Political Behavior

, Volume 40, Issue 1, pp 79–101 | Cite as

Motivated Responding in Studies of Factual Learning

  • Kabir KhannaEmail author
  • Gaurav Sood
Original Paper


Large partisan gaps in reports of factual beliefs have fueled concerns about citizens’ competence and ability to hold representatives accountable. In three separate studies, we reconsider the evidence for one prominent explanation of these gaps—motivated learning. We extend a recent study on motivated learning that asks respondents to deduce the conclusion supported by numerical data. We offer a random set of respondents a small financial incentive to accurately report what they have learned. We find that a portion of what is taken as motivated learning is instead motivated responding. That is, without incentives, some respondents give incorrect but congenial answers when they have correct but uncongenial information. Relatedly, respondents exhibit little bias in recalling the data. However, incentivizing people to faithfully report uncongenial facts increases bias in their judgments of the credibility of what they have learned. In all, our findings suggest that motivated learning is less common than what the literature suggests, but also that there is a whack-a-mole nature to bias, with reduction in bias in one place being offset by increase in another place.


Motivated reasoning Learning Responding Partisan bias Factual beliefs Polarization Biased assimilation Prior attitude effect 



We would like to thank Princeton Research in Experimental Social Science (PRESS) for financial support. We are also very grateful to Dan Kahan for generously sharing experimental design details; Doug Ahler, Martin Bisgaard, Katie McCabe, Peter Mohanty, and Markus Prior for insightful comments on a previous draft; participants of the PRESS workshop for suggestions about the experimental design; and finally, the editor of this journal and three reviewers for their critical feedback and guidance. The data and code necessary to replicate the results in this paper are available at

Supplementary material

11109_2017_9395_MOESM1_ESM.pdf (552 kb)
Supplementary material 1 (pdf 553 KB)


