The effects of student composition on school outcomes

School Effectiveness and School Improvement

Volumn 15, Issue 2, 2004, Pages 177-199

  Harker, Richard ^a   Tymms, Peter ^b  

^a MASSEY UNIVERSITY   (New Zealand)

^b DURHAM UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 3142743161     PISSN: 09243453     EISSN: None     Source Type: Journal    
DOI: 10.1076/sesi.15.2.177.30432     Document Type: Article

References (46)

1. Biddle, B.J., & Berliner, D.C. (2002). What research says about unequal funding for schools in America. Education Policy Reports Project, Arizona State University. Downloaded (Oct. 2003) from: http://www.asu.edu/educ/ epsl/EPRP/Reports/EPRP-0202-103.pdf
2. Bryk, A.S., & Raudenbush, S.W. (1992). Hierarchical linear models: Applications and data analysis methods. Newbury Park, CA: Sage.
3. Bums, R.B., & Mason, D.A. (2002). Class composition and student achievement in elementary schools. American Educational Research Journal, 39(1), 207-233.
4. Campbell, D.T. (1969). Reforms as experiments. American Psychologist, 24, 409-429.
5. Chubb, J., & Moe, T. (1990). Politics, markets, and America's schools. Washington, DC: The Brookings Institute.
6. Cook, T.D. (2002). Randomized experiments in educational policy research: A critical examination of the reasons the educational evaluation community has offered for not doing them. Educational Evaluation and Policy Analysis, 24(3), 175-199.
7. Daly, P. (1995). Public accountability and the academic effectiveness of grant-aided Catholic schools. School Effectiveness and School Improvement, 6, 367-379.
8. Edwards, T., Fitz, J., & Whitty, G. (1989). The state and private education: An evaluation of the assisted places scheme. London: The Palmer Press.
9. Fiske, E.B., & Ladd, H.F. (2000). When schools compete: A cautionary tale. Washington, DC: The Brookings Institute.
10. Fitz-Gibbon, C.T. (1996). Monitoring education: Indicators, quality and effectiveness. London: Cassell.
11. Fitz-Gibbon, C.T., & Stephenson-Forster, N.J. (1999). Is Ofsted helpful? An evaluation using social science criteria. In C. Cullingford (Ed.), An inspector calls: Ofsted and its effect on school standards (pp. 97-118). London: Kogan Page.
12. Gaffney, M., & Smith, A. (1999). Evaluation of the TIE scheme: Summary report. Dunedin, NZ: University of Otago, Children's Issues Centre.
13. Harker, R., & Nash, R. (1996). Academic outcomes and school effectiveness: Type "A" and type "B" effects. New Zealand Journal of Educational Studies, 32(2), 143-170.
14. Harris, J.R. (1998). The nurture assumption. London: Bloomsbury.
15. Hauser, R.M. (1970). Context and consex: A cautionary tale. American Journal of Sociology, 75, 645-654.
16. Hauser, R.M. (1974). Contextual analysis revisited. Sociological Methods and Research, 2(3), 365-375.
17. Kreft, I., & De Leeuw, J. (1998). Introducing multilevel modelling. London: Sage.
18. Lauder, H., & Hughes, D. (1999). Trading in futures: Why markets in education don't work. Milton Keynes, UK: Open University Press.
19. Lee, V.E., Bryk, A.S., & Smith, J.B. (1993). The organization of effective secondary schools. In L. Darling-Hammond (Ed.), Review of research in education, 19, 171-267.
20. Marsh, H.W. (1987). The Big-Fish-Little-Pond effect on academic self concept. Journal of Educational Psychology, 79, 280-295.
21. Marsh, H.W., Byrne, B.M., & Shavelson, R.J. (1988). A multifaceted academic self-concept: Its hierarchical structure and its relation to academic achievement. Journal of Educational Psychology, 80, 366-380.
22. Nash, R. (2002). Peer effects and peer group processes: Joining the conversation on quantitative and qualitative methods. Australian Journal of Education, 46(1), 6-18.
23. Powell, A., Farrar, E., & Cohen, D. (1985). The shopping mall high school: Winners and losers in the educational marketplace. Boston: Houghton Mifflin.
24. Raudenbush, S.W., Rowan, B., & Kang, S.J. (1991). A multilevel, multivariate model for studying school climate in secondary schools with estimation via the EM algorithm. Journal of Educational Statistics, 16, 295-330.
25. Raudenbush, S.W., & Sampson, R. (1999). Assessing direct and indirect effects in multilevel designs with latent variables. Sociological Methods and Research, 25(2), 123-153.
26. Robinson, W.S. (1950). Ecological correlations and the behavior of individuals. American Sociological Review, 15(3), 351-357.
27. Snijders, T., & Bosker, R. (1999). Multilevel analysis: An introduction to basic and advanced multilevel modeling. London: Sage.
28. Teddlie, C., & Reynolds, D. (Eds.). (2000). The international handbook of school effectiveness research. London: Palmer Press.
29. Teddlie, C., & Stringfield, S. (1993). Schools make a difference: Lessons learned from a 10-year study of school effects. New York: Teachers College Press.
30. Teddlie, C., Stringfield, S., & Reynolds, D. (2000). Context issues within school effectiveness research. In C. Teddlie & D. Reynolds (Eds.), The international handbook of school effectiveness research (pp. 160-185). London: Palmer Press.
31. Thomas, S., & Mortimore, P. (1994). Report on value added analysis of 1993 GCSE examination results in Lancashire. London: Curriculum Studies Department, University of London Institute of Education.
32. Thrupp, M. (1999). Schools making a difference: Let's be realistic! Buckingham, UK: Open University Press.
33. Tooley, J. (1999). The global education industry: Lessons from private education in developing countries. London: IEA Education and Training Unit in association with the International Finance Corporation.
34. Tymms, P.B. (1992). The relative effectiveness of post-16 institutions in England (including Assisted Places Scheme schools). British Educational Research Journal, 18(2), 175-192.
35. Tymms, P.B. (1999a). Baseline assessment and monitoring in primary schools: Achievements, attitudes and value-added indicators. London: David Fulton.
36. Tymms, P.B. (1999b). Baseline assessment, value-added and the prediction of reading. Journal of Research in Reading, 22(1), 27-36.
37. Tymms, P.B. (2001a). The development of a computer-adaptive assessment in the early years. Educational and Child Psychology, 18(3), 20-30.
38. Tymms, P.B. (2001b). A test of the Big Fish in a Little Pond hypothesis: An investigation into the feelings of seven-year-old pupils in school. School Effectiveness and School Improvement, 12, 161-181.
39. Tymms, P.B., Fitz-Gibbon, C.T., Hazelwood, R.D., & McCabe, J.J.C. (1990). The effect of a national initiative on exam results, School Effectiveness and School Improvement, 1, 281-298.
40. Wilkinson, I.A.G., Hattie, J.A., Parr, J.M., & Townsend, M.A.R. (2000). Influence of peer effects on learning outcomes: A review of the literature. Wellington, NZ: Ministry of Education.
41. Willms, J.D. (1985). Catholic school effects on academic achievement: New evidence from the High School and Beyond follow-up study. Sociology of Education, 58, 98-114.
42. Willms, J.D. (1986). Social class segregation and its relationship to pupils' examination results in Scotland. American Sociological Review, 51, 224-241.
43. Willms, J.D. (1992). Monitoring school performance: A guide for educators. Lewes, UK: Palmer.
44. Willms, J.D. (2000, March). Three hypotheses about community effects relevant to the contribution of human and social capital to sustain economic growth and well-being. Paper presented at the OECD and Human Resources Development Canada Conference, Quebec City, Canada.
45. Willms, J.D., & Raudenbush, S.W. (1989). A longitudinal hierarchical linear model for estimating school effects and their stability. Journal of Educational Measurement, 26(3), 209-232.
46. Wylie, C. (1999). Is the land of the flightless bird the home of the voucherless voucher? New Zealand Journal of Educational Studies, 34(1), 99-109.