The Problem Solving Process

Problem solving is an intellectual process, which involves realizing, evaluating and then solving problems. Therefore, the main aim of problem solving is to conquer obstacles and uncover a solution which best determine the issue. However, the best approach for solving a problem depends widely on the distinctiveness of the situation. Creativity also plays an important role in problem solving (Frensch & Funke, 2014). Creative problem solving is not just brainstorming though people do correlate it with but rather it is a well-defined procedure, which can guide a person from defining a problem to apply solutions. With creative problem solving, a person tries to search for an inventive as well as formerly unknown solution to a problem (Baer & Kaufman, 2012). Thus, a creative solution will habitually have discrete characteristics, which involve using only accessible components or the problematic aspect, as the basis for the result.

However, there are four basic steps in solving a problem, which are first to define the problem, then producing alternatives, evaluating and opt for alternatives and lastly applying the solution (Bardach & Patashnik, 2015). In the premature stages of Problem-solving people needs to have strong observational skills. Therefore, one need to exhibit their lateral thinking and analytical abilities, which will further help them to review what, is going on and identifies the actual cause of the problem. However, finding the appropriate solution to the problem is not being easy therefore; creative thinking will assist individuals in the process of problem solving. Critical thinking is mainly utilized when the solution is implemented which helps access the result and twist the strategy  as needed to make sure that the problem is solved successfully (Cottrell, 2017).

The aim of this report is to discuss the issue in the case study provided. Following which solutions need to be provided and lastly, the appropriate models/theory/strategy in the process of problem solving will be discussed.   

Issue (s)/problem(s) of the case

The main issue in this case study is that a 19years old girl named Helen is intensely in love with a man who is 10 years elder to her. However, this man named Johnny is employed in the same college as an IT technician where Helen is a student. The problem rose when they decided to get married the following year. Helen is the eldest child in her family and her parents anticipate that she will start working after finishing her studies and will look after the family. However, Helen has some other plan.

Case Study Example

The main problem here is for Helen, she is stuck in-between her love Johnny on one side and her responsibilities for her family on the other side. Therefore, she needs to successfully reach a solution where she can balance both her love and her family. However, in order to solve this problem effectively Helen needs to follow a chain of steps. According to previous researches, Helen can follow the problem solving cycle that mainly involves build up strategies as well as systematize knowledge. Therefore, she can skip few steps or rather go through few steps multiple times until and unless the preferred solution is reached.

Solution to this problem

The solution that for Helen’s problem can be reached through the following four steps and they are as follows-

1. Identify the problem- To reach appropriate solution Helen needs to diagnose the situation first so that she can focus on her issue. These steps include flowcharts as well as cause and effect diagrams so that the problem can be well defined and the root cause can be evaluated (Savery, 2015). Thus, information, assessment of expectations towards reality as well as focus towards the roots of the problem is needed.
2. Produce alternative- In this case before selecting any one solution Helen should come up with several other solutions so that she can get the chance to compare the characteristics of her final solution. However, a standard can help Helen to analyze the various intended outcome that is suggested by the alternatives. Multiple alternatives can increase the value of the final solution (Brown & Chandrasekaran, 2014). Brainstorming can be a useful technique for generating the solution for Helen’s problem. Therefore, first alternative solutions are identified and then they are analyzed.
3. Evaluate and choose alternatives- While selecting the best alternative there are certain consideration which helps in reaching the exact solution which are –

• The alternative that has been identified will solve the problem in hand rather than generating other probable problems
• The alternatives must be accepted by all
• Accomplishment of the alternative is possible
• The alternatives must fit with the issue (Hayes, 2013). 

