Algorithmic problem solving is based on the formulation and solution of problems and solutions that are involved and principle techniques that are used. It involves a “ set” of specific steps to solve a particular problem(Natsopoulos, Grouios, Bostantzopoulou, Mentenopoulos, Katsrou & Logothetis,1993)..Heuristics is often used more in everyday life; it gives people some guidance on how to accomplish or tackle a task, but it does not always “ guarantee” a solution continuously (Gonzalez, Lerch & Lebiere, 2003). This often requires some critical thinking skills such as reflection and indicative reasoning (Gonzalez, Lerch & Lebiere, 2003). When I think of time constraint tasks, I always think of situations that require immediate attention and have a specific time it needs to be completed (Minton, Johnson, PhilipsLaird,1992). The example that comes to mind is something that I feel like I experience a lot working at a hospital. When a patient makes a claim against a star for another patient whether it is a sexual or physical assault the team needs to meet and discuss the incident within that same business day. Which means meeting with both parties involved, gathering data, taking notes, and making a clinical decision on what needs to be accomplished. For this specific situation, it appears that algorithmic problem solving would be more appropriate as there are specific steps that need to happen before a solution can occur.However, when it comes to the solution, it makes me think that Heuristics is pertained more, which means with when each solution there is not consistently, and there are not any guarantees(Gonzalez, Lerch & Lebiere, 2003). According to Rock, Ford, McRobert & Williams (2011) indicated that perceptual-cognitive skills play a crucial role in time constrained domains. I think both methods can be used in day-to-day life, it just depends on the situation.
References:
Gonzalez, C., Lerch, J. & Lebiere, C..(2003). Instance-based learning in dynamic decision making. Cognitive Science, 27, 591-635
Minton, S & Johnson, M., Philips, A.& Laird, P.(1992).Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems. Artificial Intelligence, 58, 161-205
Natsopoulos, D., Grouios, G., Bostantzopoulou, S., Mentenopoulos, G., Katsrou, Z. & Logothetis, J.(1993).algorthmic and heuristic strategies in comprehension of complement clauses by patients with Parkinson’s disease. Neuropsychologia, 31, 951-964
Rock, A., Ford, P., McRobert, A. & Williams, M.(2011).identifying the process underpinning anticipation and decision-making in a dyadic time constrained task. Cognition process, 12, 301-310
2. Re:Module 4 DQ 1 Chris
A growing real-world situation in which decision-making is time-constrained is the assessment test given online during applying for a job. The assessment is a mixture of questions ethical situations, business decisions and basic math problems. There is a time constraint placed upon the whole assessment. Obviously, the taker is seeking a job and realizes that if they do not complete the assessment in the time given they will not receive the job. But at the same time they also realize that if they get the questions wrong they will also not have an opportunity for the job. The desire to get the right answer on the assessment would lead one to turn to the algorithmic problem-solving method which is a method that follows a specific path or steps to solve the problem. This method is a logical approach that seeks to look at problems from all sides and work towards the only solution. It uses deductive reason to get to the right answer. However, this approach coupled with the time constraint might leave the taker short on time.
Thus, the heuristic problem-solving method might be the go to because of the time involved. This method is a short cut that relies upon what likely might be the answer. It is a modified algorithm that does not look at all sides of the problem but at what would likely be the case. This can help a person quickly move through problems and get to the answer that they think sounds/looks best. The problem with this method is that what looks best is not always right.
In the example above it would be wise for the test taker to use both approaches but know when to use the right method at the right time. When asked objective questions math, business questions the taker ought to use the heuristic approach for logic is already at work in these type questions thus, it is easier to make jumps to the right answer. This approach can help remove obstacles of problem solving by helping a person not get caught up in functional fixedness (Goldstein, 2011).
However, when it comes to ethical and social situations it would be important to use the algorithmic approach to logical walk through the problem to get to the proper answer. It is easier for a person to jump to an answer that they think is right or what they think wants to be heard using the heuristic method. Therefore, a person ought to logically think their way through this section of the assessment. I would argue that many of these type of assessments are designed with the mindset that people will answer heuristically which will expose their true ethical and social worldview.
The Zeigarnik effect could clearly help people prepare for such assessments in life by helping them develop a more logical and efficient approaches to assessment taking. Landrum (1993) suggest that there is a sensitivity of implicit memory when coupled with Zeigranik effect. This would suggest that if people approached assessment test as something that was incomplete in their job hunt they could better pull from implicit memory about many of the questions they are asked. The Zegarnik effect can help people see that they have an unfinished task before them and help them pull the needed information from memory to help complete the task.
Goldstein, E. B., (2011). Cognitive psychology: connecting mind, research and everyday experience, 3rd ed. Belmont, CA: Wadsworth.
Landrum, R. E. (1993). Sensitivity of implicit memory to input processing and the Zeigarnik effect. Journal Of General Psychology, 120(2), 91-98. doi:10.1080/00221309.1993.9921186
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