Skip to main content
SpringerLink
Log in

Is underestimation less detrimental than overestimation? The impact of experts’ beliefs about a layperson’s knowledge on learning and question asking

  • Published:
Instructional Science Aims and scope Submit manuscript

Abstract

Although prior research has shown that experts tend to overestimate or underestimate what laypersons actually know, little is known about the specific consequences of biased estimations for communication. To investigate the impact of biased estimations of a layperson’s knowledge on the effectiveness of experts’ explanations, we conducted a web-based dialog experiment with 45 pairs of experts and laypersons. We manipulated the experts’ mental model of the layperson by presenting them either valid information about the layperson’s knowledge or information that was biased towards overestimation or underestimation. Results showed that the experts adopted the biased estimations and adapted their explanations accordingly. Consequently, the laypersons’ learning from the experts’ explanations was impaired when the experts overestimated or underestimated the layperson’s knowledge. In addition, laypersons whose knowledge was overestimated more often generated questions that reflected comprehension problems. Laypersons whose knowledge was underestimated asked mainly for additional information previously not addressed in the explanations. The results suggest that underestimating a learner during the instructional dialog is as detrimental to learning as is the overestimation of a learner’s knowledge. Thus, the provision of effective explanations presupposes an accurate mental model of the learner’s knowledge prerequisites.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  • Alexander, P. A., Kulikowich, J. M., & Schulze, S. K. (1994). How subject-matter knowledge affects recall and interest. American Educational Research Journal, 31, 313–337.

    Article  Google Scholar 

  • Alty, J. L., & Coombs, M. J. (1981). Communicating with university computer users: A case study. In M. J. Coombs & J. L. Alty (Eds.), Computing skills and the user interface (pp. 7–71). London: Academic Press.

  • Anderson, K. C., & Leinhardt, G. (2002). Maps as representations: Expert novice comparison of projection understanding. Cognition and Instruction, 20, 283–321.

    Article  Google Scholar 

  • Beck, I. L., McKeown, M. G., Sinatra, G. M., & Loxterman, J. A. (1991). Revising social studies text from a textprocessing perspective: Evidence of improved comprehensibility. Reading Research Quarterly, 26, 251–276.

    Article  Google Scholar 

  • Borko, H., & Putnam, R. (1996). Learning to teach. In D. Berliner & R. Calfee (Eds.), Handbook of educational psychology (pp. 673–708). New York: Macmillan.

  • Brennan, S. E., & Clark, H. H. (1996). Conceptual pacts and lexical choice in conversation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22, 1482–1493.

    Article  Google Scholar 

  • Britton, B. K., & Gülgöz, S. (1991). Using Kintsch’s computational model to improve instructional text: Effects of repairing inference calls on recall and cognitive structures. Journal of Educational Psychology, 83, 329–345.

    Article  Google Scholar 

  • Bromme, R., Jucks, R., & Runde, A. (2005a). Barriers and biases in computer-mediated expert-layperson-communication. In R. Bromme, F. W. Hesse, & H. Spada (Eds.), Barriers and biases in computer-mediated knowledge communication – and how they may be overcome (pp. 89–118). New York: Springer.

  • Bromme, R., Jucks, R., & Wagner, T. (2005b). How to refer to “diabetes”? Language in online health advice. Applied Cognitive Psychology, 19, 569–586.

    Article  Google Scholar 

  • Bromme, R., Nückles, M., & Rambow, R. (1999). Adaptivity and anticipation in expert-laypeople communication. In S. E. Brennan, A. Giboin, & D. Traum (Eds.), Psychological models of communication in collaborative systems. AAAI Fall Symposion Series (pp. 17–24). Menlo Park, CA: AAAI.

  • Bromme, R., Rambow, R., & Nückles, M. (2001). Expertise and estimating what other people know: The influence of professional experience and type of knowledge. Journal of Experimental Psychology: Applied, 7, 317–330.

    Google Scholar 

  • Brown, P. M., & Dell, G. S. (1987). Adapting production to comprehension: The explicit mention of instruments. Cognitive Psychology, 19, 441–472.

    Article  Google Scholar 

  • Candlin, C. N., & Candlin, S. (2002). Discourse, expertise, and the management of risk in health care settings. Research on Language and Social Interaction, 35, 115–137.

    Article  Google Scholar 

  • Chi, M. T. H., Feltovich, P., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121–152.

