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Bireyselleştirilmiş Bilgisayarlı Test Uygulamalarında Farklı Sonlandırma Kurallarının Ölçme Kesinliği ve Test Uzunluğu Açısından Karşılaştırılması

Year 2015, Volume: 28 Issue: 1, 31 - 52, 29.12.2015
https://doi.org/10.19171/uuefd.87973

Abstract

Bireyselleştirilmiş testlerde, geleneksel testlerden farklı olarak test
algoritması söz konusudur. Test algoritması; teste başlama, devam etme ve testi
sonlandırma olmak üzere üç bölümden oluşmaktadır. Bu çalışmanın amacı,
bireyselleştirilmiş bilgisayarlı test (BBT) uygulamalarında farklı sonlandırma
kurallarının kullanılmasının ölçme kesinliğine ve test uzunluğuna etkisini incelemek
ve birbirleri ile karşılaştırmaktır. Araştırma simülasyon çalışması olarak
yürütülmüştür. Araştırma kapsamında sabit uzunluk, standart hata, standart hata-en
az madde, theta yakınsama ve theta yakınsama-en az madde olmak üzere beş farklı
sonlandırma kuralı kullanılmıştır. Her bir sonlandırma kuralında farklı koşullar söz
konusu olup toplam 12 koşul birbiriyle karşılaştırılmıştır. Ayrıca sonlandırma
kurallarının karşılaştırılmasında BBT’de test algoritmasında önemli yere sahip olan
farklı madde havuzu büyüklükleri (250 ve 500 madde) ve yetenek kestirim
yöntemleri (Maksimum Olabilirlik Kestirimi ve Beklenen Sonsal Dağılım)
seçilmiştir. Her bir BBT uygulamasında ölçme kesinliği için RMSE, yanlılık ve
uyum değerleri hesaplanmış ve test uzunlukları elde edilip, birbirleriyle
karşılaştırılmıştır. Araştırmanın sonucunda, genel olarak 20 madde sabit uzunluk,
0,220 standart hata ve 0,02 theta yakınsama sonlandırma koşullarında RMSE,
yanlılık değerlerinin düşük elde edildiği ancak uyum katsayılarının önemli oranda
etkilenmediği belirlenmiştir. Ayrıca en az madde koşulunun eklenmesi ile bazı
sonlandırma koşulları ölçme kesinliği açısından daha iyi sonuçlar vermiştir.
Ortalama test uzunluk değerlerinin RMSE değerleri ile ters yönde değiştiği
bulunmuştur. Aynı sonlandırma koşullarında madde havuzu büyüklüğünün artması
ile ölçme kesinliği için elde edilen RMSE ve yanlılık değerlerinin genel olarak daha
düşük elde edilmiştir. Yetenek kestirim yöntemi olarak Beklenen Sonsal Dağılım
yönteminin kullanılmasının RMSE ve yanlılık değerlerinde düşmeye neden olduğu
belirlenmiştir.

