Acceleration in elementary school: Using propensity score matching to estimate the effects on academic achievement

Journal of Educational Psychology

Volumn 106, Issue 4, 2014, Pages 1080-1095

  Kretschmann, Julia ^a   Vock, Miriam ^a   Lüdtke, Oliver ^b  

^a UNIVERSITY OF POTSDAM   (Germany)

^b HUMBOLDT UNIVERSITY   (Germany)

Author keywords

Academic performance; Acceleration; Elementary school; Grade skipping; Propensity score matching

Indexed keywords

EID: 84925437367     PISSN: 00220663     EISSN: 19392176     Source Type: Journal    
DOI: 10.1037/a0036631     Document Type: Article

References (77)

1. Allison, P. D. (2001). Missing data. Thousand Oaks, CA: Sage.
2. Austin, P. C. (2009). Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Statistics in Medicine, 28, 3083-3107. doi:10.1002/ sim.3697
3. Austin, P. C. (2011). An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behavioral Research, 46, 399-424. doi:10.1080/00273171.2011 .568786
4. Bang, H., & Robins, J. M. (2005). Doubly robust estimation in missing data and causal inference models. Biometrics, 61, 962-973. doi:10.1111/j .1541-0420.2005.00377.x
5. Baumert, J., Becker, M., Neumann, M., & Nikolova, R. (2009). Frühübergang in ein grundständiges Gymnasium-Übergang in ein privilegiertes Entwicklungsmilieu? Ein Vergleich von Regressionsanalyse und Propensity Score Matching [Early transition into the academic track of secondary schooling-Transfer to a privileged learning environment? A comparison of regression analysis and propensity score matching]. Zeitschrift für Erziehungswissenschaft, 12, 189 -215. doi:10.1007/ s11618-009-0072-4
6. Becker, M., Lüdtke, O., Trautwein, U., Köller, O., & Baumert, J. (2012). The differential effects of school tracking on psychometric intelligence: Do academic-track schools make students smarter? Journal of Educational Psychology, 104, 682-699. doi:10.1037/a0027608
7. Bisanz, J., Morrison, F. J., & Dunn, M. (1995). Effects of age and schooling on the acquisition of elementary quantitative skills. Developmental Psychology, 31, 221-236. doi:10.1037/0012-1649.31.2.221
8. Bos, W., Lankes, E.-M., Prenzel, M., Schwippert, K., Walther, G., & Valtin, R. (Eds.). (2003). Erste Ergebnisse aus IGLU. Schülerleistungen am Ende der vierten Jahrgangsstufe im internationalen Vergleich [First results from IGLU: Students' performance at the end of the fourth grade in comparison with other countries]. Münster, Germany: Waxmann.
9. Brody, L. E., & Benbow, C. (2004). Accelerative strategies: How effective are they for the gifted? In L. E. Brody (Ed.), Grouping and acceleration practices in gifted education (pp. 57-67). Thousand Oaks, CA: Corwin Press.
10. Cahan, S., & Cohen, N. (1989). Age versus schooling effects on intelligence development. Child Development, 60, 1239-1249. doi:10.2307/ 1130797
11. Caliendo, M., & Kopeinig, S. (2008). Some practical guidance for the implementation of propensity score matching. Journal of Economic Surveys, 22, 31-72. doi:10.1111/j.1467-6419.2007.00527.x
12. Christopherson, S. L. (1981). Developmental placement in the regular school program. Gifted Child Today, 4(4), 40 - 41. doi:10.1177/ 107621758100400418
13. Cochran, W. G., & Rubin, D. B. (1973). Controlling bias in observational studies: A review. Sankhya: Series A, 35, 417-446.
14. Colangelo, N., Assouline, S. G., & Gross, M. U. M. (Eds.). (2004). A nation deceived: How schools hold back America's brightest students. Retrieved from http://www.accelerationinstitute.org/Nation_Deceived/ Get_Report.aspx