    Article  Google Scholar 

  • Chi, M. T. H., Glaser, R., & Farr, M. (Eds.). (1988). The nature of expertise. Hillsdale, NJ: Lawrence Erlbaum.

  • Chi, M. T. H., Siler, S., & Jeong, H. (2004). Can tutors monitor students’ understanding accurately? Cognition and Instruction, 22, 363–387.

    Article  Google Scholar 

  • Chi, M. T. H., Siler, S., Jeong, H., Yamauchi, T., & Hausmann, R. G. (2001). Learning from human tutoring. Cognitive Science, 25, 471–533.

    Article  Google Scholar 

  • Clark, H. H. (1992). Arenas of language use. Chicago: University of Chicago Press.

    Google Scholar 

  • Clark, H. H. (1996). Using language. Cambridge: University Press.

    Google Scholar 

  • Clark, H. H., & Brennan, S. E. (1991). Grounding in communication. In L. B. Resnick, J. M. Levine, & S. D. Teasley (Eds.), Perspectives on socially shared cognition (pp. 127–149). Washington, DC: American Psychological Association.

  • Clark, H. H., & Murphy, G. L. (1982). Audience design in meaning and reference. In J. F. LeNy & W. Kintsch (Eds.), Language and comprehension (pp. 287–299). Amsterdam: North-Holland Publishing Company.

  • Cohen, P. A., Kulik, J. A., & Kulik, C. (1982). Educational outcomes of tutoring: A meta-analysis of findings. American Educational Research Journal, 19, 237–248.

    Article  Google Scholar 

  • Cramton, C. D. (2001). The mutual knowledge problem and its consequences for dispersed collaboration. Organization Science, 12, 346–371.

    Article  Google Scholar 

  • Erickson, F., & Schultz, J. (1982). The counselor as gatekeeper. Social interaction in interviews. New York: Academic Press.

    Google Scholar 

  • Fleiss, J. L. (1981). Statistical methods for rates and proportions. New York, NY: Wiley.

    Google Scholar 

  • Fussell, S. R., & Krauss, R. M. (1992). Coordination of knowledge in communication: Effects of speakers’ assumptions about what others know. Journal of Personality and Social Psychology, 62, 378–391.

    Article  Google Scholar 

  • Glass, M., Kim, J. H., Evens, M. E., Michael, J. A., & Rovick, A. A. (1999). Novice vs. expert tutors: A comparison of style. In Tenth midwest artificial intelligence and cognitive science conference (pp. 43–49). Bloomington, IN: AAAI Press.

  • Graesser, A. C., Léon, J. A., & Otero, J. C. (2002). Introduction to the psychology of science text comprehension. In J. Otero, J. A. Léon, & A. C. Graesser (Eds.), The psychology of science text comprehension (pp. 1–15). Mahwah, NJ: Lawrence Erlbaum.

  • Graesser, A. C., & McMahen, C. L. (1993). Anomalous information triggers questions when adults solve quantitative problems and comprehend stories. Journal of Educational Psychology, 85, 136–151.

    Article  Google Scholar 

  • Graesser, A. C., Person, N. K., & Huber, J. (1992). Mechanisms that generate questions. In T. Lauer, E. Peacock, & A. Graesser (Eds.), Questions and information systems (pp. 167–187). Hillsdale, NJ: Lawrence Erlbaum.

  • Hinds, P. J. (1999). The curse of expertise: The effects of expertise and debiasing methods on predictions of novice performance. Journal of Experimental Psychology: Applied, 5, 205–221.

    Article  Google Scholar 

  • Hinds, P. J., Patterson, M., & Pfeffer, J. (2001). Bothered by abstraction: The effect of expertise on knowledge transfer and subsequent knowledge performance. Journal of Applied Psychology, 86, 1232–1243.

    Article  Google Scholar 

  • Hinds, P. J., & Pfeffer, J. (2003). Why organizations don’t “know what they know”: Cognitive and motivational factors affecting the transfer of expertise. In M. Ackerman, V. Pipek, & V. Wulf (Eds.), Beyond knowledge management: Sharing expertise (pp. 3–26). Cambridge, MA: MIT Press.

  • Horton, W. S., & Gerrig, R. J. (2002). Speakers’ experiences and audience design: Knowing when and knowing how to adjust utterances to addressees. Journal of Memory and Language, 47, 589–606.

