PISA proficiency scores predict educational outcomes

Learning and Individual Differences

Volumn 24, Issue , 2013, Pages 63-72

  Fischbach, Antoine ^a   Keller, Ulrich ^a   Preckel, Franzis ^b   Brunner, Martin ^c  

^a UNIVERSITY OF LUXEMBOURG   (Luxembourg)

^b UNIVERSITY OF TRIER   (Germany)

^c FREIE UNIVERSITÄT BERLIN   (Germany)

Author keywords

Achievement tests; Educational outcomes; Large scale assessment; PISA; Prediction; School grades

Indexed keywords

EID: 84875239889     PISSN: 10416080     EISSN: 18733425     Source Type: Journal    
DOI: 10.1016/j.lindif.2012.10.012     Document Type: Article

References (75)

1. AERA, APA, NCME Standards for educational and psychological testing 2002, AERA, Washington, DC.
2. Andersen D. 4 år efter grundskolen [4years after basic compulsory education] 2005, AKF, Copenhagen.
3. Baumert J., Brunner M., Lüdtke O., Trautwein U. Was messen internationale Schulleistungsstudien? - Resultate kumulativer Wissenserwerbsprozesse. Eine Antwort auf Heiner Rindermann [What do international student assessment studies measure? - Results of processes of cumulative knowledge acquisition. A response to Heiner Rindermann]. Psychologische Rundschau 2007, 58(2):118-145.
4. Baumert J., Lüdtke O., Trautwein U., Brunner M. Large-scale student assessment studies measure the results of processes of knowledge acquisition: Evidence in support of the distinction between intelligence and student achievement. Educational Research Review 2009, 4(3):165-176. 10.1016/j.edurev.2009.04.002.
5. Bautier E., Rayou P. What PISA really evaluates: Literacy or students' universes of reference?. Journal of Educational Change 2007, 8(4):359-364. 10.1007/s10833-007-9043-9.
6. Bonderup Dohn N. Knowledge and skills for PISA? Assessing the assessment. Journal of Philosophy of Education 2007, 41(1):1-16. 10.1111/j.1467-9752.2007.00542.x.
7. Brunner M. No g in education?. Learning and Individual Differences 2008, 18(2):152-165. 10.1016/j.lindif.2007.08.005.
8. Brunner M., Keller U., Hornung C., Reichert M., Martin R. The cross-cultural generalizability of a new structural model of academic self-concepts. Learning and Individual Differences 2009, 19(4):387-403. 10.1016/j.lindif.2008.11.008.
9. Brunner M., Lüdtke O., Trautwein U. The internal/external frame of reference model revisited: Incorporating general cognitive ability and general academic self-concept. Multivariate Behavioral Research 2008, 43(1):137-172. 10.1080/00273170701836737.
10. Burton R., Martin R. L'orientation scolaire au Luxembourg: "Au-delà de l'égalité des chances. le gâchis d'un potentiel humain" [Tracking decisions in Luxembourg: "Beyond equal opportunities. a waste of human capital"]. La place de l'école dans la société luxembourgeoise de demain 2008, 165-186. De Boeck, Bruxelles. R. Martin, C. Dierendonck, C. Meyers, M. Noesen (Eds.).
11. Burton N.W., Ramist L. Predicting success in college: SAT studies of classes graduating since 1980. College Board Research Report No. 2001-2 2001, College Entrance Examination Board, New York.
12. Cohen J. A power primer. Psychological Bulletin 1992, 112(1):155-159. 10.1037/0033-2909.112.1.155.
13. Cognitive epidemiology [Special issue]. Intelligence 2009, 37(6):517-633.
14. Dolin J. PISA - An example of the use and misuse of large-scale comparative tests. PISA zufolge PISA. Hält PISA, was es verspricht? - PISA according to PISA. Does PISA keep what it promises? 2007, 93-125. Lit, Wien. S.T. Hopmann, G. Brinek, M. Retzl (Eds.).
15. Ehmke T., Drechsel B., Carstensen C.H. Klassenwiederholen in PISA-I-Plus: Was lernen Sitzenbleiber in Mathematik dazu? [Grade retention in PISA-I-Plus: What do retained students learn in mathematics?]. Zeitschrift für Erziehungswissenschaft 2008, 11(3):368-387. 10.1007/s11618-008-0033-3.
16. Else-Quest N.M., Hyde J.S., Linn M.C. Cross-national patterns of gender differences in mathematics: A meta-analysis. Psychological Bulletin 2010, 136(1):103-127. 10.1037/a0018053.
17. Gottfredson L.S., Deary I.J. Intelligence predicts health and longevity, but why?. Current Directions in Psychological Science 2004, 13(1):1-4.
18. Grek S. Governing by numbers: The PISA "effect" in Europe. Journal of Education Policy 2009, 24(1):23-37. 10.1080/02680930802412669.
19. Grigorenko E.L., Sternberg R.J. Dynamic testing. Psychological Bulletin 1998, 124(1):75-111. 10.1037/0033-2909.124.1.75.
20. Hillman K., Thomson S. Pathways from PISA: LSAY and the 2003 PISA sample two years on 2006, ACER, Melbourne.
21. Jimerson S.R. A synthesis of grade retention research: Looking backward and moving forward. California School Psychologist 2001, 6:47-59.
22. Knighton T., Bussière P. Educational outcomes at age 19 associated with reading ability at age 15 2006, Statistics Canada, Ottawa.
23. Köller O., Trautwein U. Englischleistungen von Schülerinnen und Schülern an allgemein bildenden und beruflichen Gymnasien [English proficiency of students from the highest academic track]. Wege zur Hochschulreife in Baden-Württemberg. TOSCA - Eine Untersuchung an allgemein bildenden und beruflichen Gymnasien 2004, 285-326. Leske & Budrich, Opladen. O. Köller, R. Watermann, U. Trautwein, O. Lüdtke (Eds.).
24. Kuncel N.R., Hezlett S.A. Standardized tests predict graduate students' success. Science 2007, 315:1080-1081.
25. Kuncel N.R., Hezlett S.A. Fact and fiction in cognitive ability testing for admissions and hiring decisions. Current Directions in Psychological Science 2010, 19(6):339-345. 10.1177/0963721410389459.
26. Kuncel N.R., Hezlett S.A., Ones D.S. Academic performance, career potential, creativity, and job performance: Can one construct predict them all?. Journal of Personality and Social Psychology 2004, 86(1):148-161.
27. Lee J. Universals and specifics of math self-concept, math self-efficacy, and math anxiety across 41 PISA 2003 participating countries. Learning and Individual Differences 2009, 19(3):355-365. 10.1016/j.lindif.2008.10.009.
28. Lumley T. Analysis of complex survey samples. Journal of Statistical Software 2004, 9:1-19.
29. Lumley T. Survey: Analysis of complex survey samples. R package 2011, (Retrieved from http://CRAN.R-project.org/package=survey).
30. Lumley T. Mitools: Tools for multiple imputation of missing data. R package 2012, (Retrieved from http://CRAN.R-project.org/package=mitools).
31. Lykken D.T. Statistical significance in psychological research. Psychological Bulletin 1968, 70(3):151-159.
32. Lynn R., Mikk J. National IQs predict educational attainment in math, reading and science across 56 nations. Intelligence 2009, 37(3):305-310. 10.1016/j.intell.2009.01.002.
33. Marsh H.W., Hau K.-T. Big-fish-little-pond effect on academic self-concept. A cross-cultural (26-country) test of the negative effects of academically selective schools. American Psychologist 2003, 58(5):364-376. 10.1037/0003-066X.58.5.364.
34. Marsh H.W., Hau K.-T. Explaining paradoxical relations between academic self-concepts and achievements: Cross-cultural generalizability of the internal/external frame of reference predictions across 26 countries. Journal of Educational Psychology 2004, 96(1):56-67. 10.1037/0022-0663.96.1.56.
35. Mattern K.D., Patterson B.F. Is performance on the SAT related to college retention?. College Board Research Report No. 2009-7 2009, College Board, New York.
36. Mattern K.D., Patterson B.F., Shaw E.J., Kobrin J.L., Barbutti S.M. Differential validity and prediction of the SAT. College Board Research Report No. 2008-4 2008, College Board, New York.
37. Northern lights on PISA 2003. A reflection from the nordic countries 2006, Nordic Council of Ministers, Copenhagen. J. Mejding, R. Astrid (Eds.).
38. Muthén L.K., Muthén B.O. Mplus. Statistical analysis with latent variables. User's guide 2010, Muthén & Muthén, Los Angeles. Sixth edition.
39. Nagy G., Neumann M., Becker M., Watermann R., Köller O., Lüdtke O., et al. Mathematikleistungen am Ende der Sekundarstufe II [Mathematical proficiency at the end of secondary education]. Schulleistungen von Abiturienten. Regionale, schulformbezogene und soziale Disparitäten 2007, 71-112. Waxmann, Münster. U. Trautwein, O. Köller, R. Lehmann, O. Lüdtke (Eds.).
40. OECD PISA 2003. Technical report 2005, OECD Publishing, Paris.
41. OECD Assessing scientific, reading and mathematical literacy: A framework for PISA 2006 2006, OECD Publishing, Paris.
42. OECD PISA 2006. Analysis 2007, Vol.1. OECD Publishing, Paris.
43. OECD PISA data analysis manual. SPSS 2009, OECD Publishing, Paris. 2nd edition.
44. OECD Education at a glance 2010 2010, OECD Publishing, Paris.
45. OECD Pathways to success. How knowledge and skills at age 15 shape future lives in Canada 2010, OECD Publishing, Paris.
46. OECD National accounts at a glance 2010 2011, OECD Publishing, Paris.
47. Patterson B.F., Mattern K.D. Validity of the SAT for predicting first-year grades: 2008 SAT validity sample (College Board Statistical Report No. 2011-5). Research and development 2011, College Board, New York.
48. Penman R. An easy reference guide to longitudinal surveys of Australian youth research reports, 1996-2003. LSAY research reports 2004, ACER, Camberwell, Victoria.
