DOCSLIB.ORG

J University Microfilms, a XEROX Company, Ann Arbor, Michigan I

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
J University Microfilms, a XEROX Company, Ann Arbor, Michigan I 70-26,291 GRIEGER II, Russell Marvin, 1942- THE EFFECTS OF TEACHER EXPECTANCIES ON THE INTELLIGENCE OF STUDENTS AND THE BEHAVIOR OF TEACHERS. The Ohio State University, Ph.D., 1970 Education, psychology j University Microfilms, A XEROX Company, Ann Arbor, Michigan i THIS DISSERTATION HAS BEEN MICROFILMED EXACTLY AS RECEIVED THE EFFECTS OF TEACHER EXPECTANCIES ON THE INTELLIGENCE OF STUDENTS AND THE BEHAVIOR OF TEACHERS DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Russell Marvin Grieger II, B.A., M.A. «##««*#« The Ohio State University 1970 Approved by Advisor Department of Psychology ACKNOWLEDGEMENTS This paper is lovingly dedicated, to my parents, Russell and Florence Grieger, and to my wife, Tanya. Mom and Dad, through their constant guidance, trust and confidence, provided a motivation for growth and a sense of Joy and pride in accomplishment. Tanya, through her untiring patience and affection, made this venture, and many others, both pleasant and rewarding. To them I shall always be grateful. Gratitude is also expressed to Dr. Donald C. Smith, m y advisor, for direction in the writing of this paper. More important, deep thanks are extended to him for the five years of guidance and friendship that contributed to my personal as well as professional growth. Special thanks go to Dr. Robert Wherry for advice concerning the statistical analysis of the data. Thanks are also extended to Mark Fulcomerfor help in the analysis. Appreciation Is offered to those people who contributed technical assistance to this study. Specifically, Michael Amann, William Callahan, Ellen Hoch, Edward Ladon, Eleanor Lynch, Rosalee Zukosd, Laura Titus, Lawrence Venham; and Linda Zenar diligently conducted the observations, and Eileen Brown and Carol DeLong scored the tests. ii Finally, special thankB go to the teachers of the Jonathan Alder District of the Plain City (Ohio) School System for allowing me to invade their classrooms. iii VITA February 6 , 19^+2.......................... Born: Evansville, Indiana. 196 5...................................... B.A. : Evansville College, Evansville, Indiana. 1966 ...................................... M.A. : The Ohio State University, Columbus, Ohio. 1966-68........... ........................ Child clinical trainee, Children's Hospital, Columbus, Ohio. 1968-6 9 ................................... School Psychology/Child- clinical internship, The Devereux Found­ ation, Devon, Pa. 1969-70 .............................. .Teaching Associate, Department of Psychology, The Ohio State University, Columbus, Ohio. FIELDS OF STUDY School Major Field Minor Field Evansville College Psychology Sociology English Literature The Ohio State University (HA) School Psychology The Ohio State University (PhD) School Psychology iv PUBLICATIONS Grieger, R.M. II. Behavior modifications with a total class: a case report. Article to be published in the Journal of School Psychology, 1970. Grieger, R., Mordock, J.R., and Breyer, N. General guidelines for conducting behavior modification programs in public school settings. Article accepted for publication in the Journal of School Psychology, 1970. v TABLE OF CONTENTS Page ACKNOWLEDGEMENTS............................................ li VITA........................................................iv LIST OF TABLES.............................................. viii LIST OF FIGURES............................................. ix Chapter I. INTRODUCTION TO THE PROBLEM.......................... 1 II. REVIEW OF THE LITERATURE............................. 7 The Self-fulfilling Prophecy io Everyday Life......... 7 Experimenter Bias in Research on Animal Behavior...... 10 Experimenter Bias in Research on Human Behavior....... lU Factors Accounting for the Experimenter Bias.......... 22 Summary and Critique of Experimenter Bias Research.... 3l* The Teacher Expectancy Effect..... .................. 37 Summary and Evaluation of Teacher Expectancy Research,, ,1*5 III. PROCEDURES.......................................... 1*9 Subjects............................................ 1*9 Instruments......................................... 51 Procedures for Collection of Data.................... 57 Major Hypotheses and Statistical Analysis............. 62 IV. RESULTS............................................. 67 Teacher Behavior In Relation to Teacher Bias.......... 67 Intelligence Quotient in Relation to Teacher Bias..... 70 Subject sex as a Variable............................ 75 Teacher Recall of’^loomers”.............. ............ 79 Summary of Results...... ............................ 30 vi Page V. SUMMARY AMD CONCLUSIONS............................... 82 Summary.............................................. 82 Discussion of the Results............................. 87 Conclusions and Recommendations....................... 95 APPENDIX..................................................... 99 BIBLIOGRAPHY................................................. 115 vli LIST OF TABLES Table Page 1 Descriptive Data on Teachers.......................51 2 Number of Students in the Total District, Experimental Group, and Control Group by Sex and Grade.....................................52 3 Means and Standard Deviations of Pretest Total IQs of the Experimental and Control Groups Students at Each Grade Level...................... 5^ U Analysis of Variance Summary Table for Positive Teacher Behaviors.................................68 5 Mean Frequency of Positive Teacher Behaviors for The Control and Experimental Groups............... 69 6 Frequency of Positive Teacher Behaviors for the Pre-bias and Post-bias Observation Periods by Grade and Group Membership........................ 71 7 Analysis of Variance Summary Table for Total IQ............................................... 73 8 Mean IQ Scores for Pre-bias and Post-bias Periods by Grade and Group Membership..................... 7^ 9 Point Biserial Coefficients of Correlation Between Sex and Pre-biaB Frequency of Positive Teacher Behavior by Grade and Group Membership............ 79 10 Point Biserial Coefficients of Correlation Between Sex and Pre-bias Frequency of Positive Teacher Behavior by Grade and Group Membership.... 79 11 Percentage of Experimental Group Children Recalled by Teachers at Each Grade Level....... ...80 viil LIST OF FIGURES Figure Page 1 Basic Design for the Statistical Analysis of the Data......................................... 65 2 Mean Pre- and Post-Mas Frequency of Teacher Behavior by Grade............... ................ 12 3 Mean Pre- and Post-bias Total IQs by Grade.........16 ix CHAPTER I INTRODUCTION TO THE PROBLEM It is a fact of life that people behave In a predictahle way. Societal norms, group pressures, and inner expectations of success or failure, among other things, serve to order and control a person's behavior. In addition, evidence suggests that one person's expectations concerning another's behavior often serves to Increase the probability of the other's behaviorf in other words, to act as a self-fulfilling prophecy (Merton, 1948; Rosenthal, 1966), Most of the systematic evidence concerning the self-fulfilling prophecy comes from laboratory situations where researchers have shown that the expectancies of a behavioral scientist can significantly Influence the outcome of his experiments, These instances of the self-fulfilling prophecy have heen termined the experimenter bias or experimenter expectancy effect, A large proportion of experimenter expectancy studies employed a standardized taak of person perception, For example, Rosenthal and Fode (1963) assigned 20 graduate student experimenters to ahow a serlea of ten photographa of peoples' faces to introductory psychology students, Each experimenter had ten subjects, The subject was to rate the degree of success or failure showing in the face of I 2 each pictured person on a scale from -IQ to +10 (-10- meaning extreme failure and +10 meaning extreme success), The photos had been selected so they would he neutral with an average score of zero. While all experimenters were given identical Instructions on administration and were told not to deviate, half were told that well established findings showed that most subjects should rate the photos as being of successful people (+5) and half were told that the subjects should rate the photos as being of unsuccessful people. As expected, those experimenters expecting higher photo ratings did, in fact, obtain higher ratings than did experimenters expecting lower photo ratings. Rosenthal and Fode (1963a) also illustrated the experimenter expectancy effect in a study of maze running in rats. Using an experimental psychology class, the authors told half the students that their rats were "maze bright" and half that their rats were "maze dull." Actually, all rats were "perfectly ordinary laboratory rats." Results showed that from the first day, and continuing through the experiment, rats believed to be maze bright performed significantly better than the other rats (p^.Ol). Further, those experimenters who were led to believe they had bright rats reported that they viewed their rats as more likeable and pleasant, and described their behavior toward the rats as more friendly and enthusiastic. 3 Barber and Silver (1968), however, doubted that the expectancy phenomenon was as pervasive and general as Rosenthal and others claimed. They analyzed the design and data of 31 studies purporting to demonstrate the experimenter expectancy
