1.1. What Does the SAT Measure?
1.2. What Is the Impact of Teachers and Classrooms after Accounting for g?
1.3. The Fallacy of the Neglected Aspect
2. Study 1: A Higher Education “g Vector”: Colleges Distributed by General Ability
2.1. Sample 1: U.S. News & World Report SAT and ACT Scores for Colleges and Universities
3. Study 2: College Attendance as a Proxy for General Ability to Study Other Groups
3.1. Sample 2: U.S. Occupationally Select Groups and the SAT and ACT Scores of the Colleges and Universities They Attended
4.1. Study 1
4.2. Study 2
5.1. Standardized Tests Throughout Education as Proxy Measures of g
5.2. Cognitive Segregation in Higher Education and Society
5.3. Standardized Tests, When Used to Test all Students, Improves the Identification of Disadvantaged Students
5.4. The Importance of Other Individual Differences Beyond g
5.5. Accounting for g in Educational Observational Studies and Interventions
Conflicts of Interest
- Kelley, T.L. Interpretation of Educational Measurements; World Book Company: Yonkers, NY, USA, 1927. [Google Scholar]
- Coleman, W.; Cureton, E.E. Intelligence and achievement: The “jangle fallacy” again. Educ. Psychol. Meas. 1954, 14, 347–351. [Google Scholar] [CrossRef]
- Gottfredson, L.S. Schools and the g factor. Wilson Quart. 2004, 28, 35–45. [Google Scholar]
- Jensen, A.R. Straight Talk about Mental Tests; The Free Press: New York, NY, USA, 1981. [Google Scholar]
- Murray, C. Real Education: Four Simple Truths for Bringing America’s Schools Back to Reality; Crown Forum: New York, NY, USA, 2008. [Google Scholar]
- National Research Council. Ability Testing: Uses, Consequences, and Controversies; The National Academies Press: Washington, DC, USA, 1982. [Google Scholar]
- Zwick, R. Is the SAT a ‘wealth test’? Phi Delta Kappan 2002, 84, 307–311. [Google Scholar] [CrossRef]
- Kohn, A. Two Cheers for an End to the SAT. Chronicle Higher Educ. 2011. Available online: https://www.chronicle.com/article/Two-Cheers-for-an-End-to-the/15930 (accessed on 27 July 2018).
- Colvin, R.L. Q & A: Should UC do away with the SAT? Los Angeles Times. 1997. Available online: http://articles.latimes.com/1997/oct/01/local/me-38061 (accessed on 27 July 2018).
- Frey, M.C.; Detterman, D.K. Scholastic assessment or g? The relationship between the Scholastic Assessment Test and general cognitive ability. Psychol. Sci. 2004, 15, 373–378. [Google Scholar] [CrossRef] [PubMed]
- Koenig, K.A.; Frey, M.C.; Detterman, D.K. ACT and general cognitive ability. Intelligence 2008, 36, 153–160. [Google Scholar] [CrossRef]
- Beaujean, A.A.; Firmin, M.W.; Knoop, A.J.; Michonski, J.D.; Berry, T.P.; Lowrie, R.E. Validation of the Frey and Detterman (2004) IQ prediction equations using the Reynolds Intellectual Assessment Scales. Personal. Individ. Differ. 2006, 41, 353–357. [Google Scholar] [CrossRef]
- Hsu, S.D.H.; Schombert, J. Data mining the university: College GPA predictions from SAT scores. arXiv, 2010; arXiv:1004.2731v1. [Google Scholar] [CrossRef]
- Angoff, W.H.; Johnson, E.G. The differential impact of curriculum on aptitude test scores. J. Educ. Meas. 1990, 27, 291–305. [Google Scholar] [CrossRef]
- Hunt, E. Teaching intelligence: Why, why it is hard and perhaps how to do it. Intelligence 2014, 42, 156–165. [Google Scholar] [CrossRef]
- Kuncel, N.R.; Hezlett, S.A.; Ones, D.S. Academic performance, career potential, creativity, and job performance. Can one construct predict them all? J. Person. Soc. Psychol. 2004, 86, 148–161. [Google Scholar] [CrossRef] [PubMed]
- Lubinski, D. Cognitive epidemiology: With emphasis on untangling cognitive ability and socioeconomic status. Intelligence 2009, 37, 625–633. [Google Scholar] [CrossRef]
- Strauss, V. Why the new SAT scores are meaningless. The Washington Post. 2013. Available online: https://www.washingtonpost.com/news/answer-sheet/wp/2013/09/26/why-the-new-sat-scores-are-meaningless/?utm_term=.25ad351d4551 (accessed on 27 July 2018).
- Hoxby, C.; Avery, C. The missing “one-offs”: The hidden supply of high-achieving low-income students. Brook. Papers Econ. Act. Spring 2013, 1–65. [Google Scholar] [CrossRef]
- Card, D.; Giuliano, L. Universal screening increases the representation of low-income and minority students in gifted education. Proc. Natl. Acad. Sci. USA 2016, 113, 13678–13683. [Google Scholar] [CrossRef] [PubMed]
- Dynarski, S.M. ACT/Sat for all: A cheap, effective way to narrow income gaps in college. Brookings 2018. Available online: https://www.brookings.edu/research/act-sat-for-all-a-cheap-effective-way-to-narrow-income-gaps-in-college/ (accessed on 27 July 2018).
- Grissom, J.A.; Redding, C. Discretion and disproportionality: Explaining the underrepresentation of high-achieving students of color in gifted programs. AERA Open 2016, 2, 1–25. [Google Scholar] [CrossRef]
- McBee, M.T.; Peters, S.J.; Miller, E.M. The impact of the nomination stage on gifted program identification. Gifted Child. Quart. 2016, 60, 258–278. [Google Scholar] [CrossRef]
- Carroll, J.B. Human Cognitive Abilities: A Survey of Factor Analytic Studies; Cambridge University Press: Cambridge, UK, 1993. [Google Scholar]
- Detterman, D.K. Education and intelligence: Pity the poor teacher because student characteristics are more significant than teachers or schools. Span. J. Psychol. 2016, 19, E93. [Google Scholar] [CrossRef] [PubMed]
- Chabris, C.F. Cognitive and neurobiological mechanisms of the law of general intelligence. In Integrating the Mind: Domain General Versus Domain Specific Processes in Higher Cognition; Roberts, M.J., Ed.; Psychology Press: New York, NY, USA, 2007; pp. 449–491. [Google Scholar]
- Jensen, A.R. The g Factor: The Science of Mental Ability; Praeger: Westport, CT, USA, 1998. [Google Scholar]
- Spearman, C. The Abilities of Man: Their Nature and Measurement; Macmillan: New York, NY, USA, 1927. [Google Scholar]
- Ree, M.J.; Earles, J.A. The stability of g across different methods of estimation. Intelligence 1991, 15, 271–278. [Google Scholar] [CrossRef]
- Johnson, W.; Bouchard, T.J.; Krueger, R.F.; McGue, M.; Gottesman, I.I. Just one g: Consistent results from three test batteries. Intelligence 2004, 32, 95–107. [Google Scholar] [CrossRef]
- Schult, J.; Sparfeldt, J.R. Do non-g factors of cognitive ability tests align with specific academic achievements? A combined bifactor modeling approach. Intelligence 2016, 59, 96–102. [Google Scholar] [CrossRef]
- Kaufman, S.B.; Reynolds, M.R.; Liu, X.; Kaufman, A.S.; McGrew, K.S. Are cognitive g and academic achievement g one and the same g? An exploration on the Woodcock-Johnson and Kaufman tests. Intelligence 2012, 40, 123–138. [Google Scholar] [CrossRef]
- Chetty, R.; Friedman, J.N.; Hilger, N.; Saez, E.; Schanzenbach, D.W.; Yagan, D. How does your kindergarten classroom affect your earnings? Evidence from Project Star. Quart. J. Econ. 2011, 126, 1593–1660. [Google Scholar] [CrossRef]
- Rivkin, S.G.; Hanushek, E.A.; Kain, J.F. Teachers, schools, and academic achievement. Econometrica 2005, 73, 417–458. [Google Scholar] [CrossRef]
- The 74 Million Staff. Flashcards: Test scores and Teacher Evals: A Complex Controversy Explained. The 74 Million. Available online: https://www.the74million.org/article/test-scores-and-teacher-evals-a-complex-controversy-explained/ (accessed on 27 July 2018).
- Ioannidis, J.P.A. Why most published research findings are false. Chance 2005, 18, 40–47. [Google Scholar] [CrossRef]
- Open Science Collaboration. Estimating the reproducibility of psychological science. Science 2015, 349, aac4716. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Simmons, J.P.; Nelson, L.D.; Simonsohn, U. False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychol. Sci. 2011, 22, 1359–1366. [Google Scholar] [CrossRef] [PubMed]
- Makel, M.C.; Plucker, J.A. Facts are more important than novelty: Replication in the education sciences. Educ. Res. 2014, 43, 304–316. [Google Scholar] [CrossRef]
- Schmidt, F.L. Beyond questionable research methods: The role of omitted relevant research in the credibility of research. Arch. Sci. Psychol. 2017, 5, 32–41. [Google Scholar] [CrossRef]
- Ellis, R.S. The Psychology of Individual Differences; D. Appleton and Co.: New York, NY, USA, 1928. [Google Scholar]
- Carnap, R. Logical Foundations of Probability; University of Chicago Press: Chicago, IL, USA, 1950. [Google Scholar]
- Lubinski, D. Scientific and social significance of assessing individual differences: “Sinking shafts at a few critical points”. Annu. Rev. Psychol. 2000, 51, 405–444. [Google Scholar] [CrossRef] [PubMed]
- America’s Best Colleges. 2015. Available online: http://colleges.usnews.rankingsandreviews.com/best-colleges (accessed on 27 July 2018).
