Using Decision-Making Science in Our Classrooms and Schools

Understanding advancements in cognitive science, neuroscience, and behavioral economics regarding individual’s decision-making and behaviors can greatly benefit educational leaders, teachers, and students alike. Teachers on average make 4 to 7 decisions every minute during classroom instruction, and an individual teacher makes up to 1500 important professional decisions daily that impact their students and classrooms. Similarly our students make hundreds of decisions that impact their learning, self-regulation, and socialization throughout the typical school day. As a high school principal, I know that the decisions I make every day impact the efficacy of our school, our classrooms, and help define relationships between educators, parents and students. Understanding the latest developments in cognitive science, neuroscience, and behavioral economics can lead to a better understanding of decision-making at both the classroom and school levels.

Decisions: Big and Small, Fast and Slow

As educators we often discuss best practices, research-based and data-driven processes, but we infrequently examine the key decisions, and the speed of decisions, that underpin the successful implementation of these practices in our classrooms and schools. I know that many of my own decisions as a high school principal are made routinely, seemingly with little thought or deliberation, in response to the questions, situations, or problems at hand. As such, most of my decisions are small decisions, or micro-decisions, and these small momentary decisions have ripple effects for teachers and students throughout the school. The fathers of behavioral economics, Daniel Kahneman (2011) and Amos Tversky defined two cognitive systems to explain how we make decisions: System 1 is fast thinking in which we operate automatically and quickly, with little or no effort, and almost no sense of voluntary control. And System 2 is slow and allocates attention to the effortful mental activities that demand it. It is not uncommon for educators and educational leaders to be deliberative about larger decisions, or macro-decisions, but we rarely pay attention to the dozens of micro-decisions we make throughout each and every day that have a tremendous impact on learning.

Some System 1 decisions are so common and automatic in our classrooms that they are almost left undiscussed in our practice and how they relate to student achievement. For example, a student request to use the bathroom typically gets an automatic response. However, if we slow down that decision by taking a System 2 approach, we can think about wherein an actual lesson a student might leave the classroom to use the lavatory that results in the minimal instructional impact. Decision making often happens in an automatic fashion based on heuristics, which are mental shortcuts or “rules of thumb”. Heuristics speed up our decisions and conserve mental energy in common situations, but fast decisions can also have outsized negative impacts in our schools. For example, simply sending a student to the lavatory at a strategic time during a lesson, while weighing the instructional impact, could facilitate increased learning.

Educators and students alike often believe that they control most decisions, and that their decisions are both rational and conscious. Decision making science demonstrates that individual factors, environmental factors, and social factors all shape our decisions in ways that don’t always ‘make sense’ and are not always rational. However, these irrational decisions are nonetheless predictable. (Ariely, 2009)

Individual Factors

Decision making by individuals can be affected by the heuristics they have developed or ego depletion. Educators can benefit from understanding how heuristics and ego depletion influence their own thinking and that of their students. For example, applying the lessons derived from a study of Israeli judges and their granting of parole in their courtrooms throughout the day. In this experiment it was demonstrated that justice is not blind, rather it fluctuates throughout the day based on fatigue and ego depletion. Ego depletion refers to the idea that self-control, ability to focus and concentrate, and willpower draws from a limited pool of mental resources that can be used up. When there is little mental energy left, self-control is typically impaired. Deep thinking or reasoning appears to require more caloric energy than a normal state. (Kahneman) In the study of Israeli judges, the rates of parole granted negatively correlated to cognitive load and ego depletion. In other words, punishments were more severe as the judges’ cognitive load or burden increased and they needed a break and some food. Following a break and/or eating justice significantly changed with more lenient granting of parole.Likewise, teachers can understand that their own mental energy, or that of their students to self-regulate, can be depleted throughout the school day. In this way, behavioral economic theory can be applied to our classrooms in strategically planning higher-order thinking activities or social emotional learning interventions.

Environmental Factors

Changing the way options are presented helps reduce cognitive load and ego depletion enabling teachers and school leaders to facilitate students making better choices. Small details embedded within choices can present students with direction and lead to better decisions. One example laid bare by Thaler and Sunstein (2008) is arranging food in a cafeteria line in a manner that allows for choice, but makes choosing healthier options more common by placing certain foods in prominent locations. Choice architecture allows for choice, but simplifies the setting of default options where the best choice is also the easiest choice. As a high school principal, I have applied choice architecture to a number of situations. For example, in promoting participation in the PSAT, where a grant fully funded freshmen participation, we made it more difficult for students and parents to opt-out of the test by requiring them to return a permission slip filled out with reasons five days before the test was given. The default for participation in the PSAT required no permission slip. The resulting participation rates exceeded that of other grade levels. Choice architecture can be applied to our schools and classrooms, where we make the best choice the easiest choice, whether having students selecting from assignments or even requesting for classes for the next school year.

