Lab Report on Heuristics
Abstract
Heuristic techniques represent approaches that are employed in decision making, and they put to task a practical methodology that is not necessarily perfect or optimal, but one that is satisfactory enough in meeting the goals at hand (Hannawa, 2013). Recognition heuristics, in particular, people select an item such as a city because they are familiar with or recognize it (Oppenheimer, 2003). This concept takes center stage when the problem solver is accessed to limited information. Therefore, the problem solver uses what they know or recognize. This experiment sought to test the concept of recognition heuristics by assessing how participants respond to questions about cities in the USA. The mean number of correct responses was higher in the condition where the capital city was the largest city (M = 8.57, SD= 1.52) than in the condition where the capital city was not the largest city (M=3.09, SD =1.93). An independent groups t-test revealed that this difference across the conditions was significant: t(497)=43.70, p<.001. This experiment has emphasized the fact that heuristics is seen as mental shortcuts that lessen the cognitive load involved in decision-making.
Lab Report on Heuristics
Background
Heuristic techniques denote approaches that are employed in decision making, and they put to task a practical methodology that is not necessarily perfect or optimal, but one that is satisfactory enough in meeting the goals at hand (Hannawa, 2013). In addition, in cases where a practical or optimal solution is beyond the reach of the problem solver or impractical, these techniques can be employed in speeding up the process of finding a solution that is nevertheless satisfactory. In other words, heuristics can be seen as mental shortcuts that lessen the cognitive load involved in decision-making (Hannawa, 2013). Some of the methods that are involved in heuristics include common sense, profiling, stereotyping, intuitive judgment, an educated guess, and the use of a thumb of rule. In essence, heuristic involves the deployment of techniques requires information that is not only readily accessible, but also loosely applicable to problem solving.
Psychology sees heuristics not only as simple, but also efficient rules that can either be hard copied or learned by evolutionary processes, and have been suggested to account for how humans make decisions or come to judgments when solving complex problems or dealing with incomplete information (Hannawa, 2013). Different studies have been conducted to evaluate whether humans employ those rules with specific methods it has been found that such rules are only executable in certain circumstances (Goldstein & Gigerenzer, 2002). In other cases, they cause cognitive biases. Previous studies have shown that humans operate with what is referred to as boundary rationality. In other words, it has been found that humans tend to seek satisfying answers to problems at hand; choices or judgments that are satisfactory enough to the situation at hand. Such choices can be optimized (Goldstein & Gigerenzer, 2002).
Another study has shown that organizations and individuals employ heuristics in an adaptive manner. It was also shown that ignoring some parts of information instead of weighing all options have the ability to produce accurate decisions (Weiten, 2012).
Through research, a number of theories on heuristics have been engineered, and a good example is the Cognitive Experiential Self Theory (CEST). This theory identifies two processes that are involved in information processing (Hannawa, 2013). The first one involves the rational, logical, systematic, effortful, deliberate and verbal approach. In the second one, there is the employment of intuition or emotions, and this is done less effortlessly. It is now clear that heuristics falls in the adaptive, experiential information processing system. This system is at times prone to error in cases that call for a logical analysis. In a more recent theory, it has been suggested that cognitive heuristics follows attribute substitution process that occurs unconsciously. In this case, a complex cognitive problem is handled by solving a simpler problem unconsciously (Gigerenzer & Gaissmaier, 2011).
In recognition heuristics, people select an item such as a city because they are familiar with or recognize it (Oppenheimer, 2003). This concept takes center stage when the problem solver is accessed to limited information. Therefore, the problem solver uses what they know or recognize.
Aims and Hypotheses
This paper seeks to test the concept of recognition heuristics by assessing how participants respond to questions about cities in the USA.
Hypothesis: Participants will use recognition (what they know) in recognizing the cities.
