What goes into a decision? Sometimes, very little.

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“Human Factors” are design principles devoted to understanding and applying how humans interact with products or processes. There are universal human factors that help guide good design, such as:

  1. Sensory Perception
  2. Pre-attentive Processing
  3. Integration of Prior Knowledge
  4. Metacognition (topic of today’s blog)
  5. Working Memory

Understanding how people make decisions and think through things (metacognition), is an essential part of design. How can we optimize those decisions so the user has the best outcome?

The pre-fix “meta” refers to beyond, or after. It indicates an abstraction from a concept. Therefore, metacognition can be understood by breaking up the word into “meta” and “cognition.” An abstraction beyond thinking.

Metacognition was originally categorized as “the feeling of knowing” in the 60’s when a researcher asked people to predict if they might know something but be unable to retrieve that information. In the decades since, metacognition has been explored in many ways, with recurring definitions and themes. The definitions tend to be similar to this:

Metacognition is the mechanism by which a higher-order agent observes and evaluates our thinking processes, while participating in those thoughts at the same time.

Think of metacognition as our cognitive “boss.” Where metacognition sets rules and regulations, cognition carries out the directives. Any type of thinking is subject to metacognition, where these processes occur simultaneously.

Metacognition serves two functions: monitoring and controlling. For example, Kate needs a flight to San Francisco next week. Kate knows that searching for a flight can be demanding of her time. Allocating an hour that evening would be a metacognitive control process – awareness of the time it would take her to search and make a decision and setting a timeframe to complete the activity.

Selecting search criteria such as flight class and clicking or unclicking the checkboxes to open additional search windows both qualify as metacognitive control processes. She is thinking about how to frame her search in a more efficient or effective way, depending on her priorities. If her priority is to save money, she might need to devote more time to checking multiple websites. If her priority is to save time, she might only check Kayak. Metacognition makes Kate aware of her priorities and allows her to implement search strategies based on them.

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Setting search parameters is a metacognitive control process.

Metacognitive monitoring is evident as Kate searches the website, observing her search while making judgments about the effectiveness and mastery of this process.

Metacognition is very closely related to decision-making, where knowledge of cognitive ability is correlated with decision-making ability. Decisions have multiple parts to them: defining the problem or decision to be made, making judgments about the possible outcome, and then evaluating the best possible outcome and making a final decision.

Researchers used to believe in this idea of an “optimal decision,” where all outcomes are weighed and evaluated fairly and the best option is chosen. The reality is, no one actually has time or the desire to do this. Instead, we follow decision-making heuristics.

For example, there is a method known as satisficing, which is exactly as it sounds. We pick the first option that satisfies the criteria. If you are hungry, and you walk into a mall with multiple food options, you might want to just stop at the first place we see. Oh, wait. It’s a pretzel place and I am gluten-free. Nevermind. The next place is pretzels! We can stop there. Product placement in the grocery store is evidence that this decision-making technique is widely used. “Eye level is buy level.” We see it, it satisfies the criteria, and we move on without weighing options.

Engaging in a trade-off questioning, where they have to decide what is worth more to them in purchasing a product, is another method of decision-making. When deciding on a new Kindle, a person might try to decide if they want the Kindle Fire, with apps and video capabilities, or just a “Paper White” screen for reading. They might think, “well, I have a phone and a computer to play games and watch videos, so I can get the Paper White for a good reading experience.”


A user tries to decide on a Kindle: What’s worth more? Color graphics, or a good reading screen?


Another type of decision-making would be where a person eliminates options based on attributes. For example, if Adam was looking for a new car, he might eliminate based on: color (no red cars, obviously), poor gas mileage, and lack of heated seats.

People will also combine decision-making heuristics. Once Adam uses elimination to narrow his options, he might engage in trade-off questioning: is it more valuable to him to have a good sound system or a car with fewer miles on it?

Understanding how people make decisions and think through things (metacognition), is an essential part of design. How can we optimize those decisions so the user has the best outcome? As we consider this, we must think about ways in which we can support their metacognition: Kayak allows a user to search for multiple attributes (price, time, class, airline, duration, etc.) This allows people to engage more with the search process and make a better decision, ultimately. The better decision might be close to the “optimal” decision, or it might just be the first option that meets a criteria. Whatever the method, we’ve given the users the tools.






For more information, see links below:

Anderson, J. R. (1987). Methodologies for studying human knowledge. Behavioral and Brain Sciences, 10(03), 467-477.

Batha, K., & Carroll, M. (2007). Metacognitive training aids decision making. Australian Journal of Psychology, 59(2), 64-69.

Broadbent, D. E. (1977). Levels, hierarchies, and the locus of control. Quarterly Journal of Experimental Psychology, 29, 181-201.

Creyer, E. H., Bettman, J. R., & Payne, J. W. (1990). The impact of accuracy and effort feedback and goals on adaptive decision behavior. Journal of Behavioral Decision Making, 3(1), 1-16.

Dyer, J. S., Fishburn, P. C., Steuer, R. E., Wallenius, J., & Zionts, S. (1992). Multiple criteria decision making, multiattribute utility theory: the next ten years. Management science, 38(5), 645-654.

Edwards, W. (1954). The theory of decision making. Psychological Bulletin, 51, 380-417.

Einhorn, H. J., & Hogarth, R. M. (1978). Confidence in judgment: Persistence of the illusion of validity. Psychological review, 85(5), 395.

Hogarth, R. M. (1981). Beyond discrete biases: Functional and dysfunctional aspects of judgmental heuristics. Psychological Bulletin, 90(2), 197.

Nelson, T. O. (1996). Consciousness and metacognition. American psychologist, 51(2), 102.

Pitz, G. F., & Sachs, N. J. (1984). Judgment and decision: Theory and application. Annual Review of Psychology, 35(1), 139-164.

Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. science, 185(4157), 1124-1131.

von Neumann, J., & Morgenstem, O. (1947). Theory of games and economic behavior. Princeton, NJ: Princeton University Press.


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