  1. Ahler, D., & Sood, G. (2016). The parties in our heads: Misperceptions about party composition and their consequences. Working paper.Google Scholar
  2. Arceneaux, K., & Vander Wielen, R. J. (2013). The effects of need for cognition and need for affect on partisan evaluations. Political Psychology, 34(1), 23–42.CrossRefGoogle Scholar
  3. Bartels, L. M. (2002). Beyond the running tally: Partisan bias in political perceptions. Political Behavior, 24(2), 117–150.CrossRefGoogle Scholar
  4. Bechlivanidis, C., & Lagnado, D. A. (2013). Does the “why” tell us the “when”? Psychological Science, 24(8), 1563–1572.CrossRefGoogle Scholar
  5. Berinsky, A. J., Huber, G. J., & Lenz, G. S. (2012). Evaluating online labor markets for experimental research:’s Mechanical Turk. Political Analysis, 20(3), 351–368.CrossRefGoogle Scholar
  6. Bisgaard, M. (2015). Bias will find a way: Economic perceptions, attributions of blame, and partisan-motivated reasoning during crisis. The Journal of Politics, 77(3), 849–860.CrossRefGoogle Scholar
  7. Blais, A., Gidengil, E., Fournier, P., Nevitte, N., Everitt, J., & Kim, J. (2010). Political judgments, perceptions of facts, and partisan effects. Electoral Studies, 29(1), 1–12.CrossRefGoogle Scholar
  8. Bolsen, T., Druckman, J. N., & Cook, F. L. (2014). The influence on partisan motivated reasoning on public opinion. Political Behavior, 36(2), 235–262.CrossRefGoogle Scholar
  9. Buhrmester, M., Kwang, T., & Gosling, S. D. (2011). Amazon’s Mechanical Turk: A new source of inexpensive, yet high-quality, data? Perspectives on Psychological Science, 6(1), 3–5.CrossRefGoogle Scholar
  10. Bullock, J. G., Gerber, A. S., Hill, S. J., & Huber, G. A. (2015). Partisan bias in factual beliefs about politics. Quarterly Journal of Political Science, 10(4), 519–578.CrossRefGoogle Scholar
  11. Chaiken, S., & Maheswaran, D. (1994). Heuristic processing can bias systematic processing: Effects of source credibility, argument ambiguity, and task importance on attitude judgment. Journal of Personality and Social Psychology, 3(66), 460–473.CrossRefGoogle Scholar
  12. Chambers, J. R., Swan, L. K., & Heesacker, M. (2014). Better off than we know: Distorted perceptions of incomes and income inequality in america. Psychological Science, 25(2), 613–618.CrossRefGoogle Scholar
  13. Chambers, J. R., Swan, L. K., & Heesacker, M. (2015). Perceptions of U.S. social mobility are divided (and distorted) along ideological lines. Psychological Science, 26(4), 413–423.CrossRefGoogle Scholar
  14. Crawford, J. T., Kay, S. A., & Duke, K. E. (2015). Speaking out of both sides of their mouths: Biased political judgments within (and between) individuals. Social Psychological and Personality Science, 6(4), 422–430.CrossRefGoogle Scholar
  15. Crawford, J. T., & Xhambazi, E. (2015). Predicting political biases against the Occupy Wall Street and Tea Party movements. Political Psychology, 36(1), 111–121.CrossRefGoogle Scholar
  16. Dawson, E., Gilovich, T., & Regan, D. T. (2002a). Motivated reasoning and performance on the Wason selection task. Personality and Social Psychology Bulletin, 28(10), 1379–1387.CrossRefGoogle Scholar
  17. Dawson, E., Gilovich, T., & Regan, D. T. (2002b). Motivated reasoning and susceptibility to the “Cell A” bias. Manuscript submitted for publication.Google Scholar
  18. Ditto, P. H., & Lopez, D. F. (1992). Motivated skepticism: Use of differential decision criteria for preferred and nonpreferred conclusions. Journal of Personality and Social Psychology, 4(63), 568–584.CrossRefGoogle Scholar
  19. Ditto, P. H., Scepansky, J. A., Munro, G. D., Apanovitch, A. M., & Lockhart, L. K. (1998). Motivated sensitivity to preference-inconsistent information. Journal of Personality and Social Psychology, 1(75), 53–69.CrossRefGoogle Scholar
  20. Edwards, K., & Smith, E. E. (1996). A disconfirmation bias in the evaluation of arguments. Journal of Personality and Social Psychology, 71(1), 5.CrossRefGoogle Scholar
  21. Gaines, B. J., Kuklinski, J. H., Quirk, P. J., Peyton, B., & Verkuilen, J. (2007). Same facts, different interpretations: Partisan motivation and opinion on Iraq. Journal of Politics, 69(4), 957–974.CrossRefGoogle Scholar
  22. Gerber, A. S., & Huber, G. A. (2009). Partisanship and economic behavior: Do partisan differences in economic forecasts predict real economic behavior? American Political Science Review, 103(3), 407–426.CrossRefGoogle Scholar
  23. Gilens, M. (2001). Political ignorance and collective policy preferences. American Political Science Review, 95(2), 379–396.CrossRefGoogle Scholar
  24. Gilovich, T. D. (1991). How we know what isn’t so: The fallibility of human reason in everyday life. New York: The Free Press.Google Scholar
  25. Hastorf, A. H., & Cantril, H. (1954). They saw a game: A case study. The Journal of Abnormal and Social Psychology, 49(1), 129.CrossRefGoogle Scholar
  26. Hochschild, J. L. (2001). Where you stand depends on what you see: Connections among values, perceptions of fact, and political prescriptions. In J. H. Kuklinski (Ed.), Citizens and politics: Perspectives from political psychology. New York: Cambridge University Press.Google Scholar
  27. Iyengar, S., Sood, G., & Lelkes, Y. (2012). Affect, not ideology: A social identity perspective on polarization. Public Opinion Quarterly, 76(3), 405–431.CrossRefGoogle Scholar
  28. Iyengar, S., & Westwood, S. J. (2015). Fear and loathing across party lines: New evidence on group polarization. American Journal of Political Science, 59(3), 690–707.CrossRefGoogle Scholar
  29. Jacobson, G. (2010). Perception, memory, and partisan polarization on the Iraq War. Political Science Quarterly, 1(125), 31–56.CrossRefGoogle Scholar
  30. Jerit, J., & Barabas, J. (2012). Partisan perceptual bias and the information environment. Journal of Politics, 74(3), 672–684.CrossRefGoogle Scholar
  31. Kahan, D. M. (2013). Ideology, motivated reasoning, and cognitive reflection. Judgment and Decision Making, 8(4), 407–424.Google Scholar
