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Okul Performansının Katma-Değerli Değerlendirilmesinde Kullanılan Yaygın İstatistik Modellerinin Karşılaştırmalı Analizi

Year 2017, Volume: 8 Issue: 3, 303 - 320, 30.09.2017
https://doi.org/10.21031/epod.321840

Abstract

Bu çalışmada iki yıllık bir standart test verisi kullanılarak bu veriden elde edilen katma-değerli ölçümler vasıtasıyla basit sabit etki modeli (SFEM) ve iki hiyerarşik doğrusal model (UHLMM ve AHLMM) analiz edilmiştir. Bu üç modelden elde edilen katma-değer ölçümleri, her modelin farklılıklarının etkisini belirlemek için analiz edildi. Bu katma değerli modellerin sonuçları arasında anlamlı ilişki olup olmadığını görmek için korelasyon analizine başvurulmuştur. SFEM ve UHLMM modelleri okul etkilerini benzer derecede sıralarken, SFEM ve AHLMM sonuçları orta derecede bir korelasyona sahiptir. Bu nedenle, okulların sıralamasına göre SFEM ve iki HLM modelinden elde edilen sonuçlar arasında çok fazla fark bulunmamıştır.

References

  • Amrein-Beardsley, A. (2008). Methodological concerns about the education value-added assessment system. Educational Researcher, 37(2), 65–75.
  • Aitkin, M., & Longford, N. (1986). Statistical modeling in school effectiveness studies. Journal of the Royal Statistical Society, A, 149,1–43.
  • Ballou, D., Sanders, W. L., & Wright, P. (2004). Controlling for student background in value-added assessment of teachers. Journal of Educational and Behavioral Statistics, 29, 37–66.
  • Braun, H. I. (2004). Value-added modeling: What does due diligence require? Princeton, NJ: Educational Testing Service.
  • Bryk, A. S., & S.W. Raudenbush. (1992). Hierarchical linear models: Applications and data analysis methods. Newbury Park, CA: Sage.
  • Doran, H., & L.T. Izumi. (2004). Putting education to the test: A value-added model for California. San Francisco, CA: Pacific Research Institute.
  • Doran, H. C., & Cohen, J. (2005). The confounding effect of linking bias on gains estimated from value-added models. In R. Lissitz (Ed.), Value-added models in education: Theory and application (pp.80–104). Maple Grove, MN: JAM Press.
  • Doran, H. C., & S. Fleischman. (2005). Challenges of value-added assessment. Educational Leadership, 63(3), 85–87.
  • Florida Department of Education. (2005). Florida Comprehensive Assessment Test (FCAT): Assessment and School Performance.
  • Hanushek, E. A. (1972). Education and Race: An Analysis of the Educational Production Process. Lexington, MA: Lexington Books.
  • Ladd, H. F., & Walsh, R. P. (2002), Implementing value-added measures of school effectiveness: Getting the incentives right. Economics of Education Review, 21, 1–17.
  • McCaffrey, D., Lockwood, J.R., Koretz, D, & Hamilton, L. (2003). Evaluating value-added models for teacher accountability. Washington, DC: RAND.
  • Murnane, R. J. (1975). The impact of school resources on the learning of children. Cambridge, MA: Ballinger Publishing Co.
  • Olson, L. (2004, November 16). “Value added” models gain in popularity. Education Week. Retrieved from http://www.edweek.org/ew/articles /2004/11/17/12value.h24.html
  • Raudenbush, S. W. (2004). What are value-added models estimating and what does this imply for statistical practice? Journal of Educational and Behavioral Statistics, 29, 121–129.
  • Raudenbush, S., & Bryk, A. S. (1986). A hierarchical model for studying school effects. Sociology of Education, 59, 1–17.
  • Raudenbush, S., & Bryk, A. (1988-89). Methodological advances in studying effects of schools and classrooms on student learning. In E. Z. Roth (Ed.), Review of research in education (pp. 423-475). Washington, DC: American Educational Research Association.
  • Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods. Newbury Park, CA: Sage Publications.
  • Sanders, W. L., & Horn, S. P. (1994). The Tennessee Value-Added Assessment System (TVAAS): Mixed model methodology in educational assessment. Journal of Personnel Evaluation in Education, 8, 299–311.
  • Sanders, W. L., Saxton, A. M., & Horn, S. P. (1997). The Tennessee Value-Added Educational Assessment System (TVAAS): A quantitative, outcomes-based approach to educational assessment. In J. Millman (Ed.), Grading teachers, grading schools: Is student achievement a valid evaluation measure? (pp. 137–162). Thousand Oaks, CA: Corwin Press.
  • Sanders, W. L., & Horn, S. (1998). Research findings from the Tennessee Value-Added Assessment System (TVAAS) database: Implications for educational evaluation and research. Journal of Personnel Evaluation in Education, 12, 247–256.
  • Sanders W. L. (2000). Annual CREATE Jason Millman Memorial Lecture: Value-added assessment from student achievement data: Opportunities and hurdles. Journal of Personnel Evaluation in Education, 14, 329–339.
  • Sanders, W. L., Saxton, A., Schneider, J., Dearden, B., Wright, S. P., & Horn, S. (2002). Effects of building change on indicators of student achievement growth: Tennessee Value-Added Assessment System. Knoxville: University of Tennessee Value-Added Research and Assessment Center.
  • Stewart, B. E. (2006). Value-added modeling: The challenge of measuring educational outcomes. New York, NY: Carnegie Corporation of New York.
  • Tekwe, C. D., Carter, R. L., Ma, C-X., Algina, J., Lucas, M. E., Roth, J., Ariet, M., Fisher, T., & Resnick, M. B. (2004). An empirical comparison of statistical models for value-added assessment of school performance. Journal of Educational and Behavioral Statistics, 29, 11–36.
  • Wainer, H. (2004). Introduction to a special issue of the journal of educational and behavioral statistics on value-added assessment. Journal of Educational and Behavioral Statistics, 29(1), 1–3.
  • Wiley, E. W. (2006). A practitioner’s guide to value-added assessment. Retrieved from http://nepc.colorado.edu/files/Wiley_APractitionersGuide.pdf

