Developing a Macroscopic Lens Into Middle School Reform: Psychometric Properties of the AMLE SIA
Abstract views: 26
/ 
PDF downloads: 22
Keywords:
School Improvement Assessment, Validity, ReliabilityAbstract
The purpose of this study was to assess the validity and reliability of the AMLE SIA, which was developed by the NMSA to provide the best educational programs for young adolescents to improve their skills. To promote these skills, NMSA suggested that schools needs to implement 16 characteristics nested within three categories. However, many middle schools failed to implement the practices. The reason might be the instrument itself due to including 96 items and the design. Therefore, the validity of the instrument was analyzed; response organization system was redesigned; the items were revised and eliminated by using regression (83 items); and the final instrument’s validity was analyzed by using EFA (73% of variance explained) and the reliability (.98) was calculated.
References
Bryant, F. (2000). Assessing the validity of measurement. In L. G. Grimm, & P. R. Yarnold (Eds.), Reading and understanding more multivariate statistics (pp. 99-139). Washington, D.C.: American Psychological Association.
Cattell, R. B. (1978). The scientific use of factor analysis in behavioral and life sciences. New York: Plenum.
Cook, C., Faulkner, S., & Kinne, L. (2009). Indicators of middle school implementation: How do Kentucky’s schools to watch measure up? Research in Middle Level Education Online, 32, 1-10.
Cook, C., Heath, F., Thompson, R. L., & Thompson, B. (2001). Score reliability in webor internet-based surveys: Unnumbered graphic rating scales versus likert-type scales. Educational and Psychological
Measurement, 61(4), 697-706. de Winter, J. C. F., Dodou, D. & Wieringa, P. A. (2009). Exploratory factor analysis with small sample sizes. Multivariate Behavioral Research, 44(2), 147-181.
Graham, J. W. (2009). Missing data analysis: Making it work in the real world. Annual review of psychology, 60, 549-576.
Gorsuch, R. L. (1983). Factor analysis (2nd ed.). Hillsdale, NJ: Erlbaum.
Guilford, J. P. (1954). Psychometric methods (2nd ed.). New York: McGraw-Hill. Authors (2004).
Horn, J. L. (1965). A rationale and test for the number if factors in factor analysis. Psychometrika, 30, 179-185.
Jackson, S., & Lunenburg, F. (2010). School performance indicators, accountability ratings, and student achievement. American Secondary Education, 39, 27-44.
McEwin, C. K., & Greene, M. W. (2011). The status of programs and practices in America’s middle schools: Results from two national studies. Association for Middle Level Education. Retrieved from http://www.amle.org/portals/0/pdf/research/Research_from_the_Field/Status_Programs_Practices_AMLE.pdf.
Mertens, S. B., & Flowers, N. (2006). Middle Start’s impact on comprehensive middle school reform. Middle Grades Research Journal, 1, 1-26.
Mundfrom, D. J., Shaw, D. G., & Ke, T. L. (2005). Minimum sample size recommendations for conducting factor analyses. International Journal of Testing, 5, 159-168.
National Middle School Association. (2010). This we believe: Keys to educating young adolescents. Westerville, OH: National Middle School Association.
National Middle School Association. (2014). This we believe: Keys to educating young adolescents position paper of national middle school association executive summary. Retrieved from http://www.uww.edu/Documents/colleges/coeps/academics/This_We_Believe_Exec_Summary.pdf
Nunnally, J. C. (1967). Psychometric theory. New York: McGraw-Hill.
O’Connor, B. P. (2000). SPSS and SAS programs for determining the number of components using parallel analysis and Velicer’s MAP test. Behavioral Research Methods, Instrument, & Computers, 32(3), 396-402.
Preacher, K. J., & MacCallum, R. C. (2002). Exploratory factor analysis in behavior genetics research: Factor recovery with small sample sizes. Behavior Genetics, 32, 153-161.
Schimid, J., & Leiman, J. (1957). The development of hierarchical factor solutions. Psychometrica, 22, 53-61.
Thompson, B. (1992). A partial test distribution for cosines among factors across samples, In B. Thompson (Ed.), Advances in social science methodology (Vol. 2, pp. 81-97). Greenwich, CT: JAI Press.
Thompson, B. (2004). Exploratory and confirmatory factor analysis. Washington, DC: American Psychological Association.
Thompson, B., & Daniel, L. G. (1996). Factor analytic evidence for the construct validity of scores: A historicalreview and some guidelines. Educational and Psychological Measurement, 56(2), 197-208.
Thurstone, L. L. (1947). Multiple factor analysis. Chicago: University of Chicago Press.
Trochim, W. M. K. (2006). Measurement validity types. Research Methods Knowledge Base. Retrieved from http://www.socialresearchmethods.net/kb/measval.php.
Zientek, L. R., & Thompson, B. (2009). Matrix summaries improve research reports: Secondary analyses using published literature. Educational Researcher, 38(5), 343-352.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 Ayse Tugba Oner, Bilgin Navruz, Robert M. Capraro
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