  32. Kahan, D. M., Peters, E., Dawson, E. C., & Slovic, P. (2017). Motivated numeracy and enlightened self-government. Behavioural Public Policy, Forthcoming. Yale Law School, Public Law Working Paper No. 307. Available at SSRN:
  33. Kahneman, D. (2013). The marvels and flaws of intuitive thinking. In J. Brockman (Ed.), Thinking: The new science of decision-making, problem-solving, and prediction. New York: Harper Collins.Google Scholar
  34. Kim, S., Taber, C. S., & Lodge, M. (2010). A computational model of the citizen as motivated reasoner: Modeling the dynamics of the 2000 presidential election. Political Behavior, 32(1), 1–28.CrossRefGoogle Scholar
  35. Kruglanski, A. W., & Webster, D. M. (1996). Motivated closing of the mind: “Seizing” and “freezing”. Psychological Review, 103(2), 263–283.CrossRefGoogle Scholar
  36. Kunda, Z. (1990). The case for motivated reasoning. Psychological Bulletin, 108(3), 480–498.CrossRefGoogle Scholar
  37. Lau, R. R., Sears, D. O., & Jessor, T. (1990). Fact or artifact revisited: Survey instrument effects and pocketbook politics. Political Behavior, 12(3), 217–242.CrossRefGoogle Scholar
  38. Lebo, M. J., & Cassino, D. (2007). The aggregated consequences of motivated reasoning and the dynamics of partisan presidential approval. Political Psychology, 28(6), 719–746.CrossRefGoogle Scholar
  39. Lord, C. G., Ross, L., & Lepper, M. R. (1979). Biased assimilation and attitude polarization: The effects of prior theories on subsequently considered evidence. Journal of Personality and Social Psychology, 37(11), 2098–2109.CrossRefGoogle Scholar
  40. Luskin, R. C., & Bullock, J. G. (2011). “Don’t know” means “don’t know”: DK responses and the public’s level of political knowledge. The Journal of Politics, 73(2), 547–557.CrossRefGoogle Scholar
  41. Luskin, R. C., Sood, G., & Blank, J. (2013). The waters of Casablanca: Political misinformation (and knowledge and ignorance). Unpublished manuscript.Google Scholar
  42. Lyons, J., & Jaeger, W. P. (2014). Who do voters blame for policy failure? Information and the partisan assignment of blame. State Politics & Policy Quarterly, 114(3), 321–341.CrossRefGoogle Scholar
  43. Mata, A., Garcia-Marques, L., Ferreira, M. B., & Mendonça, C. (2015a). Goal-driven reasoning overcomes cell D neglect in contingency judgements. Journal of Cognitive Psychology, 27(2), 238–249.CrossRefGoogle Scholar
  44. Mata, A., Sherman, S. J., Ferreira, M. B., & Mendonça, C. (2015b). Strategic numeracy: Self-serving reasoning about health statistics. Basic and Applied Social Psychology, 37(3), 165–173.CrossRefGoogle Scholar
  45. Muirhead, R. (2013). The case for party loyalty. In S. Levinson, J. Parker, & P. Woodruff (Eds.), Loyalty. New York: New York University Press.Google Scholar
  46. Mullinix, K. J., Leeper, T. J., Druckman, J. N., & Freese, J. (2015). The generalizability of survey experiments. Journal of Experimental Political Science, 2(2), 109–138.CrossRefGoogle Scholar
  47. Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175–220.CrossRefGoogle Scholar
  48. Nyhan, B. (2010). Why the “death panel” myth wouldn’t die: Misinformation in the health care reform debate. The Forum, 8(1), 5.Google Scholar
  49. Nyhan, B., & Reifler, J. (2010). When corrections fail: The persistence of political misperceptions. Political Behavior, 32(2), 303–330.CrossRefGoogle Scholar
  50. Palmer, H. D., & Duch, R. M. (2001). Do surveys provide representative or whimsical assessments of the economy? Political Analysis, 9(1), 58–77.CrossRefGoogle Scholar
  51. Paolacci, G., & Chandler, J. (2014). Inside the Turk: Understanding Mechanical Turk as a participant pool. Current Directions in Psychological Science, 23(3), 184–188.CrossRefGoogle Scholar
  52. Prior, M. (2013). Media and political polarization. Annual Review of Political Science, 16, 101–127.CrossRefGoogle Scholar
  53. Prior, M., & Lupia, A. (2008). Money, time, and political knowledge: Distinguishing quick recall and political learning skills. American Journal of Political Science, 52(1), 169–183.CrossRefGoogle Scholar
  54. Prior, M., Sood, G., & Khanna, K. (2015). You cannot be serious: The impact of accuracy incentives on partisan bias in reports of economic perceptions. Quarterly Journal of Political Science, 10(4), 489–518.CrossRefGoogle Scholar
  55. Sears, D. O., & Lau, R. R. (1983). Apparently self-interested political preferences. American Journal of Political Science, 27(2), 223–252.CrossRefGoogle Scholar
  56. Shani, D. (2006). Knowing your true colors: Can knowledge correct for partisan bias in Political perceptions? Presented at the Annual Meeting of the Midwest Political Science Association, Chicago, IL.Google Scholar
  57. Shapiro, R. Y., & Bloch-Elkon, Y. (2008). Do the facts speak for themselves? Partisan disagreement as a challenge to democratic competence. Critical Review, 20(1–2), 115–139.CrossRefGoogle Scholar
  58. Stroud, N. J. (2010). Polarization and partisan selective exposure. Journal of Communication, 60(3), 556–576.CrossRefGoogle Scholar
  59. Taber, C. S., & Lodge, M. (2006). Motivated skepticism in the evaluation of political beliefs. American Journal of Political Science, 50(3), 755–769.CrossRefGoogle Scholar
  60. Thibodeau, P., Peebles, M. M., Grodner, D. J., & Durgin, F. H. (2015). The wished-for always wins until the winner was inevitable all along: Motivated reasoning and belief bias regulate emotion during elections. Political Psychology, 36(4), 431–448.CrossRefGoogle Scholar
  61. Weller, J. A., Dieckmann, N. F., Tusler, M., Mertz, C. K., Burns, W. J., & Peters, E. (2012). Development and testing of an abbreviated numeracy scale: A Rasch analysis approach. Journal of Behavioral Decision Making, 26(2), 198–212.CrossRefGoogle Scholar
  62. Wilcox, N., & Wlezien, C. (1993). The contamination of responses to survey items: Economic perceptions and political judgments. Political Analysis, 5(1), 181–213.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Department of PoliticsPrinceton UniversityPrincetonUSA
  2. 2.Data ScientistSan FranciscoUSA

Personalised recommendations