- American College Test. ACT-SAT Concordance. 2011. Available online: http://www.act.org/aap/concordance/pdf/reference.pdf (accessed on 27 July 2018).
- Avery, C.N.; Glickman, M.E.; Hoxby, C.M.; Metrick, A. A revealed preference ranking of U.S. colleges and universities. Quart. J. Econ. 2013, 128, 425–467. [Google Scholar] [CrossRef]
- Times Higher Education. World University Rankings. Available online: https://www.timeshighereducation.com/world-university-rankings (accessed on 27 July 2018).
- Sternberg, D.A. Lumosity’s Smartest Colleges. 2013. Available online: https://www.scribd.com/document/184980304/America-s-Smartest-Colleges-2013 (accessed on 27 July 2018).
- Belkin, D. Exclusive test data: Many colleges fail to improve critical-thinking skills. Wall Street J. 2017. Available online: https://www.wsj.com/articles/exclusive-test-data-many-colleges-fail-to-improve-critical-thinking-skills-1496686662 (accessed on 27 July 2018).
- Shaw, E.J.; Marini, J.P.; Beard, J.; Shmueli, D.; Young, L.; Ng, H. The Redesigned SAT Pilot Predictive Validity Study: A First Look; College Board Research Report; College Board: New York, NY, USA, 2016. [Google Scholar]
- College Board. SAT: Understanding Scores. 2017. Available online: https://collegereadiness.collegeboard.org/pdf/understanding-sat-scores.pdf (accessed on 27 July 2018).
- Simons, D.J.; Boot, W.R.; Charness, N.; Gathercole, S.E.; Chabris, C.F.; Hambrick, D.Z.; Stine-Morrow, E.A.L. Do “brain-training” programs work? Psychol. Sci. Public Int. 2016, 17, 103–186. [Google Scholar] [CrossRef] [PubMed]
- Wai, J. Investigating the world’s rich and powerful: Education, cognitive ability, and sex differences. Intelligence 2014, 46, 54–72. [Google Scholar] [CrossRef]
- Wai, J. Investigating America’s elite: Cognitive ability, education, and sex differences. Intelligence 2013, 41, 203–211. [Google Scholar] [CrossRef]
- Wai, J.; Kell, H.J. How Important is Intelligence in the Development of Professional Expertise? Combining Prospective and Retrospective Longitudinal Data Provides an Answer. In The Science of Expertise: Behavioral, Neural, and Genetics Approaches to Complex Skill; Hambrick, D.Z., Campitelli, G., Macnamara, B., Eds.; Routledge: New York, NY, USA, 2017. [Google Scholar]
- Wai, J.; Lincoln, D. Investigating the right tail of wealth: Education, cognitive ability, giving, network power, gender, ethnicity, leadership, and other characteristics. Intelligence 2016, 54, 1–32. [Google Scholar] [CrossRef]
- Wai, J.; Rindermann, H.R. The path and performance of a company leader: An historical examination of the education and cognitive ability of Fortune 500 CEOs. Intelligence 2015, 53, 102–107. [Google Scholar] [CrossRef]
- Murray, C. Coming Apart: The State of White America, 1960–2010; Crown Forum: New York, NY, USA, 2012. [Google Scholar]
- Pinker, S. The trouble with Harvard: The Ivy League is broken and only standardized tests can fix it. The New Republic. 2014. Available online: http://www.newrepublic.com/article/119321/harvard-ivy-league-should-judge-students-standardized-tests (accessed on 27 July 2018).
