Classroom Demonstrations for the Shared Circumstance Effect

---A guide prepared by Jason Rose
---Relevant research and the creation of this site were supported by Grant SES 03-19243 to
Paul D. Windschitl from the National Science Foundation.

Below you will find a very brief overview of the shared-circumstance effect, descriptions and links for two classroom demonstrations of the effect, and references for the effect.

Overview/Background

Imagine that your favorite football team is playing in the rain this weekend. Or that you are taking a class where the instructor decides to "go easy" on the students by removing some of the more challenging exam items. How optimistic would you be about your favorite team winning the football game? Or about finishing in the top quarter of your class?

Recent research has shown that people tend to be overly optimistic about their chances of winning in competitions when the circumstances are generally favorable (e.g., easy exams, wild cards in a poker game) but overly pessimistic when the circumstances are generally unfavorable (e.g., difficult exams, rain in a football game). Of course, rain at a football game and easy exam questions are shared circumstances; they are circumstances that will tend to influence the performances of all competitors (i.e., rain would generally impair both team's performances and easy exam questions would generally facilitate students' performances). Thus, from an objective point of view, it is problematic when a vast majority of competitors believe they will outperform each other on easy tasks, but lose to each other on difficult tasks. This tendency for people to inflate likelihood estimates about winning in competitions that seem easy, but deflate likelihood estimates in competitions that seem difficult has been termed the shared-circumstance effect (SCE; Windschitl, Kruger, & Simms, 2003; see also Kruger, Windschitl, Burrus, Fessel, & Chambers, 2008; Moore & Kim, 2003; Rose & Windschitl, 2008; Windschitl, Rose, Stalkfleet, & Smith, 2008).

Why do people show the SCE? The most prominent explanations for the effects involve differences in the way that people use information or answer questions about the self vs. one's competitors. For instance, some research suggests that people egocentrically pay more attention to their own strengths/weaknesses than to the strengths/weaknesses of their competitor(s) when formulating optimism. Differential weighting of self-relevant information (at the expense of competitor-relevant information) may be due to the fact that people do not have much information about their competitors or because people have chronic biases in which more attention is devoted to self-relevant information and/or focal information (see Chambers & Windschitl, 2004; Rose & Windschitl, 2008; Windschitl et al., 2008). In either case, disproportionate weighting would lead people to pay more attention to self-strengths in cases where circumstances are favorable for a good performance (leading to over-optimism), but to pay attention to self-weaknesses in cases where circumstances are unfavorable for a good performance (leading to over-pessimism). There are also other explanations for SCEs (e.g., differential regression). Overviews of these explanations can be found in Chambers & Windschitl (2004), Moore (2007), and Windschitl, Rose, Stalkfleet, and Smith (2008).

Classroom Demonstration #1 (click here for the handout)

This first demonstration is closely related to a study described by Windschitl, Kruger, and Simms (2003) (see Experiment 2). The handout asks students to imagine being in a class and wanting to finish in the top half of the class. Several events are listed, and each falls into one of four categories: 1) shared adversities (items 5, 12, 15) are events that would hurt the absolute performance of all students, 2) shared benefits (items 6, 9, 14) are events that would help the absolute performance of all students, 3) unique adversities are events that would hurt the performance of the individual student but not others, 4) unique benefits are events that would help the performance of the individual student but not others. For each event, students indicate how the event would tend to influence the chances that the student would finish in the top half of the class. Of course, students tend to believe that the unique adversities and benefits will harm and help (respectively) their chances. The more critical finding is that students tend to believe that shared adversities and shared benefits will also harm and help (respectively) their chances. This is one version of the shared-circumstance effect.

Classroom Demonstration #2 (click here for the handout)

This second demonstration is related to a study described by Windschitl, Kruger, and Simms (2003) (see Experiment 3). It involves a case where a student will have a single, individuated opponent. In this demo, students will estimate the chance of beating a specified classmate in knowledge categories that either sound easy to most college students or difficult to most students. Overall, the majority of students should show a tendency to believe a victory is likely when shared benefits are present (i.e., the category is easy) and a loss is likely when shared adversities are present (i.e., the category is hard). Of course, not everyone can win the easy categories and lose the hard categories. In fact, given that there are always exactly two competitors per competition, the average of the competitor's probability estimates should tend to fall at about 50%. Values systematically higher than 50% reflect general overoptimism and values systematically lower than 50% reflect general overpessimism.

To conduct the demo, you'll first want to assign each student to an opponent. To do this, ask students to select a number between 2 and 4. Next, ask them to select either "left" or "right". Tell the students to locate the individual in their row that corresponds to the coordinates selected (e.g., the person sitting 2 people to the right). Of course, if this procedure creates problems with students sitting on the ends of rows, you can tell those students to select the left instead of right (or vice versa). Once this person has been located by the students, tell the students that the individual selected is their presumed opponent. Then have students complete the demonstration handout. When they are done, you can ask them to average their responses for the easy items (2, 3, 5, 6) and then the hard items (1, 4, 7, 8). Then ask them to raise their hands if their first average was greater than the second average, which would illustrate the shared-circumstance effect. Alternatively, you could go through the 8 quizzes individually-asking student to raise their hand if they gave an answer above 50%.

References

Chambers, J., & Windschitl, P. D. (2004). Biases in social comparative judgments: The role of nonmotivated factors in above-average and comparative-optimism effects. Psychological Bulletin, 130, 813-838.

Kruger, J., Windschitl, P. D., Burrus, J., Fessel, F., & Chambers, J. R. (2008). On the rational side of egocentrism in social comparisons. Journal of Experimental Social Psychology, 44, 220-232.

Moore, D. A. (2007). Not so above average after all: When people believe they are worse than average and its implications for theories of bias in social comparison. Organizational Behavior and Human Decision Processes, 102, 42-58.

Moore, D. A., & Kim, T. G. (2002). Myopic social prediction and the solo comparison effect. Journal of Personality and Social Psychology, 85, 1121-1135.

Rose, J. P., & Windschitl, P. D. (2008). How egocentrism and optimism change in response to feedback in repeated competitions. Organizational Behavior and Human Decision Processes, 105, 201-220.

Windschitl, P. D., Kruger, J., & Simms, E. N. (2003). The influence of egocentrism and focalism on people's optimism in competitions: When what affects us equally affects me more. Journal of Personality and Social Psychology, 85, 349-408.

Windschitl, P. D., Rose, J. P., Stalkfleet, M., & Smith, A. R. (2008). Are people excessive of judicious in their egocentrism? A modeling approach to understanding bias and accuracy in people's optimism. Journal of Personality and Social Psychology, 95, 253-273.