Load more

Recommended publications
  • (HCW) Surveys in Humanitarian Contexts in Lmics
    Analytics for Operations working group GUIDANCE BRIEF Guidance for Health Care Worker (HCW) Surveys in humanitarian contexts in LMICs Developed by the Analytics for Operations Working Group to support those working with communities and healthcare workers in humanitarian and emergency contexts. This document has been developed for response actors working in humanitarian contexts who seek rapid approaches to gathering evidence about the experience of healthcare workers, and the communities of which they are a part. Understanding healthcare worker experience is critical to inform and guide humanitarian programming and effective strategies to promote IPC, identify psychosocial support needs. This evidence also informs humanitarian programming that interacts with HCWs and facilities such as nutrition, health reinforcement, communication, SGBV and gender. In low- and middle-income countries (LMIC), healthcare workers (HCW) are often faced with limited resources, equipment, performance support and even formal training to provide the life-saving work expected of them. In humanitarian contexts1, where human resources are also scarce, HCWs may comprise formally trained doctors, nurses, pharmacists, dentists, allied health professionals etc. as well as community members who perform formal health worker related duties with little or no trainingi. These HCWs frequently work in contexts of multiple public health crises, including COVID-19. Their work will be affected by availability of resources (limited supplies, materials), behaviour and emotion (fear), flows of (mis)information (e.g. understanding of expected infection prevention and control (IPC) measures) or services (healthcare policies, services and use). Multiple factors can therefore impact patients, HCWs and their families, not only in terms of risk of exposure to COVID-19, but secondary health, socio-economic and psycho-social risks, as well as constraints that interrupt or hinder healthcare provision such as physical distancing practices.
    [Show full text]
  • Nonresponse Bias and Trip Generation Models
    64 TRANSPORTATION RESEARCH RECORD 1412 Nonresponse Bias and Trip Generation Models PIYUSHIMITA THAKURIAH, As:H1sH SEN, SnM S66T, AND EDWARD CHRISTOPHER There is serious concern over the fact that travel surveys often On the other hand, if the model does not satisfy these con­ overrepresent smaller households with higher incomes and better ditions, bias will occur even if there is a 100 percent response education levels and, in general, that nonresponse is nonrandom. rate. These conditions are satisfied by the model if the func­ However, when the data are used to build linear models, such as trip generation models, and the model is correctly specified, tional form of the model is correct and all important explan­ estimates of parameters are unbiased regardless of the nature of atory variables are included. the respondents, and the issues of how response rates and non­ Because categorical models do not have any problems with response bias are ameliorated. The more important task then is their functional form, and weighting and related issues are the complete specification of the model, without leaving out var­ taken care of, the authors prefer categorical trip generation iables that have some effect on the variable to be predicted. The models. This preference is discussed in a later section. There­ theoretical basis for this reasoning is given along with an example fore, the issue that remains when assessing bias in estimates of how bias may be assessed in estimates of trip generation model parameters. Some of the methods used are quite standard, but from categorical trip generation models is whether the model the manner in which these and other more nonstandard methods includes all the relevant independent variables or at least all have been systematically put together to assess bias in estimates important predictors.