Comparative Analysis of Common Statistical Models Used for Value-Added Assessment of School Performance

Year 2017, Volume: 8 Issue: 3, 303 - 320, 30.09.2017
https://doi.org/10.21031/epod.321840

Abstract

The purpose of this study was to compare four popular value-added models used in measuring school effectiveness based on their distinguishing characteristics. In this study, the simple fixed effects model (SFEM), two hierarchical models (UHLMM and AHLMM), and the layered mixed effects model (LMEM) were analyzed using value-added measures obtained from a common data set with two years standard assessment data. Value-added measures obtained from these four models were analyzed to determine the impact of the differences of each model. Correlational analyses were also conducted to see whether there were meaningful relationships among these value-added models. SFEM and UHLMM models produced very similar rank orders of school effects while SFEM and AHLMM had only a moderate correlations. Thus there was not much difference between SFEM and two HLM models in terms of the rank orders of schools. Further, there was no agreement between LMEM and the other models.  Bu çalışmanın amacı, okul etkililiğini
ölçmede yaygın olarak kullanılan üç katma-değerli modeli ayırt edici
özelliklerine dayanarak karşılaştırmaktır. 

References

  • Amrein-Beardsley, A. (2008). Methodological concerns about the education value-added assessment system. Educational Researcher, 37(2), 65–75.
  • Aitkin, M., & Longford, N. (1986). Statistical modeling in school effectiveness studies. Journal of the Royal Statistical Society, A, 149,1–43.
  • Ballou, D., Sanders, W. L., & Wright, P. (2004). Controlling for student background in value-added assessment of teachers. Journal of Educational and Behavioral Statistics, 29, 37–66.
  • Braun, H. I. (2004). Value-added modeling: What does due diligence require? Princeton, NJ: Educational Testing Service.
  • Bryk, A. S., & S.W. Raudenbush. (1992). Hierarchical linear models: Applications and data analysis methods. Newbury Park, CA: Sage.
  • Doran, H., & L.T. Izumi. (2004). Putting education to the test: A value-added model for California. San Francisco, CA: Pacific Research Institute.
  • Doran, H. C., & Cohen, J. (2005). The confounding effect of linking bias on gains estimated from value-added models. In R. Lissitz (Ed.), Value-added models in education: Theory and application (pp.80–104). Maple Grove, MN: JAM Press.
  • Doran, H. C., & S. Fleischman. (2005). Challenges of value-added assessment. Educational Leadership, 63(3), 85–87.
  • Florida Department of Education. (2005). Florida Comprehensive Assessment Test (FCAT): Assessment and School Performance.
  • Hanushek, E. A. (1972). Education and Race: An Analysis of the Educational Production Process. Lexington, MA: Lexington Books.
  • Ladd, H. F., & Walsh, R. P. (2002), Implementing value-added measures of school effectiveness: Getting the incentives right. Economics of Education Review, 21, 1–17.
  • McCaffrey, D., Lockwood, J.R., Koretz, D, & Hamilton, L. (2003). Evaluating value-added models for teacher accountability. Washington, DC: RAND.
  • Murnane, R. J. (1975). The impact of school resources on the learning of children. Cambridge, MA: Ballinger Publishing Co.
