Dergiler / International Journal of Assessment Tools in Education / 2023 / Cilt: 10 Sayı: 3

Application of the professional maturity scale as a computerized adaptive testing

Sayfa
580–593
Yayın Tarihi
2023-09-18
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

As a result, it can be said that the vocational maturity scale can be applied as a computerized adaptive test and can be used in career guidance processes.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:This study has two main purposes.
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Temel Bulgular & Veri:Firstly, to compare the different item selection methods and stopping rules used in Computerized Adaptive Testing (CAT) applications with simulative data generated based on the item parameters of the Vocational Maturity Scale.
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Sonuç & Katkı:As a result, it can be said that the vocational maturity scale can be applied as a computerized adaptive test and can be used in career guidance processes.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Computerized Adaptive Test (CAT) · CAT application · Item selection method

Özet

This study has two main purposes. Firstly, to compare the different item selection methods and stopping rules used in Computerized Adaptive Testing (CAT) applications with simulative data generated based on the item parameters of the Vocational Maturity Scale. Secondly, to test the validity of CAT application scores. For the first purpose, simulative data produced based on Vocational Maturity Scale item parameters were analyzed under different item selection methods (Maximum Fisher Information [MFI],Maximum Likelihood Weighted Information [MLWI] Maximum Posterior Weighted Information [MPWI] Maximum Expected Information [MEI] Minimum Expected Posterior Variance [MEPV] Maximum Expected Posterior Weighted Information [MEPWI]) and stopping rules (Standard Error [SE]<0.30, SE<0.50, SE <0.70, Number of Item [NI]=10, NI=20) by calculating the average number of items, standard error averages, correlation coefficients, bias, and RMSE statistics. For all the conditions of the item selection methods, standard error averages, correlation coefficients, bias, and RMSE statistics showed similar results. When the average number of items is considered, MFI and SE<0.30 were found as most appropriate methods to be used in CAT application. For the second purpose of the study, the paper-pencil form of the Vocational Maturity scale and CAT version were administered to 33 students. A moderate, positive, and statistically significant relationship was found between the CAT application scores and the paper-pencil form scores on the vocational maturity scale. As a result, it can be said that the vocational maturity scale can be applied as a computerized adaptive test and can be used in career guidance processes.

Abstract

This study has two main purposes. Firstly, to compare the different item selection methods and stopping rules used in Computerized Adaptive Testing (CAT) applications with simulative data generated based on the item parameters of the Vocational Maturity Scale. Secondly, to test the validity of CAT application scores. For the first purpose, simulative data produced based on Vocational Maturity Scale item parameters were analyzed under different item selection methods (Maximum Fisher Information [MFI],Maximum Likelihood Weighted Information [MLWI] Maximum Posterior Weighted Information [MPWI] Maximum Expected Information [MEI] Minimum Expected Posterior Variance [MEPV] Maximum Expected Posterior Weighted Information [MEPWI]) and stopping rules (Standard Error [SE]<0.30, SE<0.50, SE <0.70, Number of Item [NI]=10, NI=20) by calculating the average number of items, standard error averages, correlation coefficients, bias, and RMSE statistics. For all the conditions of the item selection methods, standard error averages, correlation coefficients, bias, and RMSE statistics showed similar results. When the average number of items is considered, MFI and SE<0.30 were found as most appropriate methods to be used in CAT application. For the second purpose of the study, the paper-pencil form of the Vocational Maturity scale and CAT version were administered to 33 students. A moderate, positive, and statistically significant relationship was found between the CAT application scores and the paper-pencil form scores on the vocational maturity scale. As a result, it can be said that the vocational maturity scale can be applied as a computerized adaptive test and can be used in career guidance processes.

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Bu Makaleye Atıf Yap

DEMİR, S., AKTAN, D. Ç., GÜLER, N. (2023). Application of the professional maturity scale as a computerized adaptive testing. International Journal of Assessment Tools in Education, Cilt: 10 Sayı: 3, 580–593. https://ajindex.com/articles/962100

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Kaynakça (6)

  1. AERA, APA, & NCME (2014). Standards for educational and psychological testing. American Educational Research Association. Akdaş, G., & Ekinci, M. (2016). Sağlık meslek lisesi öğrencilerinin mesleki olgunluk düzeylerinin ve algıladıkları aile desteğinin incelenmesi [Analysis of vocational school of health students’ professional maturity and family support perception levels]. Uluslararası Hakemli Psikiyatri ve Psikoloji Araştırmaları Dergisi 7, 83 100. https://doi.org/10.17360/UHPPD.2016723147
  2. Akıntuğ, Y., & Birol, C. (2011). Lise öğrencilerinin mesleki olgunluk ve karar verme stratejilerine yönelik karşılaştırmalı analiz [Comparative analysis of vocational maturity and decision making strategies of high school students]. Hacettepe Üniversitesi Eğitim Fakültesi Dergisi, 41, 1 12. http://efdergi.hacettepe.edu.tr/yonetim/icerik/makaleler/675 published.pdf Aybek, E.C., & Demirtaşlı, R.N. (2017). Computerized adaptive test (CAT) applications and item response theory models for polytomous items. International Journal of Research in Education and Science, 3(2), 475-487. https://doi.org/10.21890/ijres.327907
  3. Aybek, E.C., & Çıkrıkçı, R.N. (2018). Kendini Değerlendirme Envanteri’nin bilgisayar ortamında bireye uyarlanmış test olarak uygulanabilirliği [Applicability of the Self-Assessment Inventory as a computerized adaptive test]. Turkish Psychological Counseling and Guidance Journal, 8(50), 117 141. https://dergipark.org.tr/tr/pub/tpdrd/issue/40299/481364 Bardhoshi G., & Erford B.T. (2017). Processes and procedures for estimating score reliability and precision. Measurement and Evaluation in Counseling and Development, 50(4), 256-263. https://doi.org/10.1080/07481756.2017.1388680
  4. Cattell R.B. (1986). The psychometric properties of tests: Consistency, validity, and efficiency. In Cattell R.B., Johnson R.C. (Eds.), Functional psychological testing (pp. 54-78). Brunner/Mazel. Cattell R.B., Eber H.W., & Tatsuoka M.M. (1970). Handbook for the Sixteen Personality Factor Questionnaire (16PF). Institute for Personality and Ability Testing. Choi, S.W. (2009). Firestar: Computerized adaptive testing simulation program for polytomous item response theory models. Applied Psychological Measurement, 33(1), 644-645. https://doi.org/10.1177/0146621608329892
  5. Choi, S.W., & Swartz, R.J. (2009). Comparison of CAT item selection criteria for polytomous items. Applied Psychological Measurement, 33(1), 419 440. https://doi.org/10.1177/0146621608327801
  6. Choi, Y., & McClenen, C. (2020). Deve