1. Execute solution- However, the selected solution should be implemented 

Helen’s solution can also be reached by following the problem solving cycle, which contains seven steps to reach the appropriate solution successfully (Peng & Reggia, 2012). Apart from the above four points this problem solving cycle contains other three steps which are as follows-

• Identify the problem
• Explore- Here mainly the problem is thoroughly researched and the possible solving strategies are highlighted
• Set goals- goal setting is also important for reaching appropriate goals
• Produce alternative
• Select alternative
• Implement solutions
• Evaluate- after reaching the solution one needs to evaluate the results to determine whether the possible solution to the problem is at all effective or not.

 

(Source : Borko et al., 2015).

Therefore, following these stages the solution that seems most appropriate in these problems is that as she cannot chose any one from among her love Johnny or the responsibilities of her family thus, what she can do is that she should finish her college get a Job and then get married to her love Johnny. Moreover, after her marriage she can work and help her family. This is the appropriate solution because in this way she does not have to dishearten anyone. She just needs to balance her love life and her responsibilities being the elder child to support her family. This solution seems most effective after following the seven steps of problem solving cycle. Therefore, after identifying the appropriate problem, exploring it, setting goals for where to reach, and gathering alternatives, from there a solution is selected. However, this solution has been reached after following the steps which needs to get implemented and then evaluating the desired results (Whimbey, Lochhead & Narode, 2013). 

Model/theory/strategy for the process of problem solving

Problem solving is something, which people faces daily. Problems never seem to end in anyone’s life and so the need to solve them is endless. As per the studies in cognitive psychology, there are concrete psychological steps included in problem solving which if followed properly can assist people undertake every type of problem. However, one of the significant characteristic of problem solving is forming a superior strategy. A strategy might be a properly thought one which is rigorous and a sure winner but cannot be accessible in hand.  Therefore, the core strategies, which are included in solving problems, are as follows-

Problem Solving Strategies

Algorithms- Algorithm is mainly a systematic formula, which will always manufacture an accurate solution. However, a good example of problem solving algorithm is the mathematical formula (Gandomi, Yang & Alavi, 2013). However, an algorithm assures an accurate answer, it is not always the finest approach towards solving a problem. Moreover, this strategy is not convenient for various situations as it is very much time consuming. Therefore, for instance if one is trying to discover all the possible combinations with numbers to a lock utilizing an algorithm then it would definitely take a loner time. The use of the term ‘algorithmic problem solving’ is purposely uncertain. This method of algorithms has been an essential feature of problem solving but in the ancient times the algorithm has been infrequently been the focus of attention. People must become more skillful in algorithmic problem solving because of the ever-present automation in the daily lives. Therefore, algorithms are said to be the result of the problem solving procedure and it is essential that they are made open and are cautiously studied (Rao & Patel, 2012). The technique of algorithm mainly comprise of formulating a mathematical design of what the algorithm needs to calculate and then increasing the algorithm in a way which pledge that it will meet the specification. Algorithm can further provide a number of profit and one among them be in the process of development, which includes recognition of the processes, important decision points and necessary variables, which are important in problem solving. Moreover, when using algorithm the process of decision-making becomes more rational. Therefore, the process becomes more efficient and consistent. Algorithm further serves as a mnemonic device and guides ensure that the variable or any parts of the problem are not overlooked (Mirjalili, 2016). Lastly, presenting the solution procedure as an algorithm can permit communication that is more precise.

Heuristics- The next important strategy is heuristics, which is the mental rule of thumb, which might or might not work in certain situations. However, contrasting with algorithm, heuristics does not always promise a correct solution. Therefore, using this strategy of problem solving does permit people to make simpler complex problems and decrease the total number of probable solutions to a more convenient set (Michalewicz & Fogel, 2013). Heuristics does play an essential role in both problem solving and decision-making. Heuristics are intellectual shortcuts that permit people to unravel problems as well as make judgments rapidly and competently. This strategy actually shorten the decision making time as well as allocate people to function without frequently discontinuing about their next route of action. Heuristics are supportive for many situations but at times, they can also guide towards cognitive biases. While trying to solve a problem in many cases people take the help of these rapid solutions by applying these mental shortcuts. Thought there is lot information that passes individuals every moment but the brain is only capable of registering a certain amount of them (McLeod & Adams, 2012). Therefore, analyzing all the features of every situation or decision is not possible therefore, to cope with this vast amount of information and to make the decision making process rapid the brain depends on the mental strategies to make things simpler so that this process does not become time consuming by analyzing every aspect of the details. Two of the most common heuristics are the availability heuristics, whichincludes the decision-making based on how effortless it is to bring something to mind (Muoni, 2012). Thus, when one is trying to make a decision that person at once remembers a number of related examples. Another one is the representativeness heuristics that mainly includes the decision-making by evaluating the current situation to the most representative intellectual prototype. However, Heuristics can also introduce errors (Heath et al., 2013).  

