Interplay of Problem-Soving

Humans solve problems using trial and error, understanding principles, reasoning, and critical or creative thinking.

Problem-solving involves navigating through potential actions to achieve a goal, utilizing both divergent and convergent thinking. Divergent thinking helps generate various solutions, while convergent thinking narrows down possibilities to find the best answer. 

Approaches to solving problems range from algorithms, which guarantee a solution through a strict procedure, to heuristics, which are more intuitive and speculative. Heuristics may not always work, but can be quicker than algorithms.

Algorithms & Heuristics in Problem Solving: A problem-solving algorithm is a procedure that guarantees a solution if followed strictly. A problem-solving heuristic is an informal, intuitive, speculative procedure that leads to a solution in some cases but not in others.

Expertise in Problem Solving: Experts and novices approach problem-solving differently. Experts possess larger, more interconnected schemata and spend more time understanding the problem, while novices focus more on executing solutions. Experts often use a working-forward strategy, whereas novices use a working-backward strategy and monitor their problem-solving more carefully.

Thinking is not a single process but includes problem-solving and reasoning, as well as judgment and decision-making. Humans solve problems using trial and error, understanding principles, reasoning, and critical or creative thinking. Problem-solving skills can vary from person to person. Therefore, it's always important to be authentic and people-centric, and develop your own practices to improve problem-solving competency. 

Posted in: Digital Fit,Problem Solving