# The availability heuristic in the classroom: How soliciting more criticism can boost your course ratings

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3 Judgment and Decision Making, Vol. 1, No. 1, July 2006 Heuristic course evaluation 88 Table 1: Results of linear regressions predicting course evaluation scores. Model Number Critiques * * solicited (0.0334) (0.0334) (0.0446) (0.0632) Critiques produced (0.0957) (0.0928) (0.0971) (0.138) Ratio of 1.070** 1.081* 1.075** 1.12 produced (0.312) (0.439) (0.343) (0.667) to solicited Adj R < p <.10, * p <.05, ** p <.005 Note: Rows correspond to independent variables. Regression models are numbered by column. Cell entries list regression coefficients, with standard deviations in parentheses. Adjusted R 2 values for each regression are listed below the relevant column. Not surprisingly, participants produced a greater number of suggestions in the 10-slot condition (M = 2.1; SD = 1.84) than in the 2-slot condition (M = 1.6, SD = 0.72); however, this difference was small and not statistically significant (t(56) = 1.52, p =.14). In fact, only 31% of participants in the 10-slot condition provided more than two suggestions for ways in which the course could be improved. One might therefore surmise that the observed effects on course ratings were more often driven by artificially extending the natural retrieval process of students in the 10-slot condition (thereby improving subsequent course ratings) than by artificially truncating the natural retrieval process of students in the 2-slot condition (thereby depressing subsequent course ratings). In previous studies using similar methods, the vast majority of participants did manage to produce the number of examples that were solicited by the experimenter so that the number of examples solicited and the number provided were perfectly (or nearly perfectly) correlated. In the present study, the variability in the number of critiques provided by respondents in both conditions offers a unique opportunity to explore the independent effects of the number provided and the number solicited. 3 When both variables are entered into an ordinary least-square regression, the number solicited is positively related to course ratings (b =.09, t(55) = 2.56, p =.01), and the number produced is negatively related to course ratings 3 Participants in the studies of Grayson and Schwarz (1999) also failed to report all the examples solicited, however these investigators report no such internal analysis. (b = -.16, t(55) = -1.74, p =.09; see model 4, Table 1). One might infer on the basis of this result that the number of critiques solicited provides a frame against which the number recalled is evaluated. If so, one would expect course ratings to be predicted quite well by the ratio of critical comment produced to critical comments solicited. Indeed, there is a strong negative correlation between this ratio and course ratings (r = -.42; t(56) = -3.43, p <.001; see also model 3, Table 1). Moreover, when we enter both the number of critiques solicited and the ratio of critiques produced to solicited into a regression (model 5, Table 1), the independent effect of the number solicited is wiped out (b = 0.00, t(55) = 0.04, p =.97), but the association between course ratings and the ratio of criticisms produced to solicited remains strong and significant (b = -1.08, t(55) = -2.47, p =.02). 4 Similarly, when we enter both the number of critical comments produced and the ratio of critiques produced to solicited into a regression (model 6, see Table 1), the independent effect of the number of critiques produced is wiped out (b = 0.00, t(55) = -0.04, p =.97), but the independent association between course ratings the ratio of critiques produced to solicited remains strong and significant (b = -1.07, t(55) = -3.13, p =.003). 5 Taken together, these results suggest 4 Multicollinearity does not seem to be a problem. The correlation between number of critiques produced and the ratio of critiques produced to solicited is 0.38, and the Variance Inflation Factor (VIF) in the multiple regression is Again, multicollinearity does not seem to be a problem. The correlation between number of critiques solicited and the ratio of critiques

5 Judgment and Decision Making, Vol. 1, No. 1, July 2006 Heuristic course evaluation 90 Schwarz, N. (2004). Metacognitive experiences in consumer judgment and decision making. Journal of Consumer Psychology, 14, Schwarz, N., Bless, H., Strack, F., Klumpp, G., Rittenauer-Schatka, H., & Simmons, A. (1991). Ease of retrieval as information: Another look at the availability heuristic. Journal of Personality and Social Psychology, 61, Sudman, S., Bradburn, N. M. & Schwarz, N. (1996). Thinking About Answers: The application of Cognitive Processes to Survey Methodology. San Francisco: Jossey-Bass. Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5, Wänke, M., Bless, H. & Biller, B. (1996). Subjective experience versus content of information in the construction of attitude judgments. Personality and Social Psychology Bulletin, 22, Wänke, M., Bohner, G, & Jukowitsch, A. (1997). There are many reasons to drive a BMW: Does imagined ease of argument generation influence attitudes? Journal of Consumer Research, 24, Wänke, M., Schwarz, N. & Bless, H. (1995). The availability heuristic revisited: Experienced ease of retrieval in mundane frequency estimates. Acta Psychologica, 89, Winkielman, P., & Schwarz, N., & Belli, R. F. (1998). The Role of ease of retrieval and attribution in memory judgments: Judging your memory as worse despite recalling more events. Psychological Science, 9, Winkielman, P., & Schwarz, N. (2001). How pleasant was your childhood? Beliefs about memory shape inferences from experienced difficulty of recall. Psychological Science, 12,

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