    Article  Google Scholar 

  • Horton, W. S., & Keysar, B. (1996). When do speakers take into account common ground? Cognition, 59, 91–117.

    Article  Google Scholar 

  • Isaacs, E. A., & Clark, H. H. (1987). References in conversation between experts and novices. Journal of Experimental Psychology: General, 116, 26–37.

    Article  Google Scholar 

  • Kintsch, W. (1994). Text comprehension, memory, and learning. American Psychologist, 49, 294–303.

    Article  Google Scholar 

  • Krauss, R. M., & Fussell, S. R. (1996). Social psychological models of interpersonal communication. In E. T. Higgins & A. Kruglanski (Eds.), Social psychology: A handbook of basic principles (pp. 655–701). New York: Guilford.

  • Lau, I. Y.-M., Chiu, C.-Y., & Hong, Y.-Y. (2001). I know what you know: Assumptions about others’ knowledge and their effects on message construction. Social Cognition, 19, 587–600.

    Article  Google Scholar 

  • Lebie, L., Rhoades, J. A., & McGrath, J. E. (1996). Interaction process in computer-mediated and face-to-face groups. Computer Supported Cooperative Work, 4, 127–152.

    Article  Google Scholar 

  • Macintosh, G., & Gentry, J. W. (1999). Decision making in personal selling: Testing the ‘K.I.S.S. principle’. Psychology & Marketing, 16, 393–408.

    Article  Google Scholar 

  • McNamara, D. S., Kintsch, E., Songer, N. B., & Kintsch, W. (1996). Are good texts always better? Interactions of text coherence, background knowledge, and levels of understanding in learning from text. Cognition and Instruction, 14, 1–43.

    Article  Google Scholar 

  • Nathan, M. J., & Koedinger, K. R. (2000). An investigation of teachers’ beliefs of students’ algebra development. Cognition and Instruction, 18, 209–237.

    Article  Google Scholar 

  • Nathan, M. J., & Petrosino, A. J. (2003). Expert blind spot among preservice teachers. American Educational Research Journal, 40, 905–928.

    Article  Google Scholar 

  • Nickerson, R. S. (1999). How we know – and sometimes misjudge – what others know: Imputing one’s own knowledge to others. Psychological Bulletin, 125, 737–759.

    Article  Google Scholar 

  • Nückles, M., & Bromme, R. (2002). Internet experts’ planning of explanations for laypersons: A web experimental approach in the Internet domain. Experimental Psychology, 49, 292–304.

    Google Scholar 

  • Nückles, M., & Stürz, A. (2006). The assessment tool. A method to support asynchronous communication between computer experts and laypersons. Computers in Human Behavior, 22, 917–940.

    Article  Google Scholar 

  • Nückles, M., Winter, A., Wittwer, J., Herbert, M., & Hübner, S. (2006). How do experts adapt their explanations to a layperson’s knowledge in asynchronous communication? An experimental study. User Modeling and User-Adapted Interaction, 16, 87–127.

    Article  Google Scholar 

  • Nückles, M., Wittwer, J., & Renkl, A. (2005). Information about a layperson’s knowledge supports experts in giving effective and efficient online advice to laypersons. Journal of Experimental Psychology: Applied, 11, 219–236.

    Article  Google Scholar 

  • Otero, J., & Graesser, A. C. (2001). PREG: Elements of a model of question asking. Cognition and Instruction, 19, 143–175.

    Article  Google Scholar 

  • Person, N. K., Graesser, A. C., Magliano, J. P., & Kreuz, R. J. (1994). Inferring what the student knows in one-to-one tutoring: The role of student questions and answers. Learning and Individual Differences, 6, 205–229.

    Article  Google Scholar 

  • Pickering, J. M., & Garrod, S. (2004). Toward a mechanistic psychology of dialogue. Behavioral and Brain Science, 27, 169–226.

    Google Scholar 

  • Reid, F. J. M., Malinek, V., Stott, C. J. T., & Evans, J. St. B. T. (1996). The messaging threshold in computer-mediated communication. Ergonomics, 39, 1017–1037.

    Article  Google Scholar 

  • Richter, T., Naumann, J., & Groeben, N. (2000). Attitudes toward the computer: Construct validation of an instrument with scales differentiated by content. Computers in Human Behavior, 16, 473–491.