References

  • Babcock, B. and Weiss, D.J., 2012. Termination criteria in Computerized Adaptive Tests: do variable-length CAT’s provide efficient and effective measurement? International Association for Computerized Adaptive Testing, 1, 1-18.
  • Blais, J. and Raiche, G., 2002. Features of the sampling distribution of the ability estimate in Computerized Adaptive Testing according to two stopping rules, International Objective Measurement Workshop, New Orleans, April 2002.
  • Choi, S. W., Grady, M.W. and Dodd, B.G., 2011. A new stopping rule for computerized adaptive testing. Educational and Psychological Measurement, 71, 37-53.
  • Çıkrıkçı, Demirtaşlı, N., 1999. Psikometride yeni ufuklar: bilgisayar ortamında bireye uyarlanmış test. Türk Psikoloji Bülteni. 5(13), 31-36.
  • Dodd, B.G., Koch, W.R. and de Ayala, R.J., 1993. Computerized Adaptive Testing using the partial credit model effects of item pool characteristics and different stopping rules. Educational and Psychological Measurement, 53, 61-77.
  • Embretson, E. and Reise, S. P., 2000. Item response theory for psychologist principles and application. London: Lawrence Erlbaum Assc.
  • Eggen,T., 2004. Contributions to the theory and practice of Computerized Adaptive Testing. Druk: Print Partners Ipskamp B.V., Enschede.
  • Evans, J. J., 2010. Comparability of examinee proficiency scores on Computer Adaptive Tests using real and simulated data. Doctoral Dissertation. The State University of New Jersey.
  • Flaugher, R., 2000. Item pools. In H. Wainer (Eds.), Computerized Adaptive Testing, 37-59. London: Lawrence Erlbaum Assc.
  • Hambleton, R. K. and Swaminathan, H., 1985. Item response theory. principles and application. Boston: Kluwer-Nijhoff.
  • Hambleton, R. K., Swaminathan, H. and Rogers,H. J., 1991. Fundamentals of item response theory. California: Sage Publications.
  • Han, K. C., 2011. User's Manual: SimulCAT. Graduate Management Admission Council.
  • Ivei, J. L., 2007. Test taking strategies in Computer Adaptive Testing That will ımprove your score: fact or fiction? Doctoral Dissertation. University of Michigan.
  • İseri, A. I., 2002. Assessment of students' mathematics achievement through Computer Adaptive Testing procedures. Middle East Technical University.
  • Kalender, İ., 2004. Bilgisayar ortamında Bireyselleştirilmiş Testlerin eğitimde kullanımı. XIII. Ulusal Eğitim Bilimleri Kurultayı. İnönü Üniversitesi, Eğitim Fakültesi, Malatya. 6-9 Temmuz 2004.
  • Kalender, İ., 2011. Effects of different Computerized Adaptive Testing strategied on recovery of abilitiy. Doctoral Disertation. Middle East Technical University.
  • Kaptan, F., 1993. Yetenek kestiriminde Adaptive (Bireyselleştirilmiş) Test uygulaması ile geleneksel kâğıt-kalem testi uygulamasının karşılaştırılması. Doktora Tezi. Hacettepe Üniversitesi.
  • Karasar, N., 2004. Bilimsel araştırma yöntemi: kavramlar, ilkeler, teknikler (13. Baskı). Ankara: Nobel Yayın Dağıtım.
  • Köklü, N., 1990. Klasik test teorisine göre geliştirilen tailored test ile grup testi arasında bir karşılaştırma. Doktora Tezi. Hacettepe Üniversitesi.
  • Linden, W. J and Glas, G. A. W., 2002. Computerized Adaptive Testing: theory and practice. USA: Kluwer Academic Publishers.
  • Linecra, J. M., 2000. Computer-Adaptive Testing: a methodology whose time has come, [Çevrim-içi: http://www.rasch.org/memo69.htm], erişim tarihi: 02 Mayıs 2012.
  • McBride, J. R. and Martin, J. T., 1983. Reliability and validity of adaptive ability tests in a militarysetting. In D. J. Weiss (Eds.), New horizons in testing: Latent trait theory and computerized adaptive testing, 223–226). New York: Academic Press.
  • McBride, J. R., Wetzel,C.D. and Hetter, R. D., 2001. Preliminary psychometric research for CAT-ASVAB: selecting an adaptive testing strategy. In W. Sands, B. K. Waters, and J.R.McBride (Eds.). Computerized Adaptive Testing: from inquiry to operation, 83–95. Washington, DC: American Psychological Association.