Algorithms

Trial-and-Error- This strategy is the move toward dealing with trying a number of diverse solutions and ruling out the ones, which do not work. However, impending this strategy as a first method is an endeavor to solve any problem can be very much time taking. Therefore, the best utility of this strategy is as a follow up to decipher the appropriate solution after narrowing down the probable number of solutions utilizing other techniques (Osiurak et al., 2013). For example if this strategy is explained then it would be that if someone is trying to open a lock then try to pierce every possible arrangement into the lock for the trial and error. As an alternative if anyone constricts the possible combinations to lesser numbers then it would have been much easier to solve the particular problem in less time. This problem solving strategy is more effective while dealing with complex problems. Particularly it is good for problems where one has numerous chances to get the exact solution (Felin & Zenger, 2014). Therefore, this strategy is not fir for those problems, which do not have multiple probabilities to find a way out to the problems. Trial and error strategy is also a grand way to expand knowledge. Therefore, when an individual uses a trial and error strategy, he tries to method if it is at all a good solution. If they find out that this solution is not appropriate then they try another option. However, if this tried solution worked at once then they have obtained the accurate solution (Greiff, Holt & Funke, 2013).There are also some situations when there are many options and one cannot try every option to succeed so in the cases they use the options, which has the best probable opportunity to succeed. Therefore, if this option does not work out then they can try the next best possible option, which they think is suitable.

Insight- This strategy is the one, which take place suddenly. According to the previous researches, which imply that, insight can take place if one dealt with similar kind of problems in the long-ago. For example, if one has solved a problem in his or her past then it will be easier to solve a similar kind of problem at present. Moreover, it is not always essential that a mental process is relatable with the past problems (Ostafin & Kassman, 2012). In maximum cases, it has been observed that mental processes guiding to insight occur outside one’s consciousness. In some problems the solutions seems to have arrived out of nowhere. However, there are some problems, which are the outcome of elongated thought process. 

Heuristics

However, apart from these there are several other models and strategies in problem solving, which are as follows-

• Cause and effect- This strategy is used when there are too many problems and all of them are competing among each other for attention.
• Sensitivity analysis- This strategy is however, used to identify the quantity of vagueness or error in evaluating the reference or conclusions (Bardach & Patashnik, 2015).
• Risk analysis- This utilized to identify as well as evaluate the aspects, which endanger the success of a planned solution or venture.
• Brainstorming- This is a creative technique of problem solving which is engaged with formalizing and structuring. Through risk and sensitivity analysis, one can get assistance to spot the issues and then help to center on decreasing the risk or sensitivity.
• DMAIC- This is a process improvement tool that mainly helps in first finding the source of the problem and then discovering the methodology for solving the problem (De Mast & Lokkerbol, 2012). However, for establishing quality improvement processes this tool can used for problem solving in majority cases.

To conclude this report, it can be said that according to the case study provided the main problem faced by Helen who is a 19years old college student is that she loved a man who is 10 years elder to her. They decided to get married but the problem here is that Helen’s family does not approve this relationship because they want her to take the responsibility of the family after completing her studies. Therefore, the recommended solution is that Helen should balance between love and responsibilities. Thus, she should complete her studies, get a job and then get married to her love named Johnny. The model that has helped reaching this solution is the problem solving cycle that mainly consisting of seven steps. Lastly, the strategies highlighted for problem solving are algorithm, heuristics, trial and error and insight. Moreover, there are also some other models and strategies that can assist individuals in problem solving and they are cause and effect, risk analysis, sensitivity analysis, brainstorming and DMAIC. 

References 

Baer, J., & Kaufman, J. C. (2012). Creative Problem Solving (CPS). In Being Creative Inside and Outside the Classroom(pp. 93-127). SensePublishers, Rotterdam.

Bardach, E., & Patashnik, E. M. (2015). A practical guide for policy analysis: The eightfold path to more effective problem solving. CQ press.

Borko, H., Jacobs, J., Koellner, K., & Swackhamer, L. E. (2015). Mathematics professional development: Improving teaching using the problem-solving cycle and leadership preparation models. Teachers College Press.

Brown, D. C., & Chandrasekaran, B. (2014). Design problem solving: knowledge structures and control strategies. Morgan Kaufmann.

Cottrell, S. (2017). Critical thinking skills. Macmillan Education.

De Mast, J., & Lokkerbol, J. (2012). An analysis of the Six Sigma DMAIC method from the perspective of problem solving. International Journal of Production Economics, 139(2), 604-614.

Felin, T., & Zenger, T. R. (2014). Closed or open innovation? Problem solving and the governance choice. Research Policy, 43(5), 914-925.

Frensch, P. A., & Funke, J. (Eds.). (2014). Complex problem solving: The European perspective. Psychology Press.

Gandomi, A. H., Yang, X. S., & Alavi, A. H. (2013). Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems. Engineering with computers, 29(1), 17-35.

Greiff, S., Holt, D., & Funke, J. (2013). Perspectives on problem solving in cognitive research and educational assessment: analytical, interactive, and collaborative problem solving. Journal of Problem Solving (The), 5, 71-91.

Hayes, J. R. (2013). The complete problem solver. Routledge.

Heath, L., Tindale, R. S., Edwards, J., Posavac, E. J., Bryant, F. B., Henderson-King, E., … & Myers, J. (Eds.). (2013). Applications of heuristics and biases to social issues (Vol. 3). Springer Science & Business Media.

McLeod, D. B., & Adams, V. M. (Eds.). (2012). Affect and mathematical problem solving: A new perspective. Springer Science & Business Media.

Michalewicz, Z., & Fogel, D. B. (2013). How to solve it: modern heuristics. Springer Science & Business Media.

Mirjalili, S. (2016). Dragonfly algorithm: a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems. Neural Computing and Applications, 27(4), 1053-1073.

Muoni, T. (2012). Decision-making, intuition, and the midwife: understanding heuristics. British Journal of Midwifery, 20(1), 52-56.

Osiurak, F., Jarry, C., Lesourd, M., Baumard, J., & Le Gall, D. (2013). Mechanical problem-solving strategies in left-brain damaged patients and apraxia of tool use. Neuropsychologia, 51(10), 1964-1972.

Ostafin, B. D., & Kassman, K. T. (2012). Stepping out of history: Mindfulness improves insight problem solving. Consciousness and cognition, 21(2), 1031-1036.

Peng, Y., & Reggia, J. A. (2012). Abductive inference models for diagnostic problem-solving. Springer Science & Business Media.

Rao, R., & Patel, V. (2012). An elitist teaching-learning-based optimization algorithm for solving complex constrained optimization problems. International Journal of Industrial Engineering Computations, 3(4), 535-560.

Savery, J. R. (2015). Overview of problem-based learning: Definitions and distinctions. Essential readings in problem-based learning: Exploring and extending the legacy of Howard S. Barrows, 9, 5-15.

Whimbey, A., Lochhead, J., & Narode, R. (2013). Problem solving & comprehension. Routledge.