Applicability and Efficiency of a Polytomous IRT-Based Computerized Adaptive Test for Measuring Psychological Traits

Yıl 2022, Cilt: 13 Sayı: 4, 328 - 344, 25.12.2022

Ahmet Salih Şimşek , Ezel Tavşancıl

https://doi.org/10.21031/epod.1148313

Öz

Currently, research on computerized adaptive testing (CAT) focuses mainly on dichotomous items and cognitive traits (achievement, aptitude, etc.). However, polytomous IRT-based CAT is a promising research area for measuring psychological traits that has attracted much attention. The main purpose of this study is to test the practicality of the polytomous IRT-based CAT and its equivalence with the paper-pencil version. Data were collected from 1449 high school students (45% female) via the paper-pencil version. The data were used for IRT parameter estimates and CAT simulation studies. For the equivalence study, the research group consisted of 81 students (47% female) who participated in both the paper-pencil and live CAT applications. The paper-pencil version of the vocational interest inventory consists of 17 factors and 164 items. When the EAP estimation method and setting SE < .50 as the termination criterion, better performance was obtained compared with other CAT designs. The Item selection did not help to reduce test duration or increase measurement accuracy. As a result, it was found that an area of interest can be assessed with four items. The results of the live CAT application showed that the estimates of CAT were strongly positively correlated with its paper-pencil version. In addition, the live CAT application increased applicability compared to the fixed-length test version by reducing test length by 50% and time by 77%. This study shows that the polytomous IRT-based CAT is applicable and efficient for measuring psychological traits.

Anahtar Kelimeler

polytomous item response model, computerized adaptive test, equivalence, efficiency, measurement precision

