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The author or concept searched is found in the following 3 entries.
| Disputed term/author/ism | Author |
Entry |
Reference |
|---|---|---|---|
| Jigsaw Method | Psychological Theories | Haslam I 221 Jigsaw method/psychological theories: in the years since Aronson’s experiments (>Jigsaw method/Aronson; Aronson et al. (1)) research on the jigsaw classroom has continued to yield positive results in terms of enhanced academic performance and esteem, particularly among students from economically or educationally disadvantaged backgrounds, as well as improved intergroup relations within the classroom and the school (Johnson et al., 2000(2); Tomcho and Foels, 2012(3)). >E. Aronson, >Learning, >Learning theory, >Socialization, >Group behavior. It has been applied successfully to diverse topical Haslam I 222 areas such as English as a second language (ESL; Ghaith and El-Malak, 2004(4)) and physics classes (Hänze and Berger, 2007)(5), and positive results have been replicated internationally (Walker and Crogan, 1998)(6). Robert Cialdini initiated an influential set of studies on social influence that drew on observations of strategies used by individuals, such as salespeople, in applied settings, identified underlying psychological principles, and tested these ideas in field settings (Cialdini, 2009)(7). Also, basic research on attitudes and behaviour, such as the work of Ajzen and Fishbein’s (1980)(8) theory of reasoned action (…), significantly guided the development of effective interventions to change sexual practices and promote medical adherence to help curb the emerging international AIDS epidemic (Albarracin et al., 2001)(9). Ingroup relations: research on this topic was also inspired by the jigsaw classroom research; see Paluck and Green (2009)(10). Haslam I 223 Publications: Indeed, the earliest publications publications on the jigsaw classroom – also known as cooperative learning – were published in education journals rather than social psychological journals. Limitations of the method:/VsAronson: Aronson’s work spawned a new generation of cooperative learning interventions that were constructed to be effective in a wider range of classroom situations, not just under the specific circumstances associated with recently desegregated schools. These newer cooperation-based interventions were more generally effective educationally. So it was that when David Johnson and colleagues (2000)(2) ranked eight commonly used cooperation-based teaching methods in terms of their effectiveness the jigsaw classroom was only ranked sixth in terms of impact on educational achievement. By the early 1990s, 79% of US elementary schools used cooperative learning methods (Puma et al., 1993)(11) attests to the influence of the jigsaw classroom on policy implementation. >Jigsaw method/Social psychology. 1. Aronson, E., Stephan, C., Sikes, J., Blaney, N. and Snapp, M. (1978) The Jigsaw Classroom. Beverly Hills, CA: Sage. 2. Johnson, D., Johnson, R.T. and Stanne, M.B. (2000) ‘Cooperative learning methods: A meta-analysis’, https://www.researchgate.net/profile/David_Johnson50/publication/220040324_Cooperative_learning_methods_A_meta-analysis/links/00b4952b39d258145c000000.pdf (04.05. 2019)). 3. Tomcho, T.J. and Foels, R. (2012) ‘Meta-analysis of group learning activities: Empirically-based teaching recommendations’, Teaching of Psychology, 39: 159–69. 4. Ghaith, G. and El-Malak, M.A. (2004) ‘Effect of Jigsaw II on literal and higher-order EFL reading comprehension’, Educational Research and Evaluation, 10: 105–55. 5. Hänze, M. and Berger, R. (2007) ‘Cooperative learning, motivational effects, and student characteristics: An experimental study comparing cooperative learning and direct instruction in 12th grade physics classes“, Learning and instruction, 17: 29-41. 6. Walker, I. and Crogan, M. (1998) ‘Academic performance, prejudice, and the jigsaw classroom: New pieces to the puzzle’, Journal of Community & Applied Social Psychology, 8: 381–93. 7. Cialdini, R.B. (2009) Influence: Science and Practice (5th edn). New York: Pearson. 8. Ajzen, I. and Fishbein, M. (1980) Understanding Attitudes and Predicting Social Behavior: Attitudes, Intentions, and Perceived Behavioral Control. Englewood Cliffs, NJ: Prentice Hall. 9. Albarracin, D., Johnson, B.T., Fishbein, M. and Muellerleile, P.A. (2001) ‘Theories of reasoned action and planned behavior as models of condom use: A meta-analysis’. Psychological Bulletin, 127: 142–61. 10. Paluck, E.L. and Green, D.P. (2009), ‘Prejudice reduction: What works? A review and assessment of research and practice’, Annual Review of Psychology, 60: 339-67. 11. Puma M.J., Jones C.C., Rock D. and Fernandez, R. (1993) ‘Prospects: The congressionally mandated study of educational growth and opportunity’, Interim Report. Bethesda, MD: Abt Associates. John F. Dovidio, „ Promoting Positive Intergroup Relations. Revisiting Aronson et al.’s jigsaw classroom“, in: Joanne R. Smith and S. Alexander Haslam (eds.) 2017. Social Psychology. Revisiting the Classic studies. London: Sage Publications |
Haslam I S. Alexander Haslam Joanne R. Smith Social Psychology. Revisiting the Classic Studies London 2017 |