    Article  Google Scholar 

  • Rikers, R. M. J. P., Schmidt, H. G., & Boshuizen, H. P. A. (2002). On the constraints of encapsulated knowledge: Clinical case representations by medical experts and subexperts. Cognition and Instruction, 20, 27–45.

    Article  Google Scholar 

  • Ross, L., Greene, D., & House, P. (1977). The ‘false consensus’ effect: An egocentric bias in social perception and attribution processes. Journal of Experimental Social Psychology, 13, 279–301.

    Article  Google Scholar 

  • Schober, M. F. (1998). Different kinds of conversational perspective-taking. In S. R. Fussell & R. J. Kreuz (Eds.), Social and cognitive psychological approaches to interpersonal communication (pp. 145–174). Mahwah, NJ: Lawrence Erlbaum.

  • Schober, M. F., & Brennan, S. E. (2003). Processes of interactive spoken discourse: The role of the partner. In A. C. Graesser, M. A. Gernsbacher, & S. R. Goldman (Eds.), The handbook of discourse processes (pp. 123–164). Mahwah, NJ: Lawrence Erlbaum.

  • Schober, M. F., & Clark, H. H. (1989). Understanding by addressees and overhearers. Cognitive Psychology, 21, 211–232.

    Article  Google Scholar 

  • Schulze, H. H. (2003). Computerlexikon [computer glossary]. Reinbek, Germany: Rowohlt.

  • Siler, S. A., & VanLehn, K. (2003). Accuracy of tutors’ assessments of their students by tutoring context. In R. Alterman & D. Kirsch (Eds.), Proceedings of the 25th annual conference of the cognitive science society. Mahwah, NJ: Erlbaum.

  • Simon, H. A., & Chase, W. G. (1973). Skill in chess. American Scientist, 61, 394–403.

    Google Scholar 

  • Stehr, N., & Ericson, R. V. (1992). The culture and power of knowledge – Inquiries into cotemporary societies. Berlin: de Gruyter.

    Google Scholar 

  • Tversky, A., & Kahneman, D. (1974). Judgement under uncertainty: Heuristics and biases. Science, 185, 1124–1131.

    Article  Google Scholar 

  • VanLehn, K., Siler, S., Murray, C., Yamauchi, T., & Baggett, W. B. (2003). Why do only some events cause learning during human tutoring? Cognition and Instruction, 21, 209–249.

    Article  Google Scholar 

  • Vidal-Abarca, E., & Sanjose, V. (1998). Levels of comprehension of scientific prose: The role of text variables. Learning and Instruction, 8, 215–233.

    Article  Google Scholar 

  • Voss, J. F., & Silfies, L. N. (1996). Learning from history text: The interaction of knowledge comprehension skill with text structure. Cognition and Instruction, 14, 45–68.

    Article  Google Scholar 

  • Wolfe, M. B., Schreiner, M. E., Rehder, B., Laham, D., Foltz, P. W., Kintsch, W., & Landauer, T. K. (1998). Learning from text: Matching readers and text by latent semantic analysis. Discourse Processes, 25, 309–336.

    Article  Google Scholar 

Download references

Acknowledgments

This research was supported by the Deutsche Forschungsgemeinschaft (DFG; [German Research Foundation]) with a project grant awarded to Matthias Nückles and Alexander Renkl (contract NU 129/1-1). We thank Tarik Gasmi for the programming of the assessment tool database system. Many thanks also go to our student research assistants, Christine Otieno, Isabel Braun, Eva März, and Sandra Hübner, for their help with many practical aspects of the project such as data collection and scoring. We also wish to thank Marcia Neff and Susan Bell for their proofreading.

Author information

Authors and Affiliations

  1. Department of Psychology, University of Freiburg, Engelbergerstraße 41, 79085, Freiburg, Germany

    Jörg Wittwer, Matthias Nückles & Alexander Renkl

  2. Leibniz Institute for Science Education at the University of Kiel, Olshausenstraße 62, 24098, Kiel, Germany

    Jörg Wittwer

Authors
  1. Jörg Wittwer
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Matthias Nückles
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Alexander Renkl
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jörg Wittwer.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wittwer, J., Nückles, M. & Renkl, A. Is underestimation less detrimental than overestimation? The impact of experts’ beliefs about a layperson’s knowledge on learning and question asking. Instr Sci 36, 27–52 (2008). https://doi.org/10.1007/s11251-007-9021-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11251-007-9021-x

Keywords

Search

Navigation