Method
Participants
There were 498 participants. Females constituted 73.9 percent while males constituted 26.1 percent. The means, and standard deviation of ages were as follows: mean (20.5 years; S.D 6.51 years). Participants were from Melbourne, Brisbane, Canberra, and Strathfield campuses
Materials and Procedure
A questionnaire that has a set of 20 questions on cities of different states in the USA will be used. Each question has two options: a or b. Participants will have the opportunity of choosing the correct answer from the two available options. In essence, the choice of the answers will depend on the background knowledge that the participants have.
Each participant will provide their answers under observation in order to assess the recognition concept. The sessions were recorded on camera to allow for a detailed data analysis.
Results
The mean number of correct responses was calculated for the condition where the capital city was the largest (and likely most recognized) city and for the condition where the capital city was not the largest (and likely not recognized) city. The mean number of correct responses was higher in the condition where the capital city was the largest city (M = 8.57, SD= 1.52) than in the condition where the capital city was not the largest city (M=3.09, SD =1.93). An independent groups t-test revealed that this difference across the conditions was significant: t(497)=43.70, p<.001.
Discussion
The results of the study are in line with the findings of the previous studies, and they support the hypothesis at hand. Psychologists perceive heuristics not only as simple, but also efficient rules that can either be hard copied or learned by evolutionary processes, and have been suggested to account for how humans make decisions or come to judgments when solving complex problems or dealing with incomplete information (Hannawa, 2013).
In addition, in cases where a practical or optimal solution is beyond the reach of the problem solver or impractical, heuristics can be employed in speeding up the process of finding a solution that is nevertheless satisfactory (Goldstein & Gigerenzer, 2002). In other words, heuristics can be seen as mental shortcuts that lessen the cognitive load involved in decision-making. In essence, heuristic involves the deployment of techniques requires information that is not only readily accessible, but also loosely applicable in problem-solving (Goldstein & Gigerenzer, 2002).
In recognition heuristics, people select an item such as a city because they are familiar with or recognize it (Oppenheimer, 2003). This concept takes center stage when the problem solver is accessed to limited information. Therefore, the problem solver uses what they know or recognize. This experiment has proved these concepts. The participants were given a total of twenty questions with only two options. The questions were framed in a manner that would make the recognition of the answer rather easy. There were two sets of questions. In the first set, the options to choose from had a common and most populous city and a less common and less populous city. It was easy for the participants to recognize the most populous city as the capital city of the state in question. In other words, here, the participants used the recognition concept to identify the desired answer. In the second set of questions, the two options were two most populous cities, and well known. Participants had to employ the little data that they have in those cities and choose the capital city from them.
Again, in the majority of the mean number of correct responses was higher in the condition where the capital city was the largest city. In essence, the respondents compared the perceived size and popularity of the two cities. People used their limited knowledge about the chosen city and inferred that the city is the capital city because of its size or popularity.
Limitations and Future Directions
The study was limited by the fact that some participants did not take the test in camera and, therefore, their behavior could not be documented. Future studies should ensure that there is correct recording and that the option provided trigger the use of recognition heuristics.
Conclusion
This experiment evaluated the concept of recognition heuristics by assessing how participants respond to questions about cities in the USA. In essence, the respondents compared the perceived size and popularity of the two cities while choosing between two populous cities and popularity and population size when choosing the answer from the option with between one big city and a small city. Therefore, this experiment has reaffirmed the hypothesis of this experiment: Participants will use recognition (what they know) in recognizing the cities.
References
Hannawa, F. (2013). Heuristic thinking: interdisciplinary perspectives on medical error. The Journal of Public Health, 2(3), 1-10.
Gigerenzer, G. and Gaissmaier, W. (2011). Heuristic Decision Making. Annual Review of Psychology, 62. pp. 451–482.
Goldstein, D. G. & Gigerenzer, G. (2002). Models of ecological rationality: The recognition heuristic. Psychological Review, 109, 75-90.
Oppenheimer, D. M. (2003). Not so fast! (and not so frugal!): Rethinking the recognition heuristic. Cognition, 90, B1-B9.
Weiten, W. (2012). Psychology: themes and variations. (9th ed.). Belmont, CA: Wadsworth. (in particular Approaches to problem solving. Page 328.