  • Mead, A. D. and Drasgow, F., 1993. Equivalence of computerized and paper-and- pencil cognitive ability tests: a meta-analysis. Psychological Bulletin, 114, 449-458.
  • Meijer, R. R. & Nerring, M. L., 2001. New development in the area of Computerized Testing. Psychologie Francaise, 46(3), 221-230.
  • Mills, C. N. and Stocking, M.L., 1996. Practical issues in large-scale Computerized Adaptive Testing. Applied Mesurement in Education, 9(4), 287-304.
  • Pearson Asssessment., 2012. [Çevrim-içi: www.pearsonassessment.com] Erişim tarihi: 02.05.12.
  • Riley, B. B., Conrad, K. J., Bezruczko, N. and Dennis, M., 2007. Relative precision, efficiency and construct validity of different starting and stopping rules for a Computerized Adaptive Test: the GAIN substance problem scale. Journal of Applied Measurement, 8(1).
  • Rudner, L. M., 1998. Interactive Computer Adaptive Testing, [Çevrim-içi: http://EdRes.org/scripts/cat], Erişim Tarihi: 02.05.12.
  • Samejima, F., 1977. A method of estimating item characteristic functions using the maximum likelihood estimate of ability. Psychometrika, 42(2), 163-191.
  • Segall, D. O., 2004. Computerized Adaptive Testing. In Kempf-Leanard (Eds.). The Encyclopedia of Social Measurement, 429-438. San Diego, CA: Academic Press.
  • Simms, L. J. and Clark, L. A., 2005. Validation of a computerized adaptive version of the schedule for non-adaptive and adaptive personality (SNAP). Psychological Assessment, 17, 28-43.
  • Stocking, M. L., 1987. Two Simulated feasibility studies in Computerized Adaptive Testing. Applied Psychology: An International Review, 36, 263-267.
  • Thissen, D. and Mislevy, R. J., 2000. Testing algorithms. In H. Wainer (Eds.). Computerized Adaptive Testing, 101-135. London: Lawrence Erlbaum Assc.
  • Wainer, H., 2000. Computerized Adaptive Testing. London: Lawrence Erlbaum Assc.
  • Wainer, H. and Mislevy, R. J., 2000. Item response theory, item calibration and proficiency estimation. In H. Wainer (Eds.). Computerized Adaptive Testing. 65-102. London: Lawrence Erlbaum Assc.
  • Wang, T., Hanson, B. A. and Lau, C., 1999. Reducing bias in CAT ability estimation: a comparison of approaches. Applied Psychological Measurement, 23, 263-278.
  • Wang, T. and Vispoel, W. P., 1998. Properties of ability estimation methods Computerized Adaptive Testing. Journal of Educational Measurement, 35 (2), 109-135.
  • Wang, S. and Wang, T., 2001. Precision of warm’s weighted likelihood estimates for a polytomous model in Computerized Adaptive Testing. Applied Psychological Measurement, 25(4), 317–331.
  • Weiss, D. J., 1982. Improving measurement quality and efficiency with Adaptive Testing. Applied Psychological Mesurement, 6,473-492.
  • Weiss, D. J., 1983. New horizons in testing. New York: Academic Press.
  • Weiss, D. J., 2004. Computerized Adaptive Testing for effective and efficient measurement in counseling and education. Measurement and Evaluation in Counseling and Development, 37(2), 70-84.
  • Weiss, D. J. and Kingsbury, G. G. 1984. Application of Computerized Testing to educational problems. Journal of Educational Measurement, 21(4), 361- 375.
  • Yi, Q., Wang, T. and Ban, J. C., 2001. Effects of scale transformation and test termination rule on the precision of ability estimation in Computerized Adaptive Testing. Journal of Educational Measurement, 38, 267-292.
  • Yoo, H., 2011. Evaluating several Multidimensional Adaptive Testing procedures for diagnostic assessment. Doctoral Dissertation. Unıversity of Massachusetts. Başvuru: 08.07.2014
  • Yayına Kabul: 11.02.2015
Year 2015, Volume: 28 Issue: 1, 31 - 52, 29.12.2015
https://doi.org/10.19171/uuefd.87973