- Espenshade, T.J.; Radford, A.W. No Longer Separate, Not Yet Equal: Race and Class in Elite College Admission and Campus Life; Princeton University Press: Princeton, NJ. USA, 2009. [Google Scholar]
- Golden, D. The Price of Admission; Three Rivers Press: New York, NY, USA, 2006. [Google Scholar]
- Sander, R.H. A systemic analysis of affirmative action in American law schools. Stanf. Law Rev. 2004, 57, 367–483. [Google Scholar]
- Schmidt, F.L.; Hunter, J.E. General mental ability in the world of work: Occupational attainment and job performance. J. Pers. Soc. Psychol. 2004, 86, 162–173. [Google Scholar] [CrossRef] [PubMed]
- Gottfredson, L.S. G, Jobs, and Life. In The Scientific Study of General Intelligence: Tribute to Arthur R. Jensen; Nyborg, H., Ed.; Pergamon: New York, NY, USA, 2003; pp. 293–342. [Google Scholar]
- Pascarella, E.T.; Cruce, T.; Umbach, P.D.; Wolniak, G.C.; Kuh, G.D.; Carini, R.M.; Hayek, J.C.; Gonyea, R.M.; Zhao, C.-M. Institutional Selectivity and Good Practices in Undergraduate Education: How Strong is the Link? J. High. Educ. 2006, 77, 251–285. [Google Scholar] [CrossRef]
- Lubinski, D.; Benbow, C.P. Study of mathematically precocious youth after 35 years: Uncovering antecedents for the development of math-science expertise. Perspect. Psychol. Sci. 2006, 1, 316–345. [Google Scholar] [CrossRef] [PubMed]
- Wai, J.; Putallaz, M.; Makel, M.C. Studying intellectual outliers: Are there sex differences, and are the smart getting smarter? Curr. Dir. Psychol. Sci. 2012, 21, 382–390. [Google Scholar] [CrossRef]
- Rindermann, H.R.; Thompson, J. The effect of cognitive ability on wealth, as mediated through scientific achievement and economic freedom. Psychol. Sci. 2011, 22, 754–763. [Google Scholar] [CrossRef] [PubMed]
- Hyman, J. ACT for all: The effect of mandatory college entrance exams on postsecondary attainment and choice. Educ. Financ. Policy 2017, 12, 281–311. [Google Scholar] [CrossRef]
- Hambrick, D.Z.; Campitelli, G.; Macnamara, B. (Eds.) The Science of Expertise: Behavioral, Neural, and Genetics Approaches to Complex Skill; Routledge: New York, NY, USA, 2017. [Google Scholar]
- Vansteenkiste, M.; Sierens, E.; Soenens, B.; Luyckx, K.; Lens, W. Motivational profiles from a self-determination perspective: The quality of motivation matters. J. Educ. Psychol. 2009, 101, 671–688. [Google Scholar] [CrossRef]
- Kovas, Y.; Garon-Carrier, G.; Boivin, M.; Petrill, S.A.; Plomin, R.; Malykh, S.B.; Spinath, F.; Murayama, K.; Ando, K.; Bogdanova, O.Y.; et al. Why children differ in motivation to learn: Insights from over 13,000 twins from 6 countries. Person. Individ. Differ. 2015, 80, 51–63. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Revelle, W.; Wilt, J.; Condon, D.M. Individual differences and differential psychology. In The Wiley-Blackwell Handbook of Individual Differences; Chamorro-Premuzic, T., von Stumm, S., Furnham, A., Eds.; Wiley-Blackwell: Hoboken, NJ, USA, 2013. [Google Scholar]
- Wai, J.; Worrell, F.C.; Chabris, C.F. The Consistent Influence of General Cognitive Ability in College, Career, and Lifetime Achievement. In Preparing Students for College and Careers: Theory, Measurement, and Educational Practice; McClarty, K., Mattern, K., Gaertner, M., Eds.; Routledge: New York, NY, USA, 2018. [Google Scholar]
- Rogers, W.T.; Hopkins, K.D. Power estimates in the presence of a covariate and measurement error. Educ. Psychol. Meas. 1988, 48, 647–656. [Google Scholar] [CrossRef]
- Van Breukelen, G.J.P. ANCOVA versus change from baseline had more power in randomized studies and more bias in nonrandomized studies. J. Clin. Epidemiol. 2006, 59, 920–925. [Google Scholar] [CrossRef] [PubMed]
- Borm, G.F.; Fransen, J.; Lemmens, W.A.J.G. A simple sample size formula for analysis of covariance in randomized clinical trials. J. Clin. Epidemiol. 2007, 60, 1234–1238. [Google Scholar] [CrossRef] [PubMed]
- Gottfredson, L.S. Intelligence: Is it the epidemiologists’ elusive “fundamental cause” of social class inequalities in health? J. Personal. Soc. Psychol. 2004, 86, 174–199. [Google Scholar] [CrossRef] [PubMed]
- Wainer, H. Uneducated Guesses: Using Evidence to Uncover Misguided Education Policies; Princeton University Press: Princeton, NJ, USA, 2011. [Google Scholar]
|Times Higher Education World Rank||Average SAT (Math + Verbal)||Number of Institutions|
|1 to 10||1499||7|
|11 to 25||1406||11|
|26 to 50||1343||8|
|51 to 100||1281||17|
|101 to 150||1326||7|
|151 to 200||1249||12|
|201 to 300||1205||21|
|301 to 400||1182||26|
|401 to 500||1146||15|
|501 to 600||1151||14|
|601 to 1000||1104||20|
|ρ||d = 0.1||d = 0.2||d = 0.3||d = 0.4||d = 0.5|
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