Detecting gender-based differential item functioning on a constructed-response science test

Applied Measurement in Education

Volumn 12, Issue 3, 1999, Pages 211-235

  Hamilton, Laura S ^a  

^a RAND CORPORATION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0033413583     PISSN: 08957347     EISSN: None     Source Type: Journal    
DOI: 10.1207/S15324818AME1203_1     Document Type: Article

References (50)

1. Ackerman, T. A. (1992). A didactic explanation of item bias, item impact, and item validity from a multidimensional perspective. Journal of Educational Measurement, 29, 67-91.
2. Agresti, A. (1990). Categorical data analysis. New York: Wiley.
3. Angoff, W. H. (1993). Perspectives on differential item functioning methodology. In P. W. Holland & H. Wainer (Eds.), Differential item functioning (pp. 3-23). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.
4. Becker, B. J. (1989). Gender and science achievement: A reanalysis of studies from two meta-analyses. Journal of Research in Science Teaching, 26, 141-169.
5. Beller, M., & Gafni, N. (1996). The 1991 International Assessment of Educational Progress in Mathematics and Sciences: The gender differences perspective. Journal of Educational Psychology, 88, 365-377.
6. Bock, D., Gibbons, R., & Muraki, E. (1988). Full-information item factor analysis. Applied Psychological Measurement, 12, 261-280.
7. Bolger, N., & Kellaghan, T. (1990). Method of measurement and gender differences in scholastic achievement. Journal of Educational Measurement, 27, 165-174.
8. Burkam, D. T., Lee, V. E., & Smerdon, B. A. (1997). Gender and science learning early in high school: Subject matter and laboratory experiences. American Educational Research Journal, 34, 297-331.
9. Clauser, B. E., Nungester, R. J., Mazor, K., & Ripkey, D. (1996). A comparison of alternative matching strategies for DIF detection in tests that are multidimensional. Journal of Educational Measurement, 33, 202-214.
10. Clauser, B. E., Nungester, R. J., & Swaminathan, H. (1997). Improving the matching for DIF analysis by conditioning on both test score and an educational background variable. Journal of Educational Measurement, 33, 453-464.
11. Cole, N. S. (1997). The ETS gender study: How males and females perform in educational settings. Princeton, NJ: Educational Testing Service.
12. Donoghue, J. R., Holland, P. W., & Thayer, D. T. (1993). A Monte Carlo study of factors that affect the Mantel-Haenszel and standardization measures of differential item functioning. In P. W. Holland & H. Wainer (Eds.), Differential item functioning (pp. 137-166). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.
13. Dunbar, S. B., Koretz, D. M., & Hoover, H. D. (1991). Quality control in the development and use of performance assessments. Applied Measurement in Education, 4, 289-303.
14. Fennema, E., & Tartre, L. A. (1985). The use of spatial visualization in mathematics by girls and boys. Journal for Research in Mathematics Education, 16, 184-206.
15. Fleming, M. L., & Malone, M. R. (1983). The relationship of student characteristics and student performance in science as viewed by meta-analysis research. Journal of Research in Science Teaching, 20, 481-495.
16. Frederiksen, N. (1984). The real test bias. American Psychologist, 39, 193-202.
17. French, A. W., & Miller, T. R. (1996). Logistic regression and its use in detecting differential item functioning in polytomous items. Journal of Educational Measurement, 33, 315-332.
18. Halpern, D. F. (1992). Sex differences in cognitive abilities (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.
19. Halpern, D. F. (1997). Sex differences in intelligence: Implications for education. American Psychologist, 52, 1091-1102.
20. Hamilton, L. S. (1997). Construct validity of constructed-response assessments: Male and female high school science performance. Unpublished doctoral dissertation, Stanford University, School of Education, Stanford, CA.
21. Hamilton, L. S., Nussbaum, E. M., Kupermintz, H., Kerkhoven, J. I. M., & Snow, R. E. (1995). Enhancing the validity and usefulness of large scale educational assessments: II. NELS:88 Science Achievement. American Educational Research Journal, 32, 555-581.
22. Hamilton, L. S., Nussbaum, E. M., & Snow, R. E. (1997). Interview procedures for validating science assessments. Applied Measurement in Education, 10, 181-200.
23. Hanna, G. (1989). Mathematics achievement of girls and boys in grade eight: Results from twenty countries. Educational Studies in Mathematics, 20, 225-232.
24. Hauck, W. W. (1983). A note on confidence bands for the logistic response curve. The American Statistician, 37, 158-160.
25. Johnson, S. (1987). Gender differences in science: Parallels in interest, experience, and performance. International Journal of Science Education, 9, 467-481.
26. Jones, L. R., Mullis, I. V. S., Raizen, S. A., Weiss, I. R., & Weston, E. A. (1992). The 1990 science report card: NAEP's assessment of fourth, eighth, and twelfth graders. Princeton, NJ: Educational Testing Service.
27. Jovanovic, J., Solano-Flores, G., & Shavelson, R. J. (1994). Performance-based assessments: Will gender differences in science achievement be eliminated? Education and Urban Society, 26, 352-366.
28. Linn, M. C. (1985). Fostering equitable consequences from computer learning environments. Sex Roles, 13, 229-240.
29. Linn, M. C., & Hyde, J. S. (1989). Gender, mathematics, and science. Educational Researcher, 18(8), 17-19, 22-27.
30. Lohman, D. F. (1993). Spatially gifted, verbally inconvenienced. In Wallace symposium on talent development. Symposium conducted at the University of Iowa, Iowa City.
31. Mazor, K. M., Kanjee, A., & Clauser, B. E. (1995). Using logistic regression and the Mantel-Haenszel with multiple ability estimates to detect differential item functioning. Journal of Educational Measurement, 32, 131-144.
32. Mazzeo, J., Schmitt, A. P., & Bleistein, C. A. (1993). Sex-related performance differences on constructed-response and multiple-choice sections of Advanced Placement Examinations (College Board Rep. No. 92-7). New York: College Entrance Examination Board.
33. Miller, T. R., & Spray, J. A. (1993). Logistic discriminant function analysis for DIF identification of polytomously scored items. Journal of Educational Measurement, 30, 107-122.
34. Mullis, I. V. S., Dossey, J. A., Owen, E. H., & Phillips, G. W. (1991). The state of mathematics achievement: Executive summary (Report No. 21-ST-04). Washington, DC: National Center for Education Statistics.
35. National Assessment of Educational Progress. (1988). The science report card: Elements of risk and recovery: Trends and achievement levels based on the 1986 National Assessment. Princeton, NJ: Educational Testing Service.
36. Nussbaum, E. M., Hamilton, L. S., & Snow, R. E. (1997). Enhancing the validity and usefulness of large scale educational assessments: IV. NELS:88 science performance through the twelfth grade. American Educational Research Journal, 34, 151-173.
37. O' Neill, K. A., & McPeek, W. M. (1993). Item and test characteristics that are associated with differential item functioning. In P. W. Holland & H. Wainer (Eds.), Differential item functioning (pp. 255-276). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.
38. Pollack, J. M., & Rock, D. A. (1997). Constructed-response tests in the NELS:88 High School Effectiveness Study (NCES 97-804). Washington, DC: National Center for Education Statistics.
39. Rauscher, F. H., Krauss, R. M., & Chen, Y. (1996). Gesture, speech, and lexical access: The role of lexical movements in speech production. Psychological Science, 7, 226-231.
40. Resnick, L. B., & Resnick, D. P. (1992). Assessing the thinking curriculum: New tools for educational reform. In B. R. Gifford & M. C. O'Connor (Eds.), Changing assessments: Alternative views of aptitude, achievement, and instruction (pp. 35-75). Boston: Kluwer.
41. Rock, D. A., & Pollack, J. M. (1995). Psychometric report for the NELS:88 base year through second follow-up (NCES Rep. No. 95-382). Washington, DC: National Center for Education Statistics.
42. Shavelson, R. J., Carey, N. B., & Webb, N. M. (1990). Indicators of science achievement: Options for a powerful policy instrument. Phi Delta Kappan, 71, 692-697.
43. Somes, G. W. (1986). The generalized Mantel-Haenszel statistic. The American Statistician, 40, 106-108.
44. Swaminathan, H., & Rogers, H. J. (1990). Detecting differential item functioning using logistic regression procedures. Journal of Educational Measurement, 27, 361-370.
45. Wang, N., & Lane, S. (1996). Detection of gender-related differential item functioning in a mathematics performance assessment. Applied Measurement in Education, 9, 175-199.
46. Welch, C. J., & Miller, T. R. (1995). Assessing differential item functioning in direct writing assessments: Problems and an example. Journal of Educational Measurement, 32, 163-178.
47. Young, D. J., & Fraser, B. J. (1994). Gender differences in science achievement: Do school effects make a difference? Journal of Research in Science Teaching, 31, 857-871.
48. Zwick, R. (1990). When do item response function and Mantel-Haenszel definitions of differential item functioning coincide? Journal of Educational Statistics, 15, 185-197.
49. Zwick, R., Donoghue, J. R., & Grima, A. (1993). Assessment of differential item functioning for performance tasks. Journal of Educational Measurement, 30, 233-251.
50. Zwick, R., & Ercikan, K. (1989). Analysis of differential item functioning in the NAEP History Assessment. Journal of Educational Measurement, 26, 55-66.