We all use our brains to make decisions for carrying out everyday activities. Our nervous system is designed to facilitate decision- making either automatically which is effortless or deliberately, which is effortful (Shiffrin &Schneider 1977). When thinking automatically, the brain quickly retrieves previously stored information from memory. However, when thinking deliberately, the brain must also attend to information from external sources. (Shiffrin &Schneider 1977). Studying how our nervous system uses both the effortless and effortful processes will help us understand the mechanisms by which the brain regulates attentiveness to information and enables decision- making.
While the mechanistic basis of mental effort remains poorly understood, there are research-based theories to explain the phenomenology of mental effort. For example, the Cost-Benefit Theory indicates that we consciously experience mental effort (Székely, M., Michael, J, 2020) The theory attempts to explain why that experience could be aversive (Székely, M., Michael, J, 2020). The theory’s proponents argue that mental effort results from certain output processes, that track the expected costs and benefits of effortful mental activity and weighs them against each other (Székely, M., Michael, J, 2020). When the expected costs outweigh the expected benefits, an aversive state is generated. Accordingly, one of the reasons for aversion to mental effort, is the limited resource of cognitive control. As our cognitive control is limited exerting it- to focus on one task means that,- we lose the opportunity to focus on other tasks that are important to us. While we might think that increasing effortful attentiveness can result in better performance, there are times when “increase in cognitive effort can actually harm performance when expert judgement can be outperformed by simple rules based on quantifiable observations” (Székely, M., Michael, J, 2020).
Through research in cognitive psychology, the notion that mental effort is costly has been expanded (Inzlicht, M., Shenhav et al. 2018). It is argued that the effort itself can also be highly valued and rewarded. Here effort is defined as intensification of mental and/or physical activity in the service of meeting some goal (Inzlicht, M., Shenhav et al. 2018) There are many theories and phenomena that explain how and why effort is valued by some people that has to do with their personality such as need for cognition or learned industriousness (associative learning where high effort is paired with high reward) (Cacioppo, T. J., Petty, E, R., & Kao, F. 1984).
In the current study we focus on the role of cost-benefit analysis of mental effort in decision-making. The aim of this study is to determine how students with strong math background and students with some math knowledge make decisions when given a choice between solving math problems or reading and comprehension problems. This pairing might help us understand if confidence plays a role in decision-making. We assume that students with strong math background will be more confident in solving math problems and experience that process as effortless. Thus we predict that they would choose to solve math problems rather then reading- comprehension problems. In the present study we are not testing the student’s performance, but we are examining their decision-making process to determine whether confidence, and/or anxiety play role in this process. Testing this hypothesis is important because students might choose not to pursue science or STEM research for reasons such as the lack of confidence or anxiety. Mathematics and statistical data analysis are very important in research and science, but math anxiety may prevent students from attending to such cognitive tasks (Matt,S.M., & Rosli, M. K. 2016). Thus, student that do not practice effortful thinking may remain unaware of the significance of math and statistics in science and unprepared for solving problems that require such effortful thinking. The statistics anxiety is experienced by 80% of graduate students (Teman, E. D. 2013).Understanding the process of decision-making will help us design new student-centered curricula that takes into consideration the individual’s choice to engage in learning tasks, but also will help us improve the teaching methods to lower students’ anxiety.
Cacioppo, T. J., Petty, E, R., & Kao, F. Ch. (1984).The Efficient Assessment of Need for Cognition. Journal of Personality Assessment, 48:3, 306-307.
Grimaldi, P., Lau, H., & Basso, A. M. (2015). There are things that we know, and there are things that we don’t know we do not know: Confidence in decision-making. Neuroscience&Biobehavioral Reviews. 55, 88-97.
Maat, S. M., & Rosli, M. K. (2016).The Rasch Model Analysis for Statistical Anxiety Rating Scale (STARS). Creative Education, 7, 2820-2828.
Inzlicht, M., Shenhav, A., Olivola, Y, Ch (2018). The Effort Paradox: Effort Is Both Costly and Valued. Trends Cogn Sci. 22(4):337-349.
Teman, E. D. (2013). A Rasch Analysis of the Statistical Anxiety Rating Scale. Journal of Applied Measurement, 14 (4), 414-434.
Székely, M., Michael, J, (2020). The Sense of Effort: A Cost-Benefit Theory of Phenomenology of Mental Effort. Rev.Phil.Psych.
Shiffrin, M. R., Schneider, W. (1977).Controlled and Automatic Human Information Processing: II Perceptual learning, automatic Attending and a General Theory. Psychological Review, 84: 127-190.