Item Treatments on National Assessment of US History
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
In order to study the trends in educational progress and to measure the changes in performance, existing assessment instrument, administration procedures, and analysis techniques had to be retained over time. Such instruments as the NAEP in the US and the NAEA in Korea use the IRT to analyze data and to calibrate items by a subscale. During the process of estimating item parameters, checks are performed to make sure that the IRT models fit the data. However, there is no clear criterion to assist psychometric practitioners at treating items in scaling for national assessment of students' achievement, such as the NAEP and the NAEA. The objective of the current study is to investigate the impact of item treatments, specifically splitting trend items by assessment years, in scaling on the NAEP trend reporting scores. Specifically, this study investigates how item treatments, in scaling, change other item estimates in US history tests. By splitting items, the proficiency level of some students had little impact on US history subscales. In addition, this study examines how splitting items by assessment years affect reporting trend scores.
Abstract
In order to study the trends in educational progress and to measure the changes in performance, existing assessment instrument, administration procedures, and analysis techniques had to be retained over time. Such instruments as the NAEP in the US and the NAEA in Korea use the IRT to analyze data and to calibrate items by a subscale. During the process of estimating item parameters, checks are performed to make sure that the IRT models fit the data. However, there is no clear criterion to assist psychometric practitioners at treating items in scaling for national assessment of students' achievement, such as the NAEP and the NAEA. The objective of the current study is to investigate the impact of item treatments, specifically splitting trend items by assessment years, in scaling on the NAEP trend reporting scores. Specifically, this study investigates how item treatments, in scaling, change other item estimates in US history tests. By splitting items, the proficiency level of some students had little impact on US history subscales. In addition, this study examines how splitting items by assessment years affect reporting trend scores.
참고문헌 (10)
- Chapter 11 Scaling Procedures. In The NAEP 1996 Technical Report, "Allen, N. L", National Center for Education Statistics, ~, pp.NCES 1999-452 (1999)
- Birnbaum, A., "Some Latent Trait Models and Their Use in Inferring an Examinee's Ability'. In Statistical Theories of Mental Test Scores", pp.397~472 (1968), Addison-Wesley
- Chapter 13 Data Analysis for the Science Assessment. In The NAEP 1996 Technical Report, "Donoghue, J. R.", National Center for Education Statistics, ~, pp.NCES 1999-452 (1999)
- Hambleton, R. K, "Item Response Theory: Principles and applications" (1985), Kluwer Academic Publishers
- Lord, F. M, "Applications of item response theory to practical testing problems" (1980), Lawrence Erlbaum Associates
- Mislevy, R. J., "Scaling procedures in NAEP", Journal of Educational Statistics, 17(2), pp.131~154 (1992)
- Muraki, E., "A generalized partial credit model: Application of an EM algorithm", Applied Psychological Measurement, 16(2), pp.159~176 (1992)
- Muraki, E., "PARSCALE: Parameter scaling of rating data" (1991), Scientific Software, Inc.
- Stone, C. A., "Classification error and goodness-of-fit in IRT models", Paper presented at the 1994 Annual Meeting of the American Educational Research Association (1994), the American Educational Research Association
- Tay-Lim B.S-H, "The Impact of Item Treatments on NAEP Reporting Scale Scores", Paper presented at the annual meeting of the American Educational Research Association (2003), the American Educational Research Association