49. Pongratz L.A. Voluntary self-control: Education reform as a governmental strategy. Educational Philosophy and Theory 2006, 38(4):471-482. 10.1111/j.1469-5812.2006.00205.x.
50. Prais S.J. Cautions on OECD's recent educational survey (PISA). Oxford Review of Education 2003, 29(2):139-163. 10.1080/0305498032000080657.
51. Prenzel M., Walter O., Frey A. PISA misst Kompetenzen [PISA measures competencies]. Psychologische Rundschau 2007, 58(2):128-136. 10.1026/0033-3042.58.2.128.
52. R Development Core Team R: A language and environment for statistical computing 2011, R Foundation for Statistical Computing, Vienna, (Retrieved from http://www.R-project.org/).
53. Raudenbush S.W., Bryk A.S. Hierarchical linear models. Applications and data analysis methods 2002, Sage, Thousand Oaks. 2nd ed.
54. Rautalin M., Alasuutari P. The uses of the national PISA results by Finnish officials in central government. Journal of Education Policy 2009, 24(5):539-556. 10.1080/02680930903131267.
55. Ree M.J., Earles J.A., Teachout M.S. Predicting job performance: Not much more than g. Journal of Applied Psychology 1994, 79(4):518-524.
56. Rindermann H. Was messen internationale Schulleistungsstudien? [What do international student assessment studies measure?]. Psychologische Rundschau 2006, 57(2):69-86. 10.1026/0033-3042.57.2.69.
57. Robbins S.B., Lauver K., Le H., Davis D., Langley R., Carlstrom A. Do psychosocial and study skill factors predict college outcomes? A meta-analysis. Psychological Bulletin 2004, 130(2):261-288. 10.1037/0033-2909.130.2.261.
58. Roth P.L., BeVier C.A., Switzer F.S., Schippmann J.S. Meta-analyzing the relationship between grades and job performance. Journal of Applied Psychology 1996, 81(5):548-556.
59. Roth P.L., Clarke R.L. Meta-analyzing the relation between grades and salary. Journal of Vocational Behavior 1998, 53:386-400.
60. Rumberger R.W. High school dropouts: A review of issues and evidence. Review of Educational Research 1987, 57(2):101-121.
61. Rumberger R.W. Dropping out of middle school: A multilevel analysis of students and schools. American Educational Research Journal 1995, 32:583-625.
62. Sackett P.R., Borneman M.J., Connelly B.S. High stakes testing in higher education and employment: Appraising the evidence for validity and fairness. American Psychologist 2008, 63(4):215-227. 10.1037/0003-066X.63.4.215.
63. Sackett P.R., Kuncel N.R., Arneson J.J., Cooper S.R., Waters S.D. Does socioeconomic status explain the relationship between admissions tests and post-secondary academic performance?. Psychological Bulletin 2009, 135(1):1-22. 10.1037/a0013978.
64. Schafer J.L., Graham J.W. Missing data: Our view of the state of the art. Psychological Methods 2002, 7(2):147-177. 10.1037//1082-989X.7.2.147.
65. Schleicher A. Can competencies assessed by PISA be considered the fundamental school knowledge 15-year-olds should possess?. Journal of Educational Change 2007, 8(4):349-357. 10.1007/s10833-007-9042-x.
66. Schleicher A. Assessing literacy across a changing world. Science 2010, 328(5977):433-434. 10.1126/science.1183092.
67. Schmidt F.L., Hunter J.E. The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 85years of research findings. Psychological Bulletin 1998, 124(2):262-274.
68. Schuler H., Funke U., Baron-Boldt J. Predictive validity of school grades. A meta-analysis. Applied Psychology: An International Review 1990, 39(1):89-103.
69. PISA 2006. Nationaler Bericht Luxemburg [PISA 2006. National report Luxembourg] 2007, MENFP, Luxembourg. SCRIPT, EMACS (Eds.).
70. Segall M.H., Lonner W., Berry J.W. Cross-cultural psychology as a scholarly discipline: On the flowering of culture in behavioral research. American Psychologist 1998, 53(10):1101-1110.
71. Sjøberg S. PISA and "real life challenges": Mission impossible?. PISA zufolge PISA. Hält PISA, was es verspricht? - PISA according to PISA. Does PISA keep what it promises? 2007, 203-224. Lit, Wien. S.T. Hopmann, G. Brinek, M. Retzl (Eds.).
72. Strenze T. Intelligence and socioeconomic success: A meta-analytic review of longitudinal research. Intelligence 2007, 35(5):401-426. 10.1016/j.intell.2006.09.004.
73. Takayama K. Politics of externalization in reflexive times: Reinventing Japanese education reform discourses through "Finnish PISA success". Comparative Education Review 2009, 54(1):51-75.
74. Tomarken A.J., Waller N.G. Potential problems with "well fitting" models. Journal of Abnormal Psychology 2003, 112(4):578-598. 10.1037/0021-843X.112.4.578.
75. Wilkinson L., Task Force on Statistical Inference Statistical methods in psychology journals. Guidelines and explanations. American Psychologist 1999, 54(8):594-604.