Advertisement

Three-Category Adaptive Classification Testing

  • Theo J. H. Eggen
Chapter
Part of the Statistics for Social and Behavioral Sciences book series (SSBS)

Abstract

Educational and psychological testing can have many practical purposes. From the perspective of test users, a distinction among selection, placement, certification, licensuring, monitoring of progress in proficiency, and diagnostic testing can be made. From the measurement point of view, it generally suffices to distinguish between estimation and classification.

Keywords

Item Response Theory Fisher Information Item Bank Item Response Theory Model Computerize Adaptive Testing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Chang, H.-H. & Ying, Z. (1996). A global information approach to computerized adaptive testing. Applied Psychological Measurement, 20, 213–229.CrossRefGoogle Scholar
  2. Cover, T. M. & Thomas, J. A. (1991). Elements of information theory. New York: Wiley.MATHCrossRefGoogle Scholar
  3. Cronbach, L. J. & Gleser, G. C. (1965). Psychological tests and personnel decisions. (2nd ed.). Urbana, IL: University of Illinois Press.Google Scholar
  4. DeGroot, M. H. (1970). Optimal statistical decisions. New York: McGraw-Hill.MATHGoogle Scholar
  5. Eggen, T. J. H. M. (1999). Item selection with adaptive testing with the sequential probability ratio test. Applied Psychological Measurement, 23, 249–261.CrossRefGoogle Scholar
  6. Eggen, T. J. H. M. & Straetmans, G. J. J. M. (2000). Computerized adaptive testing for classifying examinees into three categories. Educational and Psychological Measurement, 66, 713–734.CrossRefGoogle Scholar
  7. Ferguson, R. L. (1969). The development, implementation, and evaluation of a computer-assisted branched test for a program of individually prescribed instruction. Unpublished doctoral dissertation, University of Pittsburgh, Pittsburgh, PA.Google Scholar
  8. Hambleton, R. K., Swaminathan, H., Algina, J. & Coulson, D. B. (1978). Criterion-referenced testing and measurement: A review of technical issues and developments. Review of Educational Research, 48, 1–47.Google Scholar
  9. Kingsbury, G. G. & Weiss, D. J. (1983). A comparison of IRT-based adaptive mastery testing and a sequential mastery testing procedure. In D. J. Weiss (Ed.), New horizons in testing (pp. 257–286). New York: Academic Press.Google Scholar
  10. Parshall, C. G., Spray, J. A., Kalohn, J. C. & Davey, T. (2002). Practical considerations in computer-based testing. New York: Springer-Verlag.MATHGoogle Scholar
  11. Reckase, M. D. (1983). A procedure for decision making using tailored testing. In: D. J. Weiss (Ed.), New horizons in testing (pp. 237–255). New York: Academic Press.Google Scholar
  12. Smith, R. L. & Lewis, C. (1995, April). A Bayesian computerized mastery model with multiple cut scores. Paper presