Equating Method for Prevent Discrimination in Classroom

Deni Iriyadi(1*), Dali Santun Naga(2), Wardani Rahayu(3),

(1) Universitas Negeri Jakarta
(2) Universitas Tarumanagara
(3) Universitas Negeri Jakarta
(*) Corresponding Author

Abstract


This study aims to determine effectivenes Simplified Cirlce Arc method used at the school level to prevent discrimination against student grades. This study National Examination data on mathematics subjects from of the Center for Educational Assessment in DKI Jakarta and Tangerang regions. Using the Rasch Model analysis, data obtained for 2135 in the DKI Jakarta (X) and 2271 in the Tangerang area (Y). The data was obtained after conducting Rasch analysis with Mean Square Outfit (MNSQ) of 0.5 <MNSQ <1.5. Replication is done 50 times for each form data distribution from each region. Results of replication then RMSE value is calculated. The results showed that equal form with normal data distribution, statistically the average RMSE with the Simplified Circle Arc method smaller than the average RMSE result of equalization with the Nominal Weight Mean method which indicates that the Simplified Circle Arc method more accurate than Nominal Weight Mean method. Likewise, with equal equations with positive skeweness and negative skewness data distribution, the average RMSE with the Simplified Circle Arc Method is smaller than average RMSE resulting in equalization of the score with Nominal Weight Mean method. A small RMSE value indicates a fairly accurate result of equalization.


Full Text:

PDF

References


Aminah, N. S. (2012). Karakteristik metode penyetaraan skor tes untuk data dikotomos. Jurnal Penelitian Dan Evaluasi Pendidikan, 16(Special Issue for UNY’s 48th Dies-Natalis), 88–101. https://doi.org/10.21831/pep.v16i0.1107

Anshel, M. H., Weatherby, N. L., Kang, M., & Watson, T. (2009). Rasch calibration of a unidimensional perfectionism inventory for sport. Psychology of Sport and Exercise, 10(1), 210–216. https://doi.org/10.1016/j.psychsport.2008.07.006

Antara, A. A. P., & Bastari, B. (2015). Penyetaraan Vertikal Dengan Pendekatan Klasik Dan Item Response Theory Pada Peserta didik Sekolah Dasar. Jurnal Penelitian Dan Evaluasi Pendidikan, 19(1), 13–24. https://doi.org/10.21831/pep.v19i1.4551

Aşiret, S., & Sünbül, S. Ö. (2016). Investigating test equating methods in small samples through various factors. Kuram ve Uygulamada Egitim Bilimleri, 16(2), 647–668. https://doi.org/10.12738/estp.2016.2.2762

Babcock, B., Albano, A., & Raymond, M. (2012). Nominal Weights Mean Equating: A Method for Very Small Samples. Educational and Psychological Measurement, 72(4), 608–628. https://doi.org/10.1177/0013164411428609

Caglak, S. (2016). Comparison of Several Small Sample Equating Methods under the NEAT Design. Turkish Journal of Education, 5(3), 96–118. https://doi.org/10.19128/turje.16916

Chai, T., & Draxler, R. R. (2014). Root mean square error ( RMSE ) or mean absolute error ( MAE )? – Arguments against avoiding RMSE in the literature. Geosci. Model Dev, 7, 1247–1250. https://doi.org/10.5194/gmd-7-1247-2014

Dwyer, A. C. (2016). Maintaining Equivalent Cut Scores for Small Sample Test Forms. Journal of Educational Measurement, 53(1), 3–22. https://doi.org/10.1111/jedm.12098

Ebel, R. L., & Frisbie, D. A. (1991). Essentials of Educational Measurement. Educational Researcher (Fifth Edit). New Delhi: Rajkamal Electirc Press. https://doi.org/10.2307/1175572

Hippel, P. Von. (2010). Skewness. International Encyclopedia of Statistical Science, 100, 1–4. https://doi.org/http://dx.doi.org/10.4135/9781412952644

Hsiao, Y. Y., Shih, C. L., Yu, W. H., Hsieh, C. H., & Hsieh, C. L. (2015). Examining unidimensionality and improving reliability for the eight subscales of the SF-36 in opioid-dependent patients using Rasch analysis. Quality of Life Research, 24(2), 279–285. https://doi.org/10.1007/s11136-014-0771-z

Joo, S.-H., Lee, P., & Stark, S. (2016). Evaluating Anchor-Item Designs for Concurrent Calibration With the GGUM. Applied Measurement in Education, 1–14. https://doi.org/10.1177/0146621616673997

Kartono. (2008). Equating the Combined Dichotomous and Polytomous Item Test Model in an Achievement Test. Jurnal Penelitian Dan Evaluasi Pendidikan, 12(2), 302–320.

