Using Rasch theory to guide the practice of survey development and survey data analysis in science education and to inform science reform efforts: An exemplar utilizing STEBI self-efficacy data

Science Education

Volumn 95, Issue 2, 2011, Pages 258-280

  Boone, William J ^a   Townsend, J Scott ^b   Staver, John ^c  

^a MIAMI UNIVERSITY   (United States)

^b EASTERN KENTUCKY UNIVERSITY   (United States)

^c PURDUE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 79551713224     PISSN: 00368326     EISSN: 1098237X     Source Type: Journal    
DOI: 10.1002/sce.20413     Document Type: Article

References (51)

1. American Association for the Advancement of Science. (1990). Project 2061: Science for all Americans. New York: Oxford University Press.
2. Andrich, D. (1978). A rating formulation for ordered response categories. Psychometrika, 43(4), 561-573.
3. Baghaei, P. (2008). The Rasch model as a construct validity tool. Rasch Measurement Transactions, 22(1), 1145-1146.
4. Bond, T. G., & Fox, C. M. (2007). Applying the Rasch model: Fundamental measurement in the human sciences (2nd ed.). Mahwah, NJ: Erlbaum.
5. Boone, W., & Scantlebury, K. (2006). The role of Rasch analysis when conducting science education research utilizing multiple-choice tests. Science Education, 90, 253-269.
6. Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical linear models: Applications and data analysis methods. Newbury Park, CA: Sage.
7. Bryk, A. S., Thum, Y. M., Easton, J. Q., & Luppescu, S. (1998). Academic productivity of Chicago public elementary schools: A technical report. Chicago: Consortium on Chicago School Research.
8. Choppin, B. H. L. (1985). Lessons for psychometrics from thermometry. Evaluation in Education, 9(1), 9-12.
9. Cronbach, L. J. (1950). Further evidence on response sets and test design. Educational and Psychological Measurement, 10(1), 3-31.
10. Desouza, S., Boone, W. J., & Yilmaz, O. (2004). A study of science teaching self-efficacy and outcome expectancy beliefs of teachers in Southern India. Science Education, 88(6), 837-854.
11. Donnelly, L. A., & Boone, W. J. (2007). Biology teachers' attitudes toward and use of Indiana's evolution standards. Journal of Research in Science Teaching, 44, 236-257.
12. Endler, L. C., & Bond, T. R. (2001). Cognitive development in a secondary science setting. Research in Science Education, 30(4), 403-416.
13. Enochs, L. G., & Riggs, I. M. (1990). Further development of an elementary science teaching efficacy belief instrument: A preservice elementary scale. School Science and Mathematics, 90(8), 694-706.
14. Fischer, G. H., & Molenaar, I. W. (Eds.). (1995). Rasch models: Foundations, recent developments, and applications. New York: Springer-Verlag.
15. Fisher, W. P., Jr. (2000). Survey design and recommendations. Popular Measurement, 3(1), 58-60.
16. Fox, C. M., & Jones, J. A. (1998). Use of Rasch modeling in counseling psychology research. Journal of Counseling Psychology, 45(1), 30-45.
17. Gall, M. D., Gall, J. P., & Borg, W. R. (2003). Educational research: An introduction (7th ed.). Boston: Allyn & Bacon.
18. Green, K. E. (1996). Applications of the Rasch model to evaluation of survey data quality. New Directions for Evaluation, 70, 81-92.
19. Hayes, J. R. (1981). The complete problem solver. Philadelphia: Franklin Institute Press.
20. Kuhn, T. S. (1970). The structure of scientific revolutions. Chicago: University of Chicago Press.
21. Lee, J. (2004). Evaluating the effectiveness of instructional resource allocation and use: IRT and HLM analysis of NAEP teacher survey and student assessment data. Studies in Educational Evaluation, 30(2), 175-199.
22. Linacre, J. M. (1996). Classification and measurement. Rasch Measurement Transactions, 10(2), 489-490.
23. Linacre, J. M. (1998). Detecting multidimensionality: Which residual data-type works best? Journal of Outcome Measurement, 2(3), 266-283.
24. Linacre, J. M. (2005, June). Measurement, meaning and morality. Paper presented at the Pacific Rim Objective Measurement Symposium (PROMS) & International Symposium on Measurement & Evaluation (ISME), 2005, Kuala Lumpur, Malaysia.
25. Linacre, J. M. (2009a). Practical Rasch measurement-Core topics [Online course].
