High-achieving and average students reading growth: Contrasting school and summer trajectories

Journal of Educational Research

Volumn 108, Issue 2, 2015, Pages 112-129

  Rambo Hernandez, Karen E ^a   Mccoach, D Betsy ^b  

^a Veterinary Dentistry and Oral Surgery   (United States)

^b UNIVERSITY OF CONNECTICUT   (United States)

Author keywords

academic achievement; hierarchical linear modeling; high achieving students; longitudinal studies; summer effect

Indexed keywords

EID: 84923567323     PISSN: 00220671     EISSN: 19400675     Source Type: Journal    
DOI: 10.1080/00220671.2013.850398     Document Type: Article

References (48)

1. Alexander, K. L., Entwisle, D. R., & Olson, L. S. (2001). Schools, achievement, and inequality: A seasonal perspective. Educational Evaluation and Policy Analysis, 23, 171-191. doi:10.3102/01623737023002171
2. Alexander, K. L., Entwisle, D. R., & Olson, L. S. (2007). Lasting consequences of the summer learning gap. American Sociological Review, 72, 167-180. doi:10.1177/000312240707200202
3. American Recovery and Reinvestment Act of 2009, Pub. L. No. 111-5 & 111-8, Stat. 115 & 524 (2009
4. Bryk, A. S., & Raudenbush, S. W. (1988). Toward a more appropriate conceptualization of research on school effects: A three-level hierarchical linear model. American Journal of Education, 97, 65-108
5. Campbell, D. T. (1999). A primer on regression artifacts. New York, NY: Guilford Press
6. Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Erlbaum
7. Cooper, H., Nye, B., Charlton, K., Lindsay, J., & Greathouse, S. (1996). The effects of summer vacation on achievement test scores: A narrative and meta-Analytic review. Review of Educational Research, 66, 227-268. doi:10.2307/1170523
8. Downey, D. B., von Hippel, P. T., & Broh, B. A. (2004). Are schools the great equalizer?. Cognitive inequality during the summer months and the school year. American Sociological Review, 69, 613-635. doi:10.1177/.000312240406900501
9. Downey, D. B., von Hippel, P. T., & Hughes, M. (2008). Are 'failing' schools really failing?. Removing the influence of non-school factors from measures of school quality. Sociology of Education, 81, 242-270. doi:10.1177/003804070808100302
10. Entwisle, D. R., & Alexander, K. L. (1992). Summer setback: Race, poverty, school composition, and mathematics achievement in the first two years of school. American Sociological Review, 57, 72-84. doi:10.2307/.2096145
11. Gallagher, J. J. (2004). No child left behind and gifted education. Roeper Review, 26, 121-123. doi:10.1080/02783190409554255
12. Hambleton, R. K., Swaminathan, H., & Rogers, H. J. (1991). Fundamentals of item response theory. Thousand Oaks, CA: Sage
13. Huang, M. (2009). Classroom homogeneity and the distribution of student math performance: A country-level fixed-effects analysis. Social Science Research, 38, 781-791. doi:10.1016/j.ssresearch.2009.05.001
14. Kaplan, S. N. (2004). Where we stand determines the answers to the question: Can the No Child Left Behind legislation be beneficial to gifted students?. Roeper Review, 26, 124-125. doi:10.1080/.02783190409554256
15. Kingsbury, G. G., & Wise, S. L. (2011). Creating a K-12 adaptive test: Examining the stability of item parameter estimates and measurement scales. Journal of Applied Testing Technology, 12, 3-15
16. Kulik, J. A. (2004). Meta-Analytic studies of acceleration. In N. Colangelo, S. Assouline, & M. Gross (Eds.), A nation deceived: How schools hold back America's brightest students (pp. 13-22). Iowa City: University of Iowa
17. Kulik, J. A., & Kulik, C. C. (1992). Meta-Analytic findings on grouping programs. Gifted Child Quarterly, 36, 73-77. doi:10.1177/001698 629203600204
18. Lohman, D. F., & Korb, K. A. (2006). Gifted today but not tomorrow?. Longitudinal changes in ability and achievement during elementary school. Journal for the Education of the Gifted, 29, 451-484
19. Lou, Y. Abrami, P. C., & Spence, J. (2000). Effects of within-class grouping on student achievement: An exploratory model. Journal of Educational Research, 94, 101-112
20. Lou, Y., Abrami, P. C., Spence, J. C., Poulsen, C., Chambers, B., & d'Apollonia, S. (1997). Within-class grouping: A meta-Analysis. In E. Dubinsky, D. Mathews, B. E. Reynolds, E. Dubinsky, D. Mathews, & B. E. Reynolds (Eds.), Readings in cooperative learning for undergraduate mathematics (pp. 109-131). Washington, DC: The Mathematical Association of America
21. Lubinski, D., & Benbow, C. P. (2006). Study of Mathematically Precocious Youth after 35 years: Uncovering antecedents for the development of math-science expertise. Perspectives on Psychological Science, 1, 316-345
22. Marsh, H. W., & Parker, J. (1984). Determinants of student self-concept: Is it better to be relatively large fish in a small pond even if you don't learn to swim as well?. Journal of Personality and Social Psychology, Psychology, 47, 213-231
23. McCaffrey, D. F., Lockwood, J. R., Koretz, D. M., & Hamilton, L. S. (2003). Evaluating value-Added models for teacher accountability. Santa Monica, CA: The RAND Corporation
24. McCall, M. S., Hauser, C., Cronin, J., Kingsbury, G. G., & Houser, R. L. (2006). Achievement Gaps: An examination of differences in student achievement and growth. Portland, OR: Northwest Evaluation Association
25. McCall, M. S, , Kingsbury, G., & Olson, A. (2004). Individual growth and school success: A technical report from the NWEA growth research database. Portland, OR: Northwest Evaluation Association
26. McCoach, D. B., O'Connell, A. A., Reis, S. M., & Levitt, H. A. (2006). Growing readers: A hierarchical linear model of children's reading growth during the first 2 years of school. Journal of Educational Psychology, 98, 14-28. doi:10.1037/0022-0663.98.1.14
27. Mendoza, C. (2006). Inside today's classrooms: Teacher voices on No Child Left Behind and the education of gifted children. Roeper Review, 29, 28-31. doi:10.1080/02783190609554381
28. Meyer, D., Princiotta, D., & Lanahan, L. (2004). The summer after kindergarten: Children's activities and library use by socioeconomic status. Washington, DC: National Center for Educational Statistics. Retrieved from http://nces.ed.gov/pubsearch/pubsinfo.asp?pubid= 2004037
29. Mulkey, L. M., Catsambis, S., Steelman, L. C., & Crain, R. L. (2005). The long-Term effects of ability grouping in mathematics: A national investigation. Social Psychology of Education, 8, 137-177. doi:10.1007/.s11218-005-4014-6
30. National Association for Gifted Children. (2012). Growth in achievement of advanced students. Retrieved from http://www.nagc.org/sites/default/.files/Position%20Statement/Growth%20in%20Achievement%20of% 20Advanced%20Students.pdf
31. National Center for Education Statistics. (1999). Indicator of the month: Summer activities of students enrolled in grades 1-12. Retrieved from http://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=1999008
32. Northwest Evaluation Association. (2005). A few notes about reliability and validity as reported in NWEA reliability and validity estimates: Achievement level tests and Measures of Academic Progress. Portland, OR: Northwest Evaluation Association
33. Northwest Evaluation Association. (2008). RIT scale norms: For use with measures of academic progress. Portland, OR: Northwest Evaluation Association
34. Northwest Evaluation Association. (2012). Measures of academic progress (MAP): MAP basics overview. Retrieved from http://www.nwea.org/.sites/www.nwea.org/files/resources/MAPBasicsOverview-0.pdf
35. Popham, W. J. (1999). Classroom assessment: What teachers need to know (2nd ed.). Boston, MA: Allyn & Bacon
36. Putallaz, M., Baldwin, J., & Selph, H. (2005). The Duke University Talent Identification Program. Journal of High Ability Studies, 16, 41-54
37. Raudenbush, S., & Bryk, A. (2002). Hierarchical linear models (2nd ed.). London, UK: Sage
38. Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis: Modeling change and event occurrence. New York, NY: Oxford University Press
39. Slavin, R. E. (1987). Ability grouping and student achievement in elementary schools: A best-evidence synthesis. Review of Educational Research, 57, 293-336. doi:10.2307/1170460
40. Slavin, R. E. (1990). Achievement effects of ability grouping in secondary schools: A best-evidence synthesis. Review of Educational Research, 60, 471-499. doi:10.3102/00346543060003471
41. Subotnik, R. F., Olszewski-Kubilius, P., &Worrell, F. C. (2011). Rethinking giftedness and gifted education: A proposed direction forward based on psychological science. Psychological Science in the Public Interest, 12, 3-54. doi:10.1177/1529100611418056
42. Terzian, M., Moore, K., & Hamilton, K. (2009). Effective and promising summer learning programs and approaches for economically-disadvantaged children and youth. Retrieved from http://www.wallacefoundation.org/.knowledge-center/summer-And-extended-learning-Time/summerlearning/.documents/effective-And-promising-summer-learningprograms. Pdf
43. Wang, S., Jiao, H., & Zhang, L. (2012). Validation of longitudinal achievement constructs of vertically scaled computer adaptive tests: A multiple indicator latent growth modeling approach (Technical Report). Portland, OR: Northwest Evaluation Association
44. Wang, S., McCall, M., Jiao, H., & Harris, G. (2012, April). Construct validity and measurement invariance of computerized adaptive testing: Application to Measures of Academic Progress (MAP) using confirmatory factor analysis. Paper presented at the meeting of the American Educational Research Association, Vancouver, British Columbia, Canada
45. Westat. (2000). ECLS-K base year public-use data files and electronic codebook (User's Manual). Retrieved from https://nces.ed.gov/pubs2001/.2001029rev-5-8.pdf
46. Wimer, C., Bouffard, S., Caronongan, P., Dearing, E., Simpkins, S., Little, P., & Weiss, H. (2006). What are kids getting into these days?. Demographic differences in youth out-of-school time participation. Retrieved from http://.www.hfrp.org/publications-resources/browse-our-publications/what-Arekids-getting-into-These-days-demographic-differences-in-youth-out-ofschool-Time-participation
47. Wyner, J., Bridgeland, J., & Diiulio, J. (2007). Achievement trap: How America is failing millions of high-Achieving students from lower-income families. Retrieved from http://www.jackkentcookefoundation.org/jkcf-web/.Documents/Achievement%20Trap.pdf
48. Xiang, Y., Dahlin, M., Cronin, J., Theaker, R., & Durant, S. (2011). Do high flyers maintain their altitude?. Performance trends of top students. Washington, DC: Thomas B. Fordham Institute. Retrieved from http://www.edexcellence.net/publications-issues/publications/highflyers. Html