Kim, S., Davier, A. A. von, & Haberman, S. (2008). Small-Sample Equating Using a Synthetic Linking Function. Journal of Educational Measurement, 45(4), 325–342. https://doi.org/10.1111/j.1745-3984.2008.00068.x

Kim, S., & Livingston, S. A. (2010). Comparisons among small sample equating methods in a common-item design. Journal of Educational Measurement, 47(3), 286–298. https://doi.org/10.1111/j.1745-3984.2010.00114.x

LaFlair, G. T., Isbell, D., May, L. D. N., Gutierrez Arvizu, M. N., & Jamieson, J. (2015). Equating in small-scale language testing programs. Language Testing, 34(1), 1–18. https://doi.org/10.1177/0265532215620825

Linacre JM, W. B. (2006). A user’s guide to Bigsteps, Winsteps. MESA Press.

Livingston, S. A., & Kim, S. (2008). Small-Sample Equating by the Circle-Arc Method. ETS Research Report Series. https://doi.org/10.1002/j.2333-8504.2008.tb02125.x

Livingston, S. A., & Kim, S. (2009). The circle-arc method for equating in small samples. Journal of Educational Measurement, 46(3), 330–343. https://doi.org/10.1111/j.1745-3984.2009.00084.x

Livingston, S. A., & Kim, S. (2010). Random-groups equating with samples of 50 to 400 test takers. Journal of Educational Measurement, 47(2), 175–185. https://doi.org/10.1111/j.1745-3984.2010.00107.x

Neumann, I., Neumann, K., & Nehm, R. (2011). Evaluating instrument quality in science education: Rasch-based analyses of a nature of science test. International Journal of Science Education, 33(10), 1373–1405. https://doi.org/10.1080/09500693.2010.511297

Ozdemir, B. (2017). Equating TIMSS Mathematics Subtests with Nonlinear Equating Methods Using NEAT Design: Circle-Arc Equating Approaches. International Journal of Progressive Eduaction, 13(2), 116–132.

Pos, L. (2018). UN 2014, Jumlah Paket Soal Ditambah. Retrieved from Acceshttps://www.linggapos.com/14812_un-2014-jumlah-paket-soal-ditambah.html

Razali, N. M., & Wah, Y. B. (2011). Power comparisons of Shapiro-Wilk, Kolmogorov-Smirnov, Lilliefors, and Anderson-Darling tests. Journal of Statistical Modeling and Analytics, 2(1), 21–33. https://doi.org/doi:10.1515/bile-2015-0008

Sainani, K. L. (2012). Dealing With Non-normal Data. PM and R, 4(12), 1001–1005. https://doi.org/10.1016/j.pmrj.2012.10.013

Shin, M. (2015). An Investigation of Subtest Score Equating Methods under Classical Test Theory and Item Response Theory Frameworks. University of Massachusetts.

Sinnema, C., Ludlow, L., & Obinson, V. (2016). Journal of Educational Administration and History. Journal of Educational Administration and History, 35(2). https://doi.org/10.1080/713676155

Skaggs, G. (2005). Accuracy of Random Groups Equating with VerySmall Samples. Journal of Educational Measurement, 42(4), 309–330. https://doi.org/10.1111/j.1745-3984.2005.00018.x

Smith, A. B., Rush, R., Fallowfield, L. J., Velikova, G., & Sharpe, M. (2008). Rasch fit statistics and sample size considerations for polytomous data. BMC Medical Research Methodology, 33(8), 1–11. https://doi.org/10.1186/1471-2288-8-33

Tabor, J. (2010). Investigating the Investigative Task: Testing for Skewness An Investigation of Different Test Statistics and their Power to Detect Skewness. Journal of Statistics Education, 18(2), 1–13. https://doi.org/10.1002/jmri.20253

Taylor, J. R. (1997). An Introduction to Error Analysis: The Studi of Uncertainties in Physical Measurements. Sauslito: Unversity Science Books.

Treptow, R. S. (1998). Precision and Accuracy in Measurements A Tale of Four Graduated Cylinders. Journal of Chemical Education, 75(8), 1–4. https://doi.org/10.1021/ed075p992

Uysal, İ., & Kilmen, S. (2016). Comparison of Item Response Theory Test Equating Methods for Mixed Format Tests. International Online Journal of Educational Sciences, 8(2), 1–11. https://doi.org/10.15345/iojes.2016.02.001

Zhu, W. (1998). Test equating: What, why, how? Research Quarterly for Exercise and Sport, 69(1), 11–23. https://doi.org/10.1080/02701367.1998.10607662




DOI: https://doi.org/10.26858/est.v5i2.9258

Article Metrics

Abstract view : 65 times | PDF view : 13 times

Refbacks

  • There are currently no refbacks.


Copyright (c) 2019 Deni Iriyadi

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Editorial Office

Journal of Educational Science and Technology
Graduate Program Universitas Negeri Makassar

   

address icon red

 Jalan Bonto Langkasa Gunungsari Baru Makassar, 90222 Kampus PPs UNM Makassar Gedung AD Ruang 406 Lt 4, Indonesia  
  [email protected] | [email protected] 
  https://ojs.unm.ac.id/JEST/index 
   085299898201 (WA) 
 

EST Index by: