Solving problems is a vital part of STEM Education strategy. It’s better to see problems as opportunities rather than issues. This gives your kids a chance to apply critical thinking to find solutions. When kids engage in problem-solving in STEM field, coding for kids and robotics for kids, they would need to construct the problem space and there are several ways to do that.
A basic understanding of how to look at problems, identifying well-defined and ill-defined problems, and laying out a process to solve them is crucial for finding potential solutions.It begins with understanding the nature of the problem and then identifying problem space which is the set of potential steps they might take to solve the problem.
As far as nature of the problem is concerned, problems can be of two types.
Well-Defined and Ill-Defined Problems
The phrases well-defined and ill-defined are not judgmental; a well-defined problem is not superior to an ill-defined problem, nor is it necessarily simpler to solve. On the other hand, well- and ill-defined are descriptive phrases that merely indicate how much knowledge you are provided before you tackle the problem.
A well-defined problem is a problem scenario with all the elements listed. The issue clearly states the desired state, the initial state, the movements, and the circumstances under which each move should be used. Such a challenge is easily solved by formulating a series of legal actions to change the problem state into the desired outcome.
Tic-tac-toe is an illustration of a clearly defined problem. The initial state is a blank board, and the motions and limitations are given. The objective state is three Xs or Os in a straight line, which can be precisely specified.
An ill-defined problem is one where at least one of the problem components is not included in the problem.
For instance, what would you do if you were a psychologist and a client said he is unhappy and wants to alter his life? He is unsure what is upsetting him; all he knows is that he is not pleased. In other words, the exact nature of his problem state is unknown.
In the case of an ill-defined problem, the main task is to find the end goal or the exact problem that needs to be solved.
A starting point for constructing a problem space is to represent the problem in the mind of the problem solver. The portrayal of the situation by the problem solver and the researcher may differ significantly. Problems are typically conveyed verbally, and psychologists have demonstrated several instances of how people can understand verbal messages by adding more than what is explicitly presented.
Problem representation typically lays down the way a person approaches a problem.
When the problem solver is presented with a problem sentence, they are likely to add information to what is explicitly given in the sentence. That added information can lead to the person wrongly interpreting the problem. In addition to wrong interpretation, the problem solver may sometimes construct an inaccurate image of the problem, different from the one the problem portrays.
These mistakes prove that interpretation or comprehension processes are at work when we encounter problems.
An example of forming mental representation in the mind would be the following. Consider an equation,
5x + 15 = 0
Assume you are familiar with algebra. When you read that problem, you know that the answer will be an equation of type x =?. You start performing the processes that will result in such an equation right away; for example, you deduct 15 from both sides, and so on.
Your understanding of algebra enabled you to comprehend the problem and start the solution process even though none of that information was directly offered in the situation. Anyone unfamiliar with algebra would be perplexed as to how to continue.
To accurately represent the problem requires going beyond what one already knows. With gradual exposure to problems, the representations also change. Therefore, repeated practice is essential for kids to apply in science, technology, engineering and mathematics.
Constructing the problem Space
The solution process, equivalent to searching that space to create a path that leads to the solution, can be started once the thinker has formed the problem space based on interpreting the instructions and the context in which the problem is presented.
The problem space, which comprises all the potential linkages that the person might explore to solve the problem, and the links that the person explores, must be distinguished in this context. The person searches the problem space selectively. They do not look at every link that may have been considered. Understanding how to control a search exercise is crucial for understanding problem-solving.
Strategies for Searching Problem Spaces
If there is a small problem space, one approach to solving a problem is to search that area thoroughly or exhaustively until you find a path that leads to the answer. That is, if you simply try every possible set of actions, you will eventually find the solution. (In Missionaries and Cannibals, you might have to restart several times.)
Depending on how effectively they search, a person may search the whole problem space before finding a solution in such situations.
However, in many problems, the problem space is too large for a single person to conduct an exhaustive search. One would need external assistance to keep track of all possible solutions.
Heuristics, general rules of thumb that help you narrow down a problem space, must be used when a problem space is too big to be exhaustively searched. Heuristic approaches may result in the search space being substantially smaller than the overall problem space since only a tiny percentage of the problem space is explored.
Knowing these techniques and strategies would help kids in their STEM learning environment.
One popular heuristic strategy to problem solve is hill climbing. If you decide to continue your ascent, you might employ the following straightforward tactic: When faced with a decision, use your sense of direction to explore the numerous options and choose the one that leads upward. You can be confident that you are, at the very least, heading in the right direction.
Working backwards from the aim to the beginning state is an alternative heuristic approach. This approach can be beneficial since it can reduce the number of potential moves that must be considered at any given time.
A different heuristic strategy compares the current state with the desired state and looks for discrepancies between the two. The next step is to look for an operator to help eliminate the most significant disparities. This approach might entail segmenting a more major problem into smaller subproblems, each of which would need to be resolved to solve the more substantial problem. It’s also known as means-end analysis.
Planning is a different heuristic that involves seeing a solution in one’s head to predict the results of a particular move or series of movements and ascertain if they should be executed.
Finally, it is crucial to remember that some problems have particular rules or algorithms that, if followed correctly, will ensure that a solution will be found. The arithmetic rules are an illustration of a set of algorithms.
The information provided in the problem is all that the heuristic methods use up to build a method of solution. They are referred to be “weak approaches to problem-solving.”
Heuristic methods are general in applicability, but precisely because of that broadness, they do not offer much detailed information helpful in solving any given situation. Due to how such issues are constructed, the person can only bring limited or no expertise to bear on them.
Although these methods may be weak, they can aid in creative thinking. Strategies like working backwards enable us to shrink the problem space and concentrate on specific pieces of evidence while overlooking others.
Heuristic methods illustrated above have essential roles in creative thinking in science. Those techniques comprise regular thinking like organising reasoning, accessing the past, and planning. Heuristic problem-solving techniques hardly ever incorporate top-down or concept-driven processes.
Nevertheless, it is possible that some significant creative developments, at least in part, resulted from employing the techniques mentioned above. Practising these can help your kids in robotics classes for kids and coding lessons.