26. Linacre, J. M. (2009b). WINSTEPS [Software and user's guide]. Chicago: Winsteps.
27. Linn, R. L., Baker, E. L., & Dunbar, S. B. (1991). Complex, performance-based assessment: Expectations and validation criteria. Educational Researcher, 20(8), 15-21.
28. Liu, X. (2007). Growth in students' understanding of matter during an academic year and from elementary through high school. Journal of Chemical Education, 84(11), 1853-1856.
29. Luce, R. D., & Tukey, J. W. (1964). Simultaneous conjoint measurement: A new type of fundamental measurement. Journal of Mathematical Psychology, 1(1), 1-27.
30. Masters, G. N. (1982). A Rasch model for partial credit scoring. Psychometrika, 47(2), 149-174.
31. Masters, G. N. (2005). Continuity and growth: Key considerations in educational improvement and accountability. E. Melbourne, Victoria, Australia: Centre for Strategic Education.
32. Meijer, R. R. (2002). Outlier detection in high-stakes certification testing. Journal of Educational Measurement, 39(3), 219-233.
33. Moore, R. W., & Foy, R. L. H. (1997). The scientific attitude inventory: A revision (SAI II). Journal of Research in Science Teaching, 34(4), 327-336.
34. Nehm, R. H., & Schonfeld, I. S. (2008). Measuring knowledge of natural selection: A comparison of the CINS, and open-response instrument, and oral interview. Journal of Research in Science Teaching, 45(10), 1131-1160.
35. Planinic, M., Boone, W.J., Krsnik, R., & Beilfuss, M. (2006). Exploring alternative conceptions from Newtonian dynamics and simple DC circuits: Links between item difficulty and item confidence. Journal of Research in Science Teaching, 43(2), 150-171.
36. Rasch, G. (1960). Probabilistic models for some intelligence and attainment tests. Copenhagen, Denmark: Danmarks Paedagogiske Institut.
37. Ritter, J. M., Boone, W. J., & Rubba, P. A. (2001). Development of an instrument to assess prospective elementary teacher self-efficacy beliefs about equitable science teaching and learning (SEBEST). Journal of Science Teacher Education, 12, 175-198.
38. Rossi, P. H., Wright, J. D., & Anderson, A. B. (Eds.). (1983). Handbook of survey research. New York: Academic Press.
39. Rowe, K. J. (2007, September). ASSESS and ASSIST: Capacity building for all teachers of students with and without learning difficulties. Background paper to keynote address presented at the combined LDA, RSTAQ, and SPELD Associations Conference, Brisbane, Australia.
40. Rowe, K. J., Hill, P. W., & Holmes-Smith, P. (1994, November). Assessing, recording and reporting students' educational progress: The case for profiles. Paper presented at the annual conference of the Australian Association for Research in Education, Newcastle, New South Wales, Australia.
41. Siegel, S. (1956). Nonparametric statistics for the behavioral sciences. New York: McGraw-Hill.
42. Smith, R. M. (1991). The distributional properties of Rasch item fit statistics. Educational and Psychological Measurement, 51, 541-565.
43. Smith, R. M., Linacre, J. M., & Smith, E. V. Jr. (2003). Guidelines for manuscripts. Journal of Applied Measurement, 4, 198-204.
44. Stenner, A. J. (1996, October). Measuring reading comprehension with the Lexile framework. Paper presented at the California Comparability Symposium, Burlingame, CA.
45. Stenner, A. J., Burdick, H., Sanford, E. E., & Burdick, D. S. (2006). How accurate are Lexile text measures? Journal of Applied Measurement, 7(3), 307-322.
46. Williamson, G. L. (2006, April). Student readiness for postsecondary endeavors. Paper presented at the Annual Meeting of the American Educational Research Association, San Francisco, CA.
47. Wilson, M. (2005). Constructing measures: An item response modeling approach. Mahwah, NJ: Erlbaum.
48. Wright, B. D. (1968, February). Sample-free test calibration and person measurement. Paper presented at the National Seminar on Adult Education Research, Chicago, IL.
49. Wright, B. D. (1984). Despair and hope for educational measurement. Contemporary Education Review, 3(1), 281-288.
50. Wright, B. D., & Stone, M. H. (1979). Best test design. Chicago: Mesa Press.
51. Wright, B. D., & Stone, M. H. (2004). Making measures. Chicago: Phaneron Press.