Kaynakça

• Abidin, A. Z., Istiyono, E., Fadilah, N., & Dwandaru, W. S. B. (2019). A computerized adaptive test for measuring the physics critical thinking skills. International Journal of Evaluation and Research in Education, 8(3), 376-383. http://dx.doi.org/10.11591/ijere.v8i3.19642
• Achtyes, E. D., Halstead, S., Smart, L., Moore, T., Frank, E., Kupfer, D. J., & Gibbons, R. D. (2015). Validation of computerized adaptive testing in an outpatient nonacademic setting: he VOCATIONS trial. Psychiatric Services, 1–6. http://doi.org/10.1176/appi.ps.201400390
• Alkhadher, O., Clarke, D. D., & Anderson, N. (1998). Equivalence and predictive validity of paper-and-pencil and computerized adaptive formats of the differential aptitude tests. Journal of Occupational and Organizational Psychology, 71(3), 205–217. http://doi.org/10.1111/j.2044-8325.1998.tb00673.x
• Aybek, E. C., & Çıkrıkçı, R. N. (2018). Kendini değerlendirme envanteri’nin bilgisayar ortamında bireye uyarlanmış test olarak uygulanabilirliği. Turkish Psychological Counseling and Guidance Journal, 8(50), 117-141. http://hdl.handle.net/20.500.12575/37233
• Babcock, B., & Weiss, D. J. (2012). Termination criteria in computerized adaptive tests: do variable - length CATs provide efficient and effective measurement? Journal of Computerized Adaptive Testing, 1(1), 1–18. http://doi.org/10.7333/1212-0101001
• Baek, S. G. (1995). Computerized adaptive attitude testing using the partial credit model. Dissertation Abstracts International, 55(7-A), 1922. Retrieved April 10, 2022, from PsychInfo database.
• Baker, F. B. (2001). The basics of item response theory (second edition). Retrieved July 22, 2022, from http://eric.ed.gov/?id=ED458219
• Betz, N. E., & Turner, B. M. (2011). Using item response theory and adaptive testing in online career assessment. Journal of Career Assessment, 19(3), 274–286. http://doi.org/10.1177/1069072710395534
• Betz, N. E., Borgen, F. H., Rottinghaus, P., Paulsen, A., Halper, C. R., & Harmon, L. W. (2003). The expanded skills confidence inventory: measuring basic dimensions of vocational activity. Journal of Vocational Behavior, 62(1), 76–100. http://doi.org/10.1016/S0001-8791(02)00034-9
• Chen, S.-K., Hou, L., Fitzpatrick, S. J., & Dodd, B. G. (1997). The effect of population and method of theta estimation on computerized adaptive testing (CAT) using the rating scale model. Educational and Psychological Measurement, 57(3), 422–439. https://doi.org/10.1177/0013164497057003004
• Choi, S. W., & Swartz, R. J. (2009). Comparison of CAT item selection criteria for polytomous items. Applied Psychological Measurement, 33(6), 419–440. http://doi.org/10.1177/0146621608327801
• Choi, S. W., Reise, S. P., Pilkonis, P. A., Hays, R. D., & Cella, D. (2010). Efficiency of static and computer adaptive short forms compared to full-length measures of depressive symptoms. Quality of Life Research, 19(1), 125–136. http://doi.org/10.1007/s11136-009-9560-5
• Crocker, L., & Algina, J. (1986). Introduction to classical and modern test theory. Harcourt Brace Jovanovich
• Demir, C., & French, B. F. (2021). Applicability and efficiency of a computerized adaptive test for the Washington assessment of the risks and needs of students. Assessment. https://doi.org/10.1177/10731911211047892
• Deng, H., Ansley, T., & Chang, H. H. (2010). Stratified and maximum information item selection procedures in computer adaptive testing. Journal of Educational Measurement, 47(2), 202–226. http://doi.org/10.1111/j.1745-3984.2010.00109.x
• Dodd, B. G., De Ayala, R. J., & Koch, W. R. (1995). Computerized adaptive testing with polytomous items. Applied Psychological Measurement, 19(1), 5–22. http://doi.org/10.1177/014662169501900103 Embretson, S. E., & Reise, S. P. (2000). Item response theory for psychologists. Lawrence Erlbaum Assocaiates.
• Eroğlu, M. G., & 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
• Fliege, H., Becker, J., Walter, O. B., Bjorner, J. B., Klapp, B. F., & Rose, M. (2005). Development of a computer-adaptive test for depression (D-CAT). Quality of Life Research : An International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation, 14(10), 2277–91. http://doi.org/10.1007/s11136-005-6651-9
• Gardner, W., Shear, K., Kelleher, K. J., Pajer, K. A., Mammen, O., Buysse, D., & Frank, E. (2004). Computerized adaptive measurement of depression: A simulation study. BMC Psychiatry, 4(1), 13. http://doi.org/10.1186/1471-244X-4-13
• Gibbons, R. D., Weiss, D. J., Kupfer, D. J., Frank, E., Fagiolini, A., Grochocinski, V. J., … Immekus, J. C. (2008). Using computerized adaptive testing to reduce the burden of mental health assessment. Psychiatric Services, 59(4), 361–8. http://doi.org/10.1176/appi.ps.59.4.361
• Gibbons, R. D., Weiss, D. J., Pilkonis, P. a, Frank, E., Moore, T., Kim, J. B., & Kupfer, D. J. (2012). Development of a computerized adaptive test for depression. Archives of General Psychiatry, 69(11), 1104–12. http://doi.org/10.1001/archgenpsychiatry.2012.14
• Gibbons, R. D., Weiss, D. J., Pilkonis, P. A., Frank, E., Moore, T., Kim, J. B., & Kupfer, D. J. (2014). Development of the CAT-ANX: A computerized adaptive test for anxiety. American Journal of Psychiatry, 171(2), 187–194. http://doi.org/10.1176/appi.ajp.2013.13020178
• Gnambs, T., & Batinic, B. (2011). Polytomous adaptive classification testing: Effects of item pool size, test termination criterion, and number of cutscores. Educational and Psychological Measurement, 71(6), 1006–1022. http://doi.org/10.1177/0013164410393956
• Hambleton, R. K., Swaminathan, H., & Rogers, D. J. (1991). Fundamentals of item response theory. SAGE
• He, W., Diao, Q., & Hauser, C. (2014). A comparison of four item-selection methods for severely constrained CATs. Educational and Psychological Measurement, 74(4), 677–696. http://doi.org/10.1177/0013164413517503
• Hol, M. A., Vorst, H. C., & Mellenbergh, G. J. (2007). Computerized adaptive testing for polytomous motivation items: Administration mode effects and a comparison with short forms. Applied Psychological Measurement, 31(5), 412–429. http://doi.org/10.1177/0146621606297314
• IACAT. (2016). Research Strategies in CAT | IACAT. Retrieved February 2, 2019, from http://iacat.org/content/research-strategies-cat International Test Commission. (2005). ITC Guidelines for Translating and Adapting Tests. Retrieved February 2, 2019, from www.intestcom.org
• Jodoin, M. G., Zenisky, A., & Hambleton, R. K. (2006). Comparison of the psychometric properties of several computer-based test designs for credentialing exams with multiple purposes. Applied Measurement in Education, 19(3), 203–220. http://doi.org/10.1207/s15324818ame1903_3
• Kang, T., Cohen, A. S., & Sung, H.-J. (2005). IRT model selection methods for polytomous items. In: Annual Meeting of the National Council on Measurement in Education, Montreal, 2005. Retrieved February 2, 2019, from https://testing.wisc.edu/
• Kang, T., Cohen, A. S., & Sung, H.-J. (2009). Msodel selection indices for polytomous items. Applied Psychological Measurement, 33(7), 499–518. http://doi.org/10.1007/s00330-011-2364-3
• Karasar, N. (2009). Bilimsel araştırma yöntemleri. Ankara: Nobel Yayın Dağıtım.
• Kezer, F. (2013). Bilgisayar ortamında bireye uyarlanmış test stratejilerinin karşılaştırılması. Eğitim Bilimleri Araştırmaları Dergisi, 4(1), 145–175. http://doi.org/http://dx.doi.org/10.12973/jesr.2014.41.8
• Langenbucher, J. W., Labouvie, E., Martin, C. S., Sanjuan, P. M., Bavly, L., Kirisci, L., & Chung, T. (2004). An application of item response theory analysis to alcohol, cannabis, and cocaine criteria in DSM-IV. Journal of abnormal psychology, 113(1), 72. https://doi.org/10.1037/0021-843x.113.1.72
• Linden, W. J. Van Der, & Glas, C. A. W. (2010). Elements of Adaptive Testing. New York, NY: Springer.
• Linden, W. J. Van Der. (2005). A comparison of item-selection methods for adaptive tests with content constraints. Journal of Educational Measurement, 42(3), 283-302. http://dx.doi.org/10.1111/j.1745-3984.2005.00015.x
• Lu, P., Zhou, D., Qin, S., Cong, X., & Zhong, S. (2012). The study of item selection method in CAT. In: 6th International Symposium, ISICA (pp. 403–415). Wuhan - China.
• Nydick, S. (2022). catIrt: Simulate IRT-Based Computerized Adaptive Tests. R package version 0.5.1. https://CRAN.R-project.org/package=catIrt
• Ostini, R., & Nering, M. L. (2006). Polytomous item response theory models. SAGE.
• Paap, M. C. S., Born, S., & Braeken, J. (2019). Measurement efficiency for fixed-precision multidimensional computerized adaptive tests: comparing health measurement and educational testing using example banks. Applied Psychological Measurement, 43(1), 68–83. https://doi.org/10.1177/0146621618765719
• Paap, M. C. S., Kroeze, K. A., Glas, C. A. W., Terwee, C. B., van der Palen, J., & Veldkamp, B. P. (2017). Measuring patient-reported outcomes adaptively: multidimensionality matters!. Applied Psychological Measurement, 42(5), 327–342. https://doi.org/10.1177/0146621617733954
• Pedraza, O., Sachs, B. C., Ferman, T. J., Rush, B. K., & Lucas, J. A. (2011). Difficulty and discrimination parameters of Boston Naming Test items in a consecutive clinical series. Archives of Clinical Neuropsychology, 26(5), 434-444. https://doi.org/10.1093/arclin/acr042
• Ping, C., Shuliang, D., Haijing, L., & Jie, Z. (2006). Item selection strategies of computerized adaptive testing based on graded response model. Acta Psychologica Sinica, 38(03), 461. https://journal.psych.ac.cn/acps/EN/Y2006/V38/I03/461
• Reckase, M. D. (2009). Multidimensional item response theory models. In Multidimensional item response theory (pp. 79-112). Springer.
• Reise, S. P. (1990). A comparison of item- and person-fit methods of assessing model-data fit in IRT. Applied Psychological Measurement, 14(2), 127-137. https://doi.org/10.1177/014662169001400202
• Reise, S. P., & Henson, J. M. (2000). Computerization and adaptive administration of the NEO PI-R. Assessment, 7(4), 347–364. https://doi.org/10.1177/107319110000700404