| Method | Aronson | Haslam I 254 Method/stereotype threat/Aronson, Joshua/Steele: (…) research on stereotype threat, beginning with the original paper by Steele and Aronson (1995)(7), has not been without critique. One aspect of that critique relates to how the original research has been described in media outlets, textbooks, and by scientists directly. stereotype threat. In their studies, Steele and Aronson covaried out participants’ prior performance on high-stakes standardized tests as assessed with their self-reported SAT (Scholastic Assessment Test) scores. This covariate analysis increases the power to detect the effect of a manipulation in the context of individual variation. However, critics have argued that this statistical caveat is too often lost in the retelling of the findings, leading people to report that the threat-free environment eliminates the racial gap in test performance (Sackett et al., 2004(1); Wicherts, 2005(2)). >Covariance, >Invariants. 1. VsAronson, Joshua/VsSteele: The problem with this conclusion is that by controlling for SAT, the authors have removed a portion of group performance differences and we simply do not know if stereotype threat or other factors led to this gap in the first place. A similar critique was lodged against Spencer et al.’s (1999)(3) research demonstrating stereotype threat impairments on highly identified women’s math performance (Stoet and Geary, 2012)(4). 2. VsAronson/VsSteele: Through the current lens of replicability, readers are increasingly skeptical of findings based on small sample sizes and effects that might seem to rely on the use of covariate analysis (Fraley and Vazire, 2014(5); Simonsohn et al., 2014(6)). 1. Sackett, P.R., Hardison, C.M. and Cullen, M.J. (2004) 10n interpreting stereotype threat as accounting for African American—White differences on cognitive tests’, American Psychologist, 59: 7—13. 2. Wicherts, J.M. (2005) 1Stereotype threat research and the assumptions underlying analysis of covariance, American Psychologist, 60 (3): 267—69. 3. Spencer, S.J., Steele, C.M. and Quinn, D.M. (1999) ‘Stereotype threat and women’s math performance’, Journal of Experimental Social Psychology, 35:4—28. 4. Stoet, G. and Geary, D.C. (2012) ‘Can stereotype threat explain the gender gap in mathematics performance and achievement?’, Review of General Psychology, 16:93—102. 5. Fraley, R.C. and Vazire, S. (2014) The N-pact factor: Evaluating the quality of empirical journals with respect to sample size and statistical power’, PLoS ONE, 9: e109019. 6. Simonsohn, U., Nelson, L.D. and Simmons, J.P. (2014) 4p-Curve and effect size correcting for publication bias using only significant results’, Perspectives on Psychological Science, 9 (6): 666—8 1. 7. Steele, C.M. and Aronson, J. (1995) ‘Stereotype threat and the intellectual test performance of African-Americans’, Journal of Personality and Social Psychology, 69: 797—811. Toni Schmader and Chad Forbes, “Stereotypes and Performance. Revisiting Steele and Aronson’s stereotypes threat experiments”, in: Joanne R. Smith and S. Alexander Haslam (eds.) 2017. Social Psychology. Revisiting the Classic Studies. London: Sage Publications |
Haslam I S. Alexander Haslam Joanne R. Smith Social Psychology. Revisiting the Classic Studies London 2017 |
| Method | Steele | Haslam I 254 Method/stereotype threat/Aronson, Joshua/Steele: (…) research on stereotype threat, beginning with the original paper by Steele and Aronson (1995), has not been without critique. One aspect of that critique relates to how the original research has been described in media outlets, textbooks, and by scientists directly. In their studies, Steele and Aronson covaried out participants’ prior performance on high-stakes standardized tests as assessed with their self-reported SAT (Scholastic Assessment Test) scores. This covariate analysis increases the power to detect the effect of a manipulation in the context of individual variation. However, critics have argued that this statistical caveat is too often lost in the retelling of the findings, leading people to report that the threat-free environment eliminates the racial gap in test performance (Sackett et al., 2004(1); Wicherts, 2005(2)). >Covariance, >Invariants. 1. VsAronson, Joshua/VsSteele: The problem with this conclusion is that by controlling for SAT, the authors have removed a portion of group performance differences and we simply do not know if stereotype threat or other factors led to this gap in the first place. A similar critique was lodged against Spencer et al.’s (1999)(3) research demonstrating stereotype threat impairments on highly identified women’s math performance (Stoet and Geary, 2012)(4). 2. VsAronson/VsSteele: Through the current lens of replicability, readers are increasingly skeptical of findings based on small sample sizes and effects that might seem to rely on the use of covariate analysis (Fraley and Vazire, 2014(5); Simonsohn et al., 2014(6)). 1. Sackett, P.R., Hardison, C.M. and Cullen, M.J. (2004) 10n interpreting stereotype threat as accounting for African American—White differences on cognitive tests’, American Psychologist, 59: 7—13. 2. Wicherts, J.M. (2005) 1Stereotype threat research and the assumptions underlying analysis of covariance, American Psychologist, 60 (3): 267—69. 3. Spencer, S.J., Steele, C.M. and Quinn, D.M. (1999) ‘Stereotype threat and women’s math performance’, Journal of Experimental Social Psychology, 35:4—28. 4. Stoet, G. and Geary, D.C. (2012) ‘Can stereotype threat explain the gender gap in mathematics performance and achievement?’, Review of General Psychology, 16:93—102. 5. Fraley, R.C. and Vazire, S. (2014) The N-pact factor: Evaluating the quality of empirical journals with respect to sample size and statistical power’, PLoS ONE, 9: e109019. 6. Simonsohn, U., Nelson, L.D. and Simmons, J.P. (2014) 4p-Curve and effect size correcting for publication bias using only significant results’, Perspectives on Psychological Science, 9 (6): 666—8 1. Toni Schmader and Chad Forbes, “Stereotypes and Performance. Revisiting Steele and Aronson’s stereotypes threat experiments”, in: Joanne R. Smith and S. Alexander Haslam (eds.) 2017. Social Psychology. Revisiting the Classic Studies. London: Sage Publications |
Haslam I S. Alexander Haslam Joanne R. Smith Social Psychology. Revisiting the Classic Studies London 2017 |
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