15. Eccles, J. S., Midgley, C., Wigfield, A., Buchanan, C. M., Reuman, D., Flanagan, C., & Mac Iver, D. (1993). Development during adolescence. The impact of stage- environment fit on young adolescents' experiences in schools and in families. American Psychologist, 48, 90-101. doi: 10.1037/0003-066X.48.2.90
16. Feldhusen, J. F. (1989). Synthesis of research on gifted youth. Educational Leadership, 46, 6-11. Retrieved from http://www.ascd.org/ASCD/pdf/ journals/ed_lead/el_198903_feldhusen.pdf
17. Gallagher, J. J. (2004). Public policy and acceleration of gifted students. In N. Colangelo, S. G. Assouline, & M. U. M. Gross (Eds.), A nation deceived: How schools hold back America's brightest students (Vol. 2, pp. 39 - 45). Retrieved from http://www.accelerationinstitute.org/ Nation_Deceived/Get_Report.aspx
18. Ganzeboom, H. B. G., De Graaf, P. M., & Treiman, D. J. (1992). A standard international socio-economic index of occupational status. Social Science Research, 21, 1-56. doi:10.1016/0049-089X(92)90017-B
19. Gu, X. S., & Rosenbaum, P. R. (1993). Comparison of multivariate matching methods: Structures, distances, and algorithms. Journal ofComputational and Graphical Statistics, 2, 405-420. doi:10.1080/ 10618600.1993.10474623
20. Hansen, B. B. (2004). Full matching in an observational study of coaching for the SAT. Journal of the American Statistical Association, 99, 609-618. doi:10.1198/016214504000000647
21. Harder, V. S., Stuart, E. A., & Anthony, J. C. (2010). Propensity score techniques and the assessment of measured covariate balance to test causal associations in psychological research. Psychological Methods, 15, 234-249. doi:10.1037/a0019623
22. Hattie, J. (2009). Visible learning: A synthesis of over 800 meta-analyses relating to achievement. New York, NY: Routledge.
23. Heckman, J. J. (1979). Sample selection bias as a specification error. Econometrica, 47, 153-161. doi:10.2307/1912352
24. Heinbokel, A. (2001a). Hochbegabung im Spiegel der Printmedien seit 1950-Vom Werdegang eines Bewusstseinswandels [Giftedness in the print media since 1950-About the history of a change in awareness]. Bonn, Germany: Bundesministerium für Bildung und Forschung.
25. Heinbokel, A. (2001b).Überspringen von Klassen [Grade skipping]. Münster, Germany: LIT Verlag.
26. Heinbokel, A. (2009). Handbuch Akzeleration [Manual of acceleration]. Münster, Germany: LIT Verlag.
27. Heinbokel, A. (n.d.). Zahlen zumÜberspringen 2011/12 [Data on skipping 2011/12]. Retrieved from http://www.netzwerk-akzeleration.de/uploads/ 2011-12.pdf
28. Heller, K. A., & Perleth, C. (2000). Kognitiver Fähigkeitstest für 4.-12. Klassen, Revision (KFT 4 12_ R) [Revision of the cognitive ability test for 4th till 12th graders (KFT 4 12_ R)]. Göttingen, Germany: Hogrefe.
29. Ho, D. E., Imai, K., King, G., & Stuart, E. A. (2007). Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Political Analysis, 15, 199-236. doi:10.1093/ pan/mpl013
30. Ho, D., Imai, K., King, G., & Stuart, E. (2011). The MatchIt package (Version 2.4 -20) [Computer program]. Retrieved from http://gking .harvard.edu/matchit/
31. Holling, H., Preckel, F., Vock, M., & Schulze Willbrenning, B. (2004). Schulische Begabtenförderung in den Ländern. Maßnahmen und Tendenzen [Academic education for gifted students in the federal states: Measures and tendencies]. Retrieved from http://www.blk-bonn.de/ papers/heft121.pdf
32. Holling, H., Vock, M., & Preckel, F. (2001). Fostering giftedness at school: A stocktaking in the states of the Federal Republic of Germany. Australasian Journal of Gifted Education, 10, 48-63.