• Reise, S. P., & Revicki, D. A. (2015). Handbook of item response theory modeling: Applications to typical performance assessment. Routledge.
• Ren, H., Choi, S.W. & van der Linden, W.J. (2020). Bayesian adaptive testing with polytomous items. Behaviormetrika 47, 427–449. https://doi.org/10.1007/s41237-020-00114-8
• Revelle, W. (2015) psych: Procedures for Personality and Psychological Research, Northwestern University, Evanston, Illinois, USA, http://CRAN.R-project.org/package=psych Version = 1.5.8.
• Rezaie, M., & Golshan, M. (2015). Computer adaptive test (CAT): Advantages and limitations. International Journal of Educational Investigations, 2(5), 128–137. http://www.ijeionline.com/attachments/article/42/IJEI_Vol.2_No.5_2015-5-11.pdf
• Rizopoulos, D. (2006). “ltm: An R package for Latent Variable Modelling and Item Response Theory Analyses.” Journal of Statistical Software, 17(5), 1–25. https://doi.org/10.18637/jss.v017.i05.
• Samejima, F. (1969). Estimation of latent ability using a response pattern of graded scores. Psychometrika, 35(17), 139. http://doi.org/10.1007/BF02290599
• Schinka, J. A., & Velicer, W. F. (2003). Research Methods in Psychology. In: I. B. Weiner (Ed.), Handbook of Psychology (Vol. 2). John Wiley & Sons, Inc.
• Simms, L. J., & Clark, L. A. (2005). Validation of a computerized adaptive version of the Schedule for Nonadaptive and Adaptive Personality (SNAP). Psychological Assessment, 17(1), 28–43. http://doi.org/10.1037/1040-3590.17.1.28
• Simms, L. J., Goldberg, L. R., Roberts, J. E., Watson, D., Welte, J., & Rotterman, J. H. (2011). Computerized adaptive assessment of personality disorder: introducing the CAT–PD project. Journal of Personality Assessment, 93(4), 380–389. http://doi.org/10.1080/00223891.2011.577475
• Şimşek, A.S., & Tavşancıl, E. (2022). Validity and reliability of Turkish version of skills confidence inventory. Turkish Psychological Counseling and Guidance Journal, 12(64), 89-107. https://doi.org/10.17066/tpdrd.1096008
• Smits, N., Cuijpers, P., & van Straten, A. (2011). Applying computerized adaptive testing to the CES-D scale: A simulation study. Psychiatry Research, 188(1), 147–155. http://doi.org/10.1016/j.psychres.2010.12.001
• Stochl, J., Böhnke, J. R., Pickett, K. E., & Croudace, T. J. (2016). An evaluation of computerized adaptive testing for general psychological distress: combining GHQ-12 and Affectometer-2 in an item bank for public mental health research. BMC Medical Research Methodology, 16(1), 58. http://doi.org/10.1186/s12874-016-0158-7
• Sulak, S., & Kelecioğlu, H. (2019). Investigation of Item Selection Methods According to Test Termination Rules in CAT Applications. Journal of Measurement and Evaluation in Education and Psychology, 315–326. https://doi.org/10.21031/epod.530528
• Thissen, D., & Wainer, H. (2001). Test Scoring. Lawrance Erlbaum Associates.
• Thompson, N. a., & Weiss, D. J. (2011). A framework for the development of computerized adaptive tests. Practical Assessment, Research and Evaluation, 16(1), 1–9. https://doi.org/10.7275/wqzt-9427 Veldkamp, B. P. (2001). Item selection in polytomous CAT. In Proceedings of the International Meeting of the Psychometric Society IMPS2001 (pp. 207–214). Osaka - Japan.
• Vogels, A. G. C., Jacobusse, G. W., & Reijneveld, S. A. (2011). An accurate and efficient identification of children with psychosocial problems by means of computerized adaptive testing. BMC Medical Research Methodology, 11, 111. http://doi.org/10.1186/1471-2288-11-111
• Wainer, H., Dorans, N. J., Eignor, D., Flaugher, R., Green, B. F., Mislevy, R., Thissen, D. (2000). Computerized adaptive testing: A primer (Second Ed). Lawrence Erlbaum Assocaiates.
• Waller, N. G., & Reise, S. P. (1989). Computerized adaptive personality assessment: an illustration with the Absorption scale. Journal of Personality and Social Psychology, 57(6), 1051–1058. http://doi.org/10.1037/0022-3514.57.6.1051
• Wang, S., & Wang, T. (2002). Relative precision of ability estimation in polytomous CAT: a comparison under the generalized partial credit model and graded response model. American Educational Research Association.
• Weiss, D. J. (1982). Improving measurement quality and efficiency with adaptive testing. Applied Psychological Measurement, 6(4), 473–492. https://doi.org/10.1177/014662168200600408
• 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. Retrieved from http://www.psych.umn.edu/psylabs/catcentral/pdf files/we04070.pdf
• Weiss, D. J. (2011). Better data from better measurements using computerized adaptive testing. Journal of Methods and Measurement in the Social Sciences, 2(1), 1–23. Retrieved from https://www.assess.com/docs/Weiss(2011)_CAT.pdf
• Yasuda, J. I., Hull, M. M., & Mae, N. (2022). Improving test security and efficiency of computerized adaptive testing for the Force Concept Inventory. Physical Review Physics Education Research, 18(1), 010112. https://doi.org/10.1103/PhysRevPhysEducRes.18.010112