    [Show full text]
  • Equally Flexible and Optimal Response Bias in Older Compared to Younger Adults
    AGING AND RESPONSE BIAS Equally Flexible and Optimal Response Bias in Older Compared to Younger Adults Roderick Garton, Angus Reynolds, Mark R. Hinder, Andrew Heathcote Department of Psychology, University of Tasmania Accepted for publication in Psychology and Aging, 8 February 2019 © 2019, American Psychological Association. This paper is not the copy of record and may not exactly replicate the final, authoritative version of the article. Please do not copy or cite without authors’ permission. The final article will be available, upon publication, via its DOI: 10.1037/pag0000339 Author Note Roderick Garton, Department of Psychology, University of Tasmania, Sandy Bay, Tasmania, Australia; Angus Reynolds, Department of Psychology, University of Tasmania, Sandy Bay, Tasmania, Australia; Mark R. Hinder, Department of Psychology, University of Tasmania, Sandy Bay, Tasmania, Australia; Andrew Heathcote, Department of Psychology, University of Tasmania, Sandy Bay, Tasmania, Australia. Correspondence concerning this article should be addressed to Roderick Garton, University of Tasmania Private Bag 30, Hobart, Tasmania, Australia, 7001. Email: [email protected] This study was supported by Australian Research Council Discovery Project DP160101891 (Andrew Heathcote) and Future Fellowship FT150100406 (Mark R. Hinder), and by Australian Government Research Training Program Scholarships (Angus Reynolds and Roderick Garton). The authors would like to thank Matthew Gretton for help with data acquisition, Luke Strickland and Yi-Shin Lin for help with data analysis, and Claire Byrne for help with study administration. The trial-level data for the experiment reported in this manuscript are available on the Open Science Framework (https://osf.io/9hwu2/). 1 AGING AND RESPONSE BIAS Abstract Base-rate neglect is a failure to sufficiently bias decisions toward a priori more likely options.
    [Show full text]
  • Guidance for Health Care Worker (HCW) Surveys in Humanitarian
    Analytics for Operations & COVID-19 Research Roadmap Social Science working groups GUIDANCE BRIEF Guidance for Health Care Worker (HCW) Surveys in humanitarian contexts in LMICs Developed by the Analytics for Operations & COVID-19 Research Roadmap Social Science working groups to support those working with communities and healthcare workers in humanitarian and emergency contexts. This document has been developed for response actors working in humanitarian contexts who seek rapid approaches to gathering evidence about the experience of healthcare workers, and the communities of which they are a part. Understanding healthcare worker experience is critical to inform and guide humanitarian programming and effective strategies to promote IPC, identify psychosocial support needs. This evidence also informs humanitarian programming that interacts with HCWs and facilities such as nutrition, health reinforcement, communication, SGBV and gender. In low- and middle-income countries (LMIC), healthcare workers (HCW) are often faced with limited resources, equipment, performance support and even formal training to provide the life-saving work expected of them. In humanitarian contexts1, where human resources are also scarce, HCWs may comprise formally trained doctors, nurses, pharmacists, dentists, allied health professionals etc. as well as community members who perform formal health worker related duties with little or no trainingi. These HCWs frequently work in contexts of multiple public health crises, including COVID-19. Their work will be affected
    [Show full text]
  • Straight Until Proven Gay: a Systematic Bias Toward Straight Categorizations in Sexual Orientation Judgments
    ATTITUDES AND SOCIAL COGNITION Straight Until Proven Gay: A Systematic Bias Toward Straight Categorizations in Sexual Orientation Judgments David J. Lick Kerri L. Johnson New York University University of California, Los Angeles Perceivers achieve above chance accuracy judging others’ sexual orientations, but they also exhibit a notable response bias by categorizing most targets as straight rather than gay. Although a straight categorization bias is evident in many published reports, it has never been the focus of systematic inquiry. The current studies therefore document this bias and test the mechanisms that produce it. Studies 1–3 revealed the straight categorization bias cannot be explained entirely by perceivers’ attempts to match categorizations to the number of gay targets in a stimulus set. Although perceivers were somewhat sensitive to base rate information, their tendency to categorize targets as straight persisted when they believed each target had a 50% chance of being gay (Study 1), received explicit information about the base rate of gay targets in a stimulus set (Study 2), and encountered stimulus sets with varying base rates of gay targets (Study 3). The remaining studies tested an alternate mechanism for the bias based upon perceivers’ use of gender heuristics when judging sexual orientation. Specifically, Study 4 revealed the range of gendered cues compelling gay judgments is smaller than the range of gendered cues compelling straight judgments despite participants’ acknowledgment of equal base rates for gay and straight targets. Study 5 highlighted perceptual experience as a cause of this imbalance: Exposing perceivers to hyper-gendered faces (e.g., masculine men) expanded the range of gendered cues compelling gay categorizations.