  • Olson, L. (2004, November 16). “Value added” models gain in popularity. Education Week. Retrieved from http://www.edweek.org/ew/articles /2004/11/17/12value.h24.html
  • Raudenbush, S. W. (2004). What are value-added models estimating and what does this imply for statistical practice? Journal of Educational and Behavioral Statistics, 29, 121–129.
  • Raudenbush, S., & Bryk, A. S. (1986). A hierarchical model for studying school effects. Sociology of Education, 59, 1–17.
  • Raudenbush, S., & Bryk, A. (1988-89). Methodological advances in studying effects of schools and classrooms on student learning. In E. Z. Roth (Ed.), Review of research in education (pp. 423-475). Washington, DC: American Educational Research Association.
  • Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods. Newbury Park, CA: Sage Publications.
  • Sanders, W. L., & Horn, S. P. (1994). The Tennessee Value-Added Assessment System (TVAAS): Mixed model methodology in educational assessment. Journal of Personnel Evaluation in Education, 8, 299–311.
  • Sanders, W. L., Saxton, A. M., & Horn, S. P. (1997). The Tennessee Value-Added Educational Assessment System (TVAAS): A quantitative, outcomes-based approach to educational assessment. In J. Millman (Ed.), Grading teachers, grading schools: Is student achievement a valid evaluation measure? (pp. 137–162). Thousand Oaks, CA: Corwin Press.
  • Sanders, W. L., & Horn, S. (1998). Research findings from the Tennessee Value-Added Assessment System (TVAAS) database: Implications for educational evaluation and research. Journal of Personnel Evaluation in Education, 12, 247–256.
  • Sanders W. L. (2000). Annual CREATE Jason Millman Memorial Lecture: Value-added assessment from student achievement data: Opportunities and hurdles. Journal of Personnel Evaluation in Education, 14, 329–339.
  • Sanders, W. L., Saxton, A., Schneider, J., Dearden, B., Wright, S. P., & Horn, S. (2002). Effects of building change on indicators of student achievement growth: Tennessee Value-Added Assessment System. Knoxville: University of Tennessee Value-Added Research and Assessment Center.
  • Stewart, B. E. (2006). Value-added modeling: The challenge of measuring educational outcomes. New York, NY: Carnegie Corporation of New York.
  • Tekwe, C. D., Carter, R. L., Ma, C-X., Algina, J., Lucas, M. E., Roth, J., Ariet, M., Fisher, T., & Resnick, M. B. (2004). An empirical comparison of statistical models for value-added assessment of school performance. Journal of Educational and Behavioral Statistics, 29, 11–36.
  • Wainer, H. (2004). Introduction to a special issue of the journal of educational and behavioral statistics on value-added assessment. Journal of Educational and Behavioral Statistics, 29(1), 1–3.
  • Wiley, E. W. (2006). A practitioner’s guide to value-added assessment. Retrieved from http://nepc.colorado.edu/files/Wiley_APractitionersGuide.pdf
There are 27 citations in total.

Details

Journal Section Articles
Authors

Sedat Sen

Seock-Ho Kim This is me

Allan S. Cohen This is me

Publication Date September 30, 2017
Acceptance Date September 8, 2017
Published in Issue Year 2017 Volume: 8 Issue: 3

Cite

APA Sen, S., Kim, S.-H., & Cohen, A. S. (2017). Okul Performansının Katma-Değerli Değerlendirilmesinde Kullanılan Yaygın İstatistik Modellerinin Karşılaştırmalı Analizi. Journal of Measurement and Evaluation in Education and Psychology, 8(3), 303-320. https://doi.org/10.21031/epod.321840