. Consequently, both learning and understanding are crucial in acquiring relevant problem-solving skills, alongside creativity. To advance the current understanding of learning and problem solving, there needs to be an improvement in models of memory organization and retrieval processes. Overall, the presented evidence aims to convince readers that there is more to problem solving than just practice.