    [Show full text]
  • Running Head: EXTRAVERSION PREDICTS REWARD SENSITIVITY
    Running head: EXTRAVERSION PREDICTS REWARD SENSITIVITY Extraversion but not Depression Predicts Reward Sensitivity: Revisiting the Measurement of Anhedonic Phenotypes Submitted: 6/xx/2020 EXTRAVERSION PREDICTS REWARD SENSITIVITY 2 Abstract RecentLy, increasing efforts have been made to define and measure dimensionaL phenotypes associated with psychiatric disorders. One example is a probabiListic reward task deveLoped by PizzagaLLi et aL. (2005) to assess anhedonia, by measuring participants’ responses to a differentiaL reinforcement schedule. This task has been used in many studies, which have connected blunted reward response in the task to depressive symptoms, across cLinicaL groups and in the generaL population. The current study attempted to replicate these findings in a large community sample and aLso investigated possible associations with Extraversion, a personaLity trait Linked theoreticaLLy and empiricaLLy to reward sensitivity. Participants (N = 299) completed the probabiListic reward task, as weLL as the Beck Depression Inventory, PersonaLity Inventory for the DSM-5, Big Five Inventory, and Big Five Aspect ScaLes. Our direct replication attempts used bivariate anaLyses of observed variables and ANOVA modeLs. FolLow-up and extension anaLyses used structuraL equation modeLs to assess reLations among Latent reward sensitivity, depression, Extraversion, and Neuroticism. No significant associations were found between reward sensitivity (i.e., response bias) and depression, thus faiLing to replicate previous findings. Reward sensitivity (both modeLed as response bias aggregated across blocks and as response bias controlLing for baseLine) showed positive associations with Extraversion, but not Neuroticism. Findings suggest reward sensitivity as measured by this probabiListic reward task may be reLated primariLy to Extraversion and its pathologicaL manifestations, rather than to depression per se, consistent with existing modeLs that conceptuaLize depressive symptoms as combining features of Neuroticism and low Extraversion.
    [Show full text]
  • Prior Belief Innuences on Reasoning and Judgment: a Multivariate Investigation of Individual Differences in Belief Bias
    Prior Belief Innuences on Reasoning and Judgment: A Multivariate Investigation of Individual Differences in Belief Bias Walter Cabral Sa A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Graduate Department of Education University of Toronto O Copyright by Walter C.Si5 1999 National Library Bibliothèque nationaIe of Canada du Canada Acquisitions and Acquisitions et Bibliographic Services services bibliographiques 395 Wellington Street 395, rue WePington Ottawa ON K1A ON4 Ottawa ON KtA ON4 Canada Canada Your file Votre rëfërence Our fi& Notre réterence The author has granted a non- L'auteur a accordé une licence non exclusive Licence allowing the exclusive permettant à la National Libraq of Canada to Bibliothèque nationale du Canada de reproduce, loan, distribute or sell reproduire, prêter, distribuer ou copies of this thesis in microforni, vendre des copies de cette thèse sous paper or electronic formats. la forme de microfiche/film, de reproduction sur papier ou sur format électronique. The author retains ownership of the L'auteur conserve la propriété du copyright in this thesis. Neither the droit d'auteur qui protège cette thèse. thesis nor subçtantial extracts fi-om it Ni la thèse ni des extraits substantiels may be printed or otherwise de celle-ci ne doivent être imprimés reproduced without the author's ou autrement reproduits sans son permission. autorisation. Prior Belief Influences on Reasoning and Judgment: A Multivariate Investigation of Individual Differences in Belief Bias Doctor of Philosophy, 1999 Walter Cabral Sa Graduate Department of Education University of Toronto Belief bias occurs when reasoning or judgments are found to be overly infiuenced by prior belief at the expense of a normatively prescribed accommodation of dl the relevant data.
    [Show full text]
  • Thinking and Reasoning
    Thinking and Reasoning Thinking and Reasoning ■ An introduction to the psychology of reason, judgment and decision making Ken Manktelow First published 2012 British Library Cataloguing in Publication by Psychology Press Data 27 Church Road, Hove, East Sussex BN3 2FA A catalogue record for this book is available from the British Library Simultaneously published in the USA and Canada Library of Congress Cataloging in Publication by Psychology Press Data 711 Third Avenue, New York, NY 10017 Manktelow, K. I., 1952– Thinking and reasoning : an introduction [www.psypress.com] to the psychology of reason, Psychology Press is an imprint of the Taylor & judgment and decision making / Ken Francis Group, an informa business Manktelow. p. cm. © 2012 Psychology Press Includes bibliographical references and Typeset in Century Old Style and Futura by index. Refi neCatch Ltd, Bungay, Suffolk 1. Reasoning (Psychology) Cover design by Andrew Ward 2. Thought and thinking. 3. Cognition. 4. Decision making. All rights reserved. No part of this book may I. Title. be reprinted or reproduced or utilised in any BF442.M354 2012 form or by any electronic, mechanical, or 153.4'2--dc23 other means, now known or hereafter invented, including photocopying and 2011031284 recording, or in any information storage or retrieval system, without permission in writing ISBN: 978-1-84169-740-6 (hbk) from the publishers. ISBN: 978-1-84169-741-3 (pbk) Trademark notice : Product or corporate ISBN: 978-0-203-11546-6 (ebk) names may be trademarks or registered trademarks, and are used
    [Show full text]
  • Validity & Ethics
    Experimenter Expectancy Effects Data Collection: Validity & Ethics A kind of “self-fulfilling prophesy” during which researchers unintentionally “produce the results they want”. Two kinds… Data Integrity Modifying Participants’ Behavior – Expectancy effects & their control • Experimenter expectancy effects – Subtle differences in treatment of participants in different • Participant Expectancy Effects conditions can change their behavior… • Single- and Double-blind designs – Inadvertently conveying response expectancies/research – Researcher and Participant Bias & their control hypotheses • Reactivity & Response Bias – Problems with participants – Difference in performance due to differential quality of • Observer Bias & Interviewer Bias – Problems w/ researchers instruction or friendliness of the interaction – Effects of attrition on initial equivalence Data Collection Bias (much like observer bias) • Ethical Considerations – Many types of observational and self-report data need to be – Informed Consent “coded” or “interpreted” before they can be analyzed – Researcher Honesty – Subjectivity and error can creep into these interpretations – usually leading to data that are biased toward expectations – Levels of Disclosure Participant Expectancy Effects A kind of “demand characteristic” during which participants modify their behavior to respond/conform to “how they should act”. Two kinds… Social Desirability – When participants intentionally or unintentionally modify their behavior to match “how they are expected to behave” – Well-known
    [Show full text]
  • Why Do Humans Reason? Arguments for an Argumentative Theory
    University of Pennsylvania ScholarlyCommons Goldstone Research Unit Philosophy, Politics and Economics 4-2011 Why Do Humans Reason? Arguments for an Argumentative Theory Hugo Mercier University of Pennsylvania, [email protected] Dan Sperber Follow this and additional works at: https://repository.upenn.edu/goldstone Part of the Epistemology Commons, and the Psychology Commons Recommended Citation Mercier, H., & Sperber, D. (2011). Why Do Humans Reason? Arguments for an Argumentative Theory. Behavioral and Brain Sciences, 34 (2), 57-74. http://dx.doi.org/10.1017/S0140525X10000968 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/goldstone/15 For more information, please contact [email protected]. Why Do Humans Reason? Arguments for an Argumentative Theory Abstract Reasoning is generally seen as a means to improve knowledge and make better decisions. However, much evidence shows that reasoning often leads to epistemic distortions and poor decisions. This suggests that the function of reasoning should be rethought. Our hypothesis is that the function of reasoning is argumentative. It is to devise and evaluate arguments intended to persuade. Reasoning so conceived is adaptive given the exceptional dependence of humans on communication and their vulnerability to misinformation. A wide range of evidence in the psychology of reasoning and decision making can be reinterpreted and better explained in the light of this hypothesis. Poor performance in standard reasoning tasks is explained by the lack of argumentative context. When the same problems are placed in a proper argumentative setting, people turn out to be skilled arguers. Skilled arguers, however, are not after the truth but after arguments supporting their views.
    [Show full text]
  • Better but Still Biased: Analytic Cognitive Style and Belief Bias
    Thinking & Reasoning ISSN: 1354-6783 (Print) 1464-0708 (Online) Journal homepage: http://www.tandfonline.com/loi/ptar20 Better but still biased: Analytic cognitive style and belief bias Dries Trippas, Gordon Pennycook, Michael F. Verde & Simon J. Handley To cite this article: Dries Trippas, Gordon Pennycook, Michael F. Verde & Simon J. Handley (2015) Better but still biased: Analytic cognitive style and belief bias, Thinking & Reasoning, 21:4, 431-445, DOI: 10.1080/13546783.2015.1016450 To link to this article: http://dx.doi.org/10.1080/13546783.2015.1016450 View supplementary material Published online: 19 Mar 2015. Submit your article to this journal Article views: 474 View related articles View Crossmark data Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=ptar20 Download by: [University of Plymouth] Date: 06 January 2016, At: 05:50 Thinking & Reasoning, 2015 Vol. 21, No. 4, 431À445, http://dx.doi.org/10.1080/13546783.2015.1016450 Better but still biased: Analytic cognitive style and belief bias Dries Trippas1, Gordon Pennycook2, Michael F. Verde3, and Simon J. Handley3 1Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany 2Department of Psychology, University of Waterloo, Waterloo, Ontario, Canada 3Cognition Institute, Plymouth University, Devon, UK Belief bias is the tendency for prior beliefs to influence people’s deductive reasoning in two ways: through the application of a simple belief-heuristic (response bias) and through the application of more effortful reasoning for unbelievable conclusions (accuracy effect or motivated reasoning). Previous research indicates that cognitive ability is the primary determinant of the effect of beliefs on accuracy.
    [Show full text]
  • Tilburg University Response Styles in Rating Scales Van Herk, H
    Tilburg University Response styles in rating scales van Herk, H.; Poortinga, Y.H.; Verhallen, T.M.M. Published in: Journal of Cross-Cultural Psychology Publication date: 2004 Link to publication in Tilburg University Research Portal Citation for published version (APA): van Herk, H., Poortinga, Y. H., & Verhallen, T. M. M. (2004). Response styles in rating scales: Evidence of method bias in data from 6 EU countries. Journal of Cross-Cultural Psychology, 35(3), 346-360. General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Download date: 26. sep. 2021 RESPONSE STYLES IN EU COUNTRIES 1 Version: November 27, 2003 Response Styles In Rating Scales: Evidence of Method Bias in Data from 6 EU Countries Hester van Herk Ype H. Poortinga Theo M.M. Verhallen Hester van Herk is Assistant Professor of Marketing, Vrije Universiteit Amsterdam, Ype H. Poortinga is Professor of Psychology at Tilburg University and at Leuven University Belgium, Theo M.
    [Show full text]