33. Hong, G., & Raudenbush, S. W. (2006). Evaluating kindergarten retention policy: A case study of causal inference for multilevel observational data. Journal of the American Statistical Association, 101, 901-910. doi:10.1198/016214506000000447
34. Hoogeveen, L., van Hell, J. G., & Verhoeven, L. (2005). Teacher attitudes toward academic acceleration and accelerated students in the Netherlands. Journal for the Education of the Gifted, 29, 30-59.
35. Hoogeveen, L., van Hell, J. G., & Verhoeven, L. (2009). Self-concept and social status of accelerated and nonaccelerated students in the first 2 years of secondary school in the Netherlands. Gifted Child Quarterly, 53, 50-67. doi:10.1177/0016986208326556
36. Hoogeveen, L., van Hell, J. G., & Verhoeven, L. (2012). Social-emotional characteristics of gifted accelerated and non-accelerated students in the Netherlands. British Journal of Educational Psychology, 82, 585-605. doi:10.1111/j.2044-8279.2011.02047.x
37. IBM Corporation. (2013). IBM SPSS statistics for Windows, version 22.0. Armonk, NY: Author.
38. Imai, K., King, G., & Stuart, E. A. (2008). Misunderstandings between experimentalists and observationalists about causal inference. Journal of the Royal Statistical Society: Series A, 171, 481-502. doi:10.1111/j .1467-985X.2007.00527.x
39. Kent, S. D. (1992). The effects of acceleration on the social and emotional development of gifted elementary students: A meta-analysis. Dissertation Abstracts International: Section A. Humanities and Social Sciences, 54, 2.
40. Kulik, J. A. (2004). Meta-analytic studies of acceleration. In N. Colangelo, S. G. Assouline, & M. U. M. Gross (Eds.), A nation deceived: How schools hold back America's brightest students (Vol. 2, pp. 13-22). Retrieved from http://www.accelerationinstitute.org/Nation_Deceived/ Get_Report.aspx
41. Kulik, J. A., & Kulik, C. C. (1984). Effects of accelerated instruction on students. Review of Educational Research, 54, 409-425. doi:10.3102/ 00346543054003409
42. Kuo, Y., & Lohmann, D. F. (2011). The timing of grade skipping. Journal for the Education of the Gifted, 34, 731-741. doi:10.1177/ 0162353211417219
43. Lehmann, R., Gänsfuß, R., & Peek, R. (1999). Aspekte der Lernausgangslage und der Lernentwicklung von Schülerinnen und Schülern an Hamburger Schulen-Klassenstufe 7 [Aspects of the initial situation and the development of students' learning at schools in Hamburg-Seventh grade]. Retrieved from http://bildungsserver.hamburg.de/contentblob/ 2815698/data/pdf-schulleistungstest-lau-7.pdf
44. Lehmann, R. H., & Lenkeit, J. (2008). Element. Erhebung zum Lese- und Mathematikverständnis. Entwicklung in den Jahrgangsstufen 4 bis 6 in Berlin, Germany: Abschlussbericht über die Untersuchungen 2003, 2004 und 2005 an Berliner Grundschulen und grundständigen Gymnasien [Element: A survey of reading and mathematics performance. Development from fourth till sixth grade in Berlin, Germany: Final report]. Retrieved from http://www.berlin.de/imperia/md/content/ sen-bildung/schulqualitaet/element6_bericht_komplett.pdf
45. Lehmann, R. H., & Nikolova, R. (2003). Element. Erhebung zum Leseund Mathematikverständnis. Entwicklung in den Jahrgangsstufen 4 bis 6 in Berlin, Germany: Projektbeschreibung [Element: A survey of reading and mathematics performance. Development from fourth till sixth grade in Berlin, Germany: Project description]. Retrieved from http://www.berlin.de/imperia/md/content/sen-bildung/schulqualitaet/ schulleistungsuntersuchungen/element_projektbeschreibung.pdf