Abstract

References

  • Babcock, B. and Weiss, D.J., 2012. Termination criteria in Computerized Adaptive Tests: do variable-length CAT’s provide efficient and effective measurement? International Association for Computerized Adaptive Testing, 1, 1-18.
  • Blais, J. and Raiche, G., 2002. Features of the sampling distribution of the ability estimate in Computerized Adaptive Testing according to two stopping rules, International Objective Measurement Workshop, New Orleans, April 2002.
  • Choi, S. W., Grady, M.W. and Dodd, B.G., 2011. A new stopping rule for computerized adaptive testing. Educational and Psychological Measurement, 71, 37-53.
  • Çıkrıkçı, Demirtaşlı, N., 1999. Psikometride yeni ufuklar: bilgisayar ortamında bireye uyarlanmış test. Türk Psikoloji Bülteni. 5(13), 31-36.
  • Dodd, B.G., Koch, W.R. and de Ayala, R.J., 1993. Computerized Adaptive Testing using the partial credit model effects of item pool characteristics and different stopping rules. Educational and Psychological Measurement, 53, 61-77.
  • Embretson, E. and Reise, S. P., 2000. Item response theory for psychologist principles and application. London: Lawrence Erlbaum Assc.
  • Eggen,T., 2004. Contributions to the theory and practice of Computerized Adaptive Testing. Druk: Print Partners Ipskamp B.V., Enschede.
  • Evans, J. J., 2010. Comparability of examinee proficiency scores on Computer Adaptive Tests using real and simulated data. Doctoral Dissertation. The State University of New Jersey.
  • Flaugher, R., 2000. Item pools. In H. Wainer (Eds.), Computerized Adaptive Testing, 37-59. London: Lawrence Erlbaum Assc.
  • Hambleton, R. K. and Swaminathan, H., 1985. Item response theory. principles and application. Boston: Kluwer-Nijhoff.
  • Hambleton, R. K., Swaminathan, H. and Rogers,H. J., 1991. Fundamentals of item response theory. California: Sage Publications.
  • Han, K. C., 2011. User's Manual: SimulCAT. Graduate Management Admission Council.
  • Ivei, J. L., 2007. Test taking strategies in Computer Adaptive Testing That will ımprove your score: fact or fiction? Doctoral Dissertation. University of Michigan.
  • İseri, A. I., 2002. Assessment of students' mathematics achievement through Computer Adaptive Testing procedures. Middle East Technical University.
  • Kalender, İ., 2004. Bilgisayar ortamında Bireyselleştirilmiş Testlerin eğitimde kullanımı. XIII. Ulusal Eğitim Bilimleri Kurultayı. İnönü Üniversitesi, Eğitim Fakültesi, Malatya. 6-9 Temmuz 2004.
  • Kalender, İ., 2011. Effects of different Computerized Adaptive Testing strategied on recovery of abilitiy. Doctoral Disertation. Middle East Technical University.
  • Kaptan, F., 1993. Yetenek kestiriminde Adaptive (Bireyselleştirilmiş) Test uygulaması ile geleneksel kâğıt-kalem testi uygulamasının karşılaştırılması. Doktora Tezi. Hacettepe Üniversitesi.
  • Karasar, N., 2004. Bilimsel araştırma yöntemi: kavramlar, ilkeler, teknikler (13. Baskı). Ankara: Nobel Yayın Dağıtım.
  • Köklü, N., 1990. Klasik test teorisine göre geliştirilen tailored test ile grup testi arasında bir karşılaştırma. Doktora Tezi. Hacettepe Üniversitesi.
  • Linden, W. J and Glas, G. A. W., 2002. Computerized Adaptive Testing: theory and practice. USA: Kluwer Academic Publishers.
  • Linecra, J. M., 2000. Computer-Adaptive Testing: a methodology whose time has come, [Çevrim-içi: http://www.rasch.org/memo69.htm], erişim tarihi: 02 Mayıs 2012.
  • McBride, J. R. and Martin, J. T., 1983. Reliability and validity of adaptive ability tests in a militarysetting. In D. J. Weiss (Eds.), New horizons in testing: Latent trait theory and computerized adaptive testing, 223–226). New York: Academic Press.
  • McBride, J. R., Wetzel,C.D. and Hetter, R. D., 2001. Preliminary psychometric research for CAT-ASVAB: selecting an adaptive testing strategy. In W. Sands, B. K. Waters, and J.R.McBride (Eds.). Computerized Adaptive Testing: from inquiry to operation, 83–95. Washington, DC: American Psychological Association.
  • Mead, A. D. and Drasgow, F., 1993. Equivalence of computerized and paper-and- pencil cognitive ability tests: a meta-analysis. Psychological Bulletin, 114, 449-458.
  • Meijer, R. R. & Nerring, M. L., 2001. New development in the area of Computerized Testing. Psychologie Francaise, 46(3), 221-230.
  • Mills, C. N. and Stocking, M.L., 1996. Practical issues in large-scale Computerized Adaptive Testing. Applied Mesurement in Education, 9(4), 287-304.
  • Pearson Asssessment., 2012. [Çevrim-içi: www.pearsonassessment.com] Erişim tarihi: 02.05.12.
  • Riley, B. B., Conrad, K. J., Bezruczko, N. and Dennis, M., 2007. Relative precision, efficiency and construct validity of different starting and stopping rules for a Computerized Adaptive Test: the GAIN substance problem scale. Journal of Applied Measurement, 8(1).
  • Rudner, L. M., 1998. Interactive Computer Adaptive Testing, [Çevrim-içi: http://EdRes.org/scripts/cat], Erişim Tarihi: 02.05.12.
  • Samejima, F., 1977. A method of estimating item characteristic functions using the maximum likelihood estimate of ability. Psychometrika, 42(2), 163-191.
  • Segall, D. O., 2004. Computerized Adaptive Testing. In Kempf-Leanard (Eds.). The Encyclopedia of Social Measurement, 429-438. San Diego, CA: Academic Press.
  • Simms, L. J. and Clark, L. A., 2005. Validation of a computerized adaptive version of the schedule for non-adaptive and adaptive personality (SNAP). Psychological Assessment, 17, 28-43.
  • Stocking, M. L., 1987. Two Simulated feasibility studies in Computerized Adaptive Testing. Applied Psychology: An International Review, 36, 263-267.
  • Thissen, D. and Mislevy, R. J., 2000. Testing algorithms. In H. Wainer (Eds.). Computerized Adaptive Testing, 101-135. London: Lawrence Erlbaum Assc.
  • Wainer, H., 2000. Computerized Adaptive Testing. London: Lawrence Erlbaum Assc.
  • Wainer, H. and Mislevy, R. J., 2000. Item response theory, item calibration and proficiency estimation. In H. Wainer (Eds.). Computerized Adaptive Testing. 65-102. London: Lawrence Erlbaum Assc.
  • Wang, T., Hanson, B. A. and Lau, C., 1999. Reducing bias in CAT ability estimation: a comparison of approaches. Applied Psychological Measurement, 23, 263-278.
  • Wang, T. and Vispoel, W. P., 1998. Properties of ability estimation methods Computerized Adaptive Testing. Journal of Educational Measurement, 35 (2), 109-135.
  • Wang, S. and Wang, T., 2001. Precision of warm’s weighted likelihood estimates for a polytomous model in Computerized Adaptive Testing. Applied Psychological Measurement, 25(4), 317–331.
  • Weiss, D. J., 1982. Improving measurement quality and efficiency with Adaptive Testing. Applied Psychological Mesurement, 6,473-492.
  • Weiss, D. J., 1983. New horizons in testing. New York: Academic Press.
  • Weiss, D. J., 2004. Computerized Adaptive Testing for effective and efficient measurement in counseling and education. Measurement and Evaluation in Counseling and Development, 37(2), 70-84.
  • Weiss, D. J. and Kingsbury, G. G. 1984. Application of Computerized Testing to educational problems. Journal of Educational Measurement, 21(4), 361- 375.
  • Yi, Q., Wang, T. and Ban, J. C., 2001. Effects of scale transformation and test termination rule on the precision of ability estimation in Computerized Adaptive Testing. Journal of Educational Measurement, 38, 267-292.
  • Yoo, H., 2011. Evaluating several Multidimensional Adaptive Testing procedures for diagnostic assessment. Doctoral Dissertation. Unıversity of Massachusetts. Başvuru: 08.07.2014
  • Yayına Kabul: 11.02.2015
There are 46 citations in total.

Details

Primary Language tr;en
Journal Section Articles
Authors

Melek Eroğlu This is me

Melek Gülşah Eroğlu This is me

Hülya Kelecioğlu

Hülya Kelecioğlu

Publication Date December 29, 2015
Submission Date December 29, 2015
Published in Issue Year 2015 Volume: 28 Issue: 1

Cite

APA Eroğlu, M., Eroğlu, M. G., Kelecioğlu, H., Kelecioğlu, H. (2015). Bireyselleştirilmiş Bilgisayarlı Test Uygulamalarında Farklı Sonlandırma Kurallarının Ölçme Kesinliği ve Test Uzunluğu Açısından Karşılaştırılması. Uludağ Üniversitesi Eğitim Fakültesi Dergisi, 28(1), 31-52. https://doi.org/10.19171/uuefd.87973