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JMETRIK: Classical Test Theory and Item Response Theory Data Analysis Software

Yıl 2019, Cilt: 10 Sayı: 2, 165 - 178, 28.06.2019
https://doi.org/10.21031/epod.483396

Öz

The aim of this study is to introduce the
jMetric program which is one of the open source programs that can be used in
the context of Item Response Theory and Classical Test Theory. In this context,
the interface of the program, importing data to the program, a sample analysis,
installing the jmetrik and support for the program are discussed. In sample
analysis, the answers given by a total of 500 students from state and private
schools, to a 10-item math test were analyzed to see whether they shows
differentiating item functioning according to the type of school they attend.
As a result of the analysis, it was found that two items were showing
medium-level Differential Item Functioning (DIF). As a result of the study, it
was found that the jMetric program, which is capable of performing Item
Response Theory (IRT) analysis for two-category and multi-category items, is
open to innovations, especially because it is open-source, and that researchers
can easily add the suggested codes to the program and thus the program can be
improved. In addition, an advantage of the program is producing visual results
related to the analysis through the item characteristic curves.

Kaynakça

  • Aksu, G., Reyhanlıoğlu, Ç., Eser M. T. (2017). Examining the two categorical datas by jMetrik, Bilog-MG and IRTPRO with application of mathematics exam. European Scientific Journal, 13(33).
  • Crocker, L., & Algina, J. (1986). Introduction to classical &modern test theory. Orlando, FL: Holt, Rinehart & Winston.
  • Embretson, S. E., & Reise, S. P. (2000). Item response theory for psychologists. Lawrence Erlbaum Associate, Inc.
  • Haebara, T. (1980). Equating logistic ability scales by a weighted least squares method. Japanese Psychological Research, 22(3), 144–149.
  • Hambleton, R. K., & Swaminathan, H. (1985). Item response theory principles and applications. Boston-USA: Kluwer-Nijhoff Publishing.
  • Kim, S. & Kolen, M. J. (2007). Effects of scale linking on different definitions of criterion functions for the IRT characteristic curve methods. Journal of Educational and Behavioral Statistics, 32(4), 371–397.
  • Lord, F.M. & Novick, M.R. (1968) Statistical Theories of Mental Test Scores. Addison-Wesley, Menlo Park.
  • Loyd, B. H. & Hoover, H. D. (1980). Vertical equating using the Rasch model. Journal of Educational Measurement, 17(3), 179–193.
  • Marco, G. L. (1977). Item characteristic curve solutions to three intractable testing problems. Journal of Educational Measurement, 14(2), 139–160.
  • McDonald, R. P. (1999). Test theory: A unified treatment. Mahwah, NJ: Lawrence Erlbaum Associates.
  • Meyer, J. P. (2010). Understanding measurement: Reliability. New York: Oxford University Press.
  • Meyer, J. P. & Hailey, E. (2012). A study of Rasch partial credit, and rating scale model parameter recovery in WINSTEPS and jMetrik. Journal of Applied Measurement, 13(3), 248–258.
  • Meyer, J. P. (2014). Applied Measurement with jMetrik. New York: Routledge.
  • Meyer, J. P. (2018). jMetrik. In Van Der Linden, W. (Ed.). Handbook of Item Response Theory, Volume 3. Boca Raton, FL: Taylor & Francis.
  • Stocking, M. L. & Lord, F. M. (1983). Developing a common metric in item response theory. Applied Psychological Measurement, 7(2), 201–210.
  • Wright, B. D. & Masters, G. N. (1982). Rating scale analysis. Chicago, IL: MESA Press.
Yıl 2019, Cilt: 10 Sayı: 2, 165 - 178, 28.06.2019
https://doi.org/10.21031/epod.483396

Öz

Bu çalışmanın
amacı özellikle son yıllarda Madde Tepki Kuramı ve Klasik test kuramı
kapsamında kullanılabilecek açık kaynak kodlu programlardan biri olan jMetrik
programının tanıtılmasıdır. Bu amaç kapsamında programın ara yüzü, programa
verinin nasıl tanıtılacağı, örnek bir analiz ve programa ilişkin desteğin nasıl
sağlanacağını konuları üzerinde durulmuştur. Örnek analiz kapsamında devler ve
özel okulda öğrenim gören toplam 500 öğrencinin 10 maddelik matematik testine
verdikleri yanıtların öğrenim gördükleri okul türüne göre değişen madde
fonksiyonu gösterip göstermediği belirlenmeye çalışılmıştır. Analiz sonucunda
iki madde orta düzeyde DMF gösteren madde olduğu belirlenmiştir. Çalışma
sonucunda hem iki kategorili hem de çok kategorili maddelere ilişkin MTK
analizleri yapabilen jMetrik programının özellikle açık kaynak kodlu olması
sebebiyle yeniliklere açık olduğu, araştırmacıların önerdikleri kodları
programa kolaylıkla ekleyebilecekleri ve bu sayede programın
geliştirilebileceği belirlenmiştir. Bunun yanında madde karakteristik eğrileri
yardımıyla madde bazında yapılacak analizlere ilişkin görsel sonuçlar üretmesi
programın bir avantajı olarak belirlenmiştir.

Kaynakça

  • Aksu, G., Reyhanlıoğlu, Ç., Eser M. T. (2017). Examining the two categorical datas by jMetrik, Bilog-MG and IRTPRO with application of mathematics exam. European Scientific Journal, 13(33).
  • Crocker, L., & Algina, J. (1986). Introduction to classical &modern test theory. Orlando, FL: Holt, Rinehart & Winston.
  • Embretson, S. E., & Reise, S. P. (2000). Item response theory for psychologists. Lawrence Erlbaum Associate, Inc.
  • Haebara, T. (1980). Equating logistic ability scales by a weighted least squares method. Japanese Psychological Research, 22(3), 144–149.
  • Hambleton, R. K., & Swaminathan, H. (1985). Item response theory principles and applications. Boston-USA: Kluwer-Nijhoff Publishing.
  • Kim, S. & Kolen, M. J. (2007). Effects of scale linking on different definitions of criterion functions for the IRT characteristic curve methods. Journal of Educational and Behavioral Statistics, 32(4), 371–397.
  • Lord, F.M. & Novick, M.R. (1968) Statistical Theories of Mental Test Scores. Addison-Wesley, Menlo Park.
  • Loyd, B. H. & Hoover, H. D. (1980). Vertical equating using the Rasch model. Journal of Educational Measurement, 17(3), 179–193.
  • Marco, G. L. (1977). Item characteristic curve solutions to three intractable testing problems. Journal of Educational Measurement, 14(2), 139–160.
  • McDonald, R. P. (1999). Test theory: A unified treatment. Mahwah, NJ: Lawrence Erlbaum Associates.
  • Meyer, J. P. (2010). Understanding measurement: Reliability. New York: Oxford University Press.
  • Meyer, J. P. & Hailey, E. (2012). A study of Rasch partial credit, and rating scale model parameter recovery in WINSTEPS and jMetrik. Journal of Applied Measurement, 13(3), 248–258.
  • Meyer, J. P. (2014). Applied Measurement with jMetrik. New York: Routledge.
  • Meyer, J. P. (2018). jMetrik. In Van Der Linden, W. (Ed.). Handbook of Item Response Theory, Volume 3. Boca Raton, FL: Taylor & Francis.
  • Stocking, M. L. & Lord, F. M. (1983). Developing a common metric in item response theory. Applied Psychological Measurement, 7(2), 201–210.
  • Wright, B. D. & Masters, G. N. (1982). Rating scale analysis. Chicago, IL: MESA Press.
Toplam 16 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Makaleler
Yazarlar

Gökhan Aksu 0000-0003-2563-6112

Cem Oktay Güzeller 0000-0002-2700-3565

Mehmet Taha Eser 0000-0001-7031-1953

Yayımlanma Tarihi 28 Haziran 2019
Kabul Tarihi 12 Mart 2019
Yayımlandığı Sayı Yıl 2019 Cilt: 10 Sayı: 2

Kaynak Göster

APA Aksu, G., Güzeller, C. O., & Eser, M. T. (2019). JMETRIK: Classical Test Theory and Item Response Theory Data Analysis Software. Journal of Measurement and Evaluation in Education and Psychology, 10(2), 165-178. https://doi.org/10.21031/epod.483396