Social Factors

Decision-making typically isn’t typically thought about as a social construct, but how people act and think often depends on the actions of those around them. Most people make reasonable efforts to conform to social norms and expectations whether consciously or not. For example, a behavioral economics experiment used social norms to reduce energy consumption by sending letters comparing each individual home’s energy usage with their immediate neighbors as well as the most efficient houses in their neighborhoods. Just sending this information within the monthly bill led to a significant reduction in energy consumption. The household’s consumption data was presented in a salient manner which transformed behavior based on the architecture of the monthly billing statement. In this way, personal behavior can be positively shaped by social norms and the social comparison effect. One similar application in a school setting could be to share general attendance rates with parents of at-risk students that have frequent absences; the salient nature of the presented information could act as an intervention for attending school more regularly.

Putting it all together

Using an interdisciplinary approach combining the recent learning in neuroscience, cognitive science, and behavioral economics regarding our decision-making tendencies can transform classroom and school-wide decisions. Behaviors, and the decision-making processes that guide them, can be understood through exploring current research and applying the lessons to situations taking place in our schools and classrooms. Decision making can be improved by exploring common cognitive biases, or systematic errors in thinking that occur when people are processing information, as well as examining and shaping the environmental architecture and social feedback factors that exist in our classrooms and schools.

While research in decision-making science is being done in university laboratories, government agencies, and businesses at a rapid rate, it is rarely utilized in an educational setting. More than likely you, the reader, have unknowingly participated in a behavioral experiment as you have clicked through websites, but data science and decision making science has rarely been used by school administrators or teachers. President Obama sought to normalize behavioral decision-making science to better serve the American people and issued an Executive Order titled the Behavioral Science Insights Policy Directive which required the development of the Social and Behavioral Sciences Team (2015) in order to “deliver better results at a lower cost for the American people”. At its core, economics is the study of decision-making, and the ‘rational’ model of decision-making has been upended with the awarding of two Nobel Prizes in Economics to Daniel Kahneman (2002) and Richard Thaler (2017). This recognition has legitimized the field of study and explained the limitations of the traditional ‘rational’ model of thinking and offered a new conception of ‘irrational’ decision-making influenced by individual factors, social pressure, and environmental architecture.

Schools and classrooms are natural action research labs where a single teacher, administrator, or a group of colleagues, can have an interest and impact in solving problems that involve decision making. Schools have received surprisingly little research attention from behavioral economists (Lavecchia et al., 2015) and even neuroscientists struggle to make their discoveries practical in actual school settings.

Practical Professional Practice and Inquiry

Teaching and educational leadership are similar in that both are parts science and art; as Leonardo Da Vinci purportedly stated, "Study the science of art. Study the art of science. Realize that everything connects you to everything else”. The application of behavioral economics and cognitive science findings should be applied by teachers and educational leaders in their own educational settings. I encourage my teachers to view assessment and grading through the context of loss aversion theory, which posits that people have a tendency to prefer avoiding losses to acquiring gains. One can implement classroom grading practices that encourage improvement through avoiding losses. I believe the endowment effect and Ikea effect, two well researched cognitive biases, need to be explored by educators to understand that the products we create, or simply own, are imbued with a disproportionately high value. This can explain teachers’ and students’ frustration in improving their own work, such as a teacher’s lesson or a student’s essay, because we tend to overvalue what is ours. Educational leaders and teachers can apply a choice architecture lens to the design of assessments, and can even encourage student and parent participation in events by making the best choice the easiest choice. Cognitive priming can be important in developing the emotional attitudes or predilections of both teachers and students. Even understanding the Halo effect or the Messenger effect, which links our reactions to messaging and who delivers it, has tremendous implications for equity in our schools.

Integrating the latest developments in cognitive science, neuroscience, and behavioral economics can lead to better decision-making throughout our classrooms and schools. As educators learn about the predictability of ‘irrational’ decisions, as well as strategies for shaping decision-making, the enormity of instructional and administrative decisions can be improved.

References

Ariely, Dan. ( 2010). Predictably irrational : the hidden forces that shape our decisions.

"Executive Order -- Using Behavioral Science Insights to Better Serve ...." 15 Sep. 2015, https://obamawhitehouse.archives.gov/the-press-office/2015/09/15/executive-order-using-behavioral-science-insights-better-serve-american. Accessed 4 Nov. 2018.

Kahneman, D. (2011). Thinking, fast and slow. New York: Farrar, Straus and Giroux.

Lavecchia, Adam M.; Liu, Heidi; Oreopoulos, Philip (2015) : Behavioral economics of education: progress and possibilities, IZA Discussion Papers, No. 8853, Institute for the Study of Labor (IZA), Bonn

Thaler, R. H., & Sunstein, C. R. (2008). Nudge: improving decisions about health, wealth, and happiness. New York: Penguin Books.