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Adaptive reasoning also includes reasoning based on pattern, analogy or metaphor." [1] "Capacity for logical thought, reflection, explanation and justification." [2] "The ability of an agent to intelligently adapt its behavior, both short-term and long-term in response to the changing needs of its problem-solving situation" [3]
Cased based reasoning is the most powerful strategy, and that used most commonly. However, the strategy won't work independently with truly novel problems, or where deeper understanding of whatever is taking place is sought. An alternative approach to problem solving is the topographic strategy which falls into the category of deep reasoning.
The iteration of such strategies over the course of solving a problem is the "problem-solving cycle". [ 30 ] Common steps in this cycle include recognizing the problem, defining it, developing a strategy to fix it, organizing knowledge and resources available, monitoring progress, and evaluating the effectiveness of the solution.
As such, this area has been found to be associated with verbal and design fluency, ability to maintain and shift set, planning, response inhibition, anticipation of conflict stimuli, [13] working memory, organisational skills, reasoning, problem-solving, and abstract thinking. [6] [14]
Higher-order thinking, also known as higher order thinking skills (HOTS), [1] is a concept applied in relation to education reform and based on learning taxonomies (such as American psychologist Benjamin Bloom's taxonomy). The idea is that some types of learning require more cognitive processing than others, but also have more generalized benefits.
How to Solve It suggests the following steps when solving a mathematical problem: . First, you have to understand the problem. [2]After understanding, make a plan. [3]Carry out the plan.
Some would refer to this as the ‘problem-solving cycle’ (Bransford & Stein, 1993). In this cycle one will recognize the problem, define the problem, develop a strategy to fix the problem, organize the knowledge of the problem cycle, figure-out the resources at the user's disposal, monitor one's progress, and evaluate the solution for accuracy.
For example, a problem-solving approach that works in one domain may be applied to a new, similar problem in a different domain. Analogical reasoning is particularly useful in scientific discovery and problem-solving tasks, as it can help generate hypotheses, create new theories, and develop innovative solutions. [31]