46. Lehmann, R. H., Peek, R., Gänsfuß, R., Lutkat, S., Mücke, S., & Barth, I. (2001). QuaSUM-Qualitätsuntersuchung an Schulen zum Unterricht in Mathematik. Ergebnisse einer repräsentativen Untersuchung im Land Brandenburg [QuaSUM-Quality control in schools regarding mathematics instruction. Results of a representative study in the federal state of Brandenburg]. Retrieved from http://www.grundschulpaedagogik .uni-bremen.de/lehre/2001ws/gspaed/pisa/quasum-end.pdf
47. Löffler, I., & Meyer-Schepers, U. (2001). Dortmunder Schriftkompetenz-Ermittlung-DoSE [DoSE-Examination of writing expertise]. Unpublished manuscript, Dortmund, Germany.
48. Lubinski, D., & Benbow, C. P. (2000). States of excellence. American Psychologist, 55, 137-150. doi:10.1037/0003-066X.55.1.137
49. Marsh, H. W. (2005). Big-fish-little-pond effect on academic self-concept. Zeitschrift für Pädagogische Psychologie, 19, 119-129. doi:10.1024/ 1010-0652.19.3.119
50. Marsh, H. W., Chessor, D., Craven, R., & Roche, L. (1995). The effect of gifted and talented programs on academic self-concept: The big fish strikes again. American Educational Research Journal, 32, 285-319. doi:10.3102/00028312032002285
51. Marsh, H. W., & O'Mara, A. J. (2010). Long-term total negative effects of school-average ability on diverse educational outcomes: Direct and indirect effects of the big-fish-little-pond effect. Zeitschrift für Pädagogische Psychologie, 24, 51-72. doi:10.1024/1010-0652/a000004
52. Marsh, H. W., Trautwein, U., Lüdtke, O., Köller, O., & Baumert, J. (2005). Academic self-concept, interest, grades and standardized test scores: Reciprocal effects models of causal ordering. Child Development, 76, 397-416. doi:10.1111/j.1467-8624.2005.00853.x
53. Morgan, S. L., & Winship, C. (2007). Counterfactuals and causal inference: Methods and principles for social research. New York, NY: Cambridge University Press.
54. Park, G., Lubinski, D., & Benbow, C. P. (2013). When less is more: Effects of grade skipping on adult STEM productivity among mathematically precocious adolescents. Journal of Educational Psychology, 105, 176-198. doi:10.1037/a0029481
55. Preckel, F., & Vock, M. (2013). Hochbegabung: Ein Lehrbuch zu Grundlagen, Diagnostik und Fördermöglichkeiten [Giftedness: A textbook about basics, diagnostics and interventions for fostering]. Göttingen, Germany: Hogrefe.
56. Pressey, S. L. (1949). Educational acceleration: Appraisals and basic problems. Columbus: Ohio State University Press.
57. Rogers, K. B. (1991). A best-evidence synthesis of research on types of accelerative programs for gifted students. Dissertation Abstracts International: Section A. Humanities and Social Sciences, 52, 796.
58. Rogers, K. B. (2004). The academic effects of acceleration. In N. Colangelo, S. G. Assouline, & M. U. M. Gross (Eds.), A nation deceived: How schools hold back America's brightest students (Vol. 2, pp. 47-57). Retrieved from http://www.accelerationinstitute.org/Nation_Deceived/ Get_Report.aspx
59. Rosenbaum, P. R. (1984). The consequences of adjustment for a concomitant variable that has been affected by the treatment. Journal of the Royal Statistical Society, Series A, 147, 656-666. doi:10.2307/2981697
60. Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70, 41-55. doi:10.1093/biomet/70.1.41
61. Rubin, D. B. (1974). Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology, 66, 688-701. doi:10.1037/h0037350
62. Rubin, D. B. (1986). Statistics and causal inference: Comment: Which ifs have causal answers? Journal of the American Statistical Association, 81, 961-962. doi:10.1080/01621459.1986.10478355
63. Rubin, D. B. (1987). Multiple imputation for nonresponse in surveys. doi:10.1002/9780470316696
64. Rubin, D. B., & Thomas, N. (2000). Combining propensity score matching with additional adjustments for prognostic covariates. Journal of the American Statistical Association, 95, 573-585. doi:10.1080/01621459 .2000.10474233
65. Schafer, J. L., & Kang, J. (2008). Average causal effects from nonrandomized studies: A practical guide and simulated example. Psychological Methods, 13, 279-313. doi:10.1037/a0014268
66. Senate Department for Education, Science and Research Berlin. (Ed.). (2011). Bildung für Berlin. Zahlen, Daten, Fakten. Ausgewählte Eckdaten der allgemein bildende Schulen 2011/2012 [Education for Berlin: Data, facts and figures. Selected key data on schools of general education]. Retrieved from http://www.berlin.de/sen/bildung/bildungsstatistik/
67. Southern, W. T., & Jones, E. D. (2004). Types of acceleration: Dimensions and issues. In N. Colangelo, S. G. Assouline, & M. U. M. Gross (Eds.), A nation deceived: How schools hold back America's brightest students (Vol. 2, pp. 5-12). Retrieved from http://www.accelerationinstitute.org/ Nation_Deceived/Get_Report.aspx
68. Statistical Offices of the Federation and the Länder. (2012). Bildung-Schüler/innen an allgemein bildenden Schulen [Education-Students in general educational schools]. Retrieved from http://www.statistik-portal .de/Statistik-Portal/de_jb04_jahrtab25sch.asp
69. Steenbergen-Hu, S., & Moon, S. M. (2011). The effects of acceleration on high-ability learners: A meta-analysis. Gifted Child Quarterly, 55, 39-53. doi:10.1177/0016986210383155
70. Steiner, P. M., Cook, T. D., Shadish, W. R., & Clark, M. H. (2010). The importance of covariate selection in controlling for selection bias in observational studies. Psychological Methods, 15, 250 -267. doi: 10.1037/a0018719
71. Stuart, E. A. (2010). Matching methods for causal inference: A review and a look forward. Statistical Science, 25, 1-21. doi:10.1214/09-STS313
72. Stuart, E. A., & Green, K. M. (2008). Using full matching to estimate causal effects in nonexperimental studies: Examining the relationship between adolescent marijuana use and adult outcomes. Developmental Psychology, 44, 395-406. doi:10.1037/0012-1649.44.2.395
73. Thoemmes, F. J., & Kim, E. S. (2011). A systematic review of propensity score methods in the social sciences. Multivariate Behavioral Research, 46, 90-118. doi:10.1080/00273171.2011.540475
74. Thorndike, R. L., & Hagen, E. (1971). Cognitive Abilities Test. Boston, MA: Houghton Mifflin.
75. Vock, M., Penk, C., & Köller, O. (2013). Wer überspringt eine Schulklasse? Befunde zum Klassenüberspringen in Deutschland [Who skips a grade? Findings concerning grade acceleration in German schools]. Psychologie in Erziehung und Unterricht. Advance online publication. doi:10.2378/peu2013.art22d
76. Vock, M., Preckel, F., & Holling, H. (2007). Förderung Hochbegabter in der Schule-Evaluationsbefunde und Wirksamkeit von Maßnahmen [Fostering giftedness in school-Evaluation of findings and effectiveness of measures]. Göttingen, Germany: Hogrefe.
77. Wells, R., Lohmann, D., & Marron, M. (2009). What factors are associated with grade acceleration? An analysis and comparison of two U.S. databases. Journal of Advanced Academics, 20, 248-273. doi:10.1177/ 1932202X0902000203