International journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN:2313-626X

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 Volume 6, Issue 6 (June 2019), Pages: 22-29

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 Original Research Paper

 Title: Validation of a developed university placement test using classical test theory and Rasch measurement approach

 Author(s): Ado Abdu Bichi *, Rohaya Talib, Noor Azean Atan, Halijah Ibrahim, Sanitah Mohd Yusof

 Affiliation(s):

 School of Education, Universiti Teknologi Malaysia 81310, Jahor Bahru, Malaysia

  Full Text - PDF          XML

 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0003-2897-5136

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2019.06.004

 Abstract:

University entrances examinations are conducted to ensure qualified applicant are placed into appropriate programs of their choices. The outcomes of the test have an important and significant value in taking appropriate decision on the applicant’s eligibility, the validity of that examination is paramount to achieving the set goal. The aim of this study is to provide empirical evidence of the construct validity of the newly developed Economics Test using traditional Classical Test Theory and Rasch Measurement Model. The developed Economics Test consists of 70 items after expert judgment and review was administered to 280 students, age 16-20 randomly selected from two public schools in Kano. The study employed a CTT and Rasch model to analyze the data using ITEMAN 4.3 and WINSTEPS 3.72.3 software. The softwares automatically generate the recommended estimate of the parameters to judge the quality of the test items. The results of CTT identified 17 problematic items using difficulty and discriminating index. The results of Rasch showed person statistics (Separation 2.40>2.00 and reliability 0.85>0.80) and item statistics (separation 3.73>3.0 and reliability 0.93>0.8) an excellent person and item reliability. The test measures unidimensional construct supported by the raw variance of 24.9% explained by measures. Investigation of the item person map revealed that the test covered a wide range of the examinees’ ability. Overall, using Rasch 10 misfitting construct irrelevant items were identified for deletion. While CTT provides information that is limited to two parameters, the Rasch results provide very detailed information on the quality of the test items. Thus both models can be integrated to generate enough evidence of validity and reliability items in the development of a standardize test. 

 © 2019 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Rash model, Classical test theory, Validity, Placement test, Item response theory

 Article History: Received 15 December 2018, Received in revised form 29 March 2019, Accepted 1 April 2019

 Acknowledgement:

No Acknowledgement.

 Compliance with ethical standards

 Conflict of interest:  The authors declare that they have no conflict of interest.

 Citation:

 Bichi AA, Talib R, and Atan NA et al. (2019). Validation of a developed university placement test using classical test theory and Rasch measurement approach. International Journal of Advanced and Applied Sciences, 6(6): 22-29

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 Figures

 Fig. 1

 Tables

 Table 1 Table 2 Table 3 Table 4 

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 References (22) 

  1. Abdul-Latif A, Jalilah I, Amin NFM, and Libunao W (2016). Multiple-choice items analysis using classical test theory and Rasch measurement model. Man in India, 96(1-2): 173-181.   [Google Scholar]
  2. Akanwa UN and Nkwocha PC (2015). Prediction of south eastern Nigerian students’ under graduate scores with their UME and Post-UME scores. IOSR Journal of Research and Method in Education, 5(5): 36-39.   [Google Scholar]
  3. Baghaei P (2008). The Rasch model as a construct validation tool. Rasch Measurement Transactions, 22(1): 1145-1146.   [Google Scholar]
  4. Baghaei P and Amrahi N (2011). Validation of a multiple choice English vocabulary test with the Rasch model. Journal of Language Teaching and Research, 2(5): 1052-1060. https://doi.org/10.4304/jltr.2.5.1052-1060   [Google Scholar]
  5. Bichi AA (2016). Classical test theory: Introduction to linear modeling approach to test and item analysis. International Journal for Social Studies, 2(9): 27–33.   [Google Scholar]
  6. Bichi AA, Embong R, and Mamat M (2015). Comparison of classical test theory and item response theory: A review of empirical studies. Australian Journal of Basic and Applied Sciences, 9(7): 549-556.   [Google Scholar]
  7. Bond TG and Fox CM (2007). Applying the Rasch model: Fundamental measurement in the social sciences. Lawrence Erlbaum Associates Publishers, Mahwah, New Jersey, USA.   [Google Scholar]
  8. Champlain DAF (2010). A primer on classical test theory and item response theory for assessments in medical education. Medical Education, 44(1): 109-117. https://doi.org/10.1111/j.1365-2923.2009.03425.x   [Google Scholar] PMid:20078762
  9. Dai-Trang L (2013). Applying item response theory modeling in educational research. Ph.D. Dissertation, Iowa State University Ames, Iowa, USA.   [Google Scholar]
  10. Ebel RI and Frisbie DA (1991). Essentials of educational measures. Prentice-Hall, Englewood Cliffs, New Jersey, USA.   [Google Scholar]
  11. Ebiri K (2006). Post jamb basis for admission says Obasanjo. The Guardian Newspaper, Kings Place, London, UK.   [Google Scholar]
  12. Haladyna TM and Downing SM (2011). Twelve steps for effective test development. In: Lane S, Raymond MR, and Haladyna TM (Eds.), Handbook of test development: 17-40. Routledge, Abingdon, UK.   [Google Scholar]
  13. Hambleton RK and Jones RW (1993). An NCME instructional module on: Comparison of classical test theory and item response theory and their applications to test development. Educational Measurement: Issues and Practice, 12(3): 38-47. https://doi.org/10.1111/j.1745-3992.1993.tb00543.x   [Google Scholar]
  14. Henning G (1987). A guide to language testing: Development, evaluation, research. Newbury House, Cambridge, USA.   [Google Scholar]
  15. Ikoghode A (2015). Post-UTME screening in Nigerian universities: How relevant today?. International Journal of Education and Research, 3(8): 101-116.   [Google Scholar]
  16. JAMB (2016). JAMB statistics: 2016 application and admission. Joint Admissions and Matriculation Board. Nigeria. Available online at: http://www.jambng.com   
  17. Linacre JM (2012). A user’s guide to Winsteps-Ministep: Rasch-model computer programs. Program manual 3.68.0. Available online at: http://www.winsteps.com/manuals.htm  
  18. Petrillo J, Cano SJ, McLeod LD, and Coon CD (2015). Using classical test theory, item response theory, and Rasch measurement theory to evaluate patient-reported outcome measures: A comparison of worked examples. Value in Health, 18(1): 25-34. https://doi.org/10.1016/j.jval.2014.10.005   [Google Scholar] PMid:25595231
  19. Salleh TS, Bakri N, and Zin ZM (2016). Evaluating a technical university’s placement test using the Rasch measurement model. In the AIP Conference Proceedings, AIP Publishing, 1782(1): 1-7.   [Google Scholar]
  20. Smiley J (2015). Classical test theory or Rasch: A personal account from a novice user. SHIKEN, 19(1): 16-29.   [Google Scholar]
  21. Zaman A, Kashmiri AUR, Mubarak M, and Ali A (2008). Students ranking, based on their abilities on objective type test: Comparison of CTT and IRT. In the EDU-COM 2008 International Conference, Edith Cowan University, Perth Western Australia, 1: 281-297.   [Google Scholar]
  22. Zubairi AM and Kassim NLA (2016). Classical and Rasch analyses of dichotomously scored reading comprehension test items. Malaysian Journal of ELT Research, 2(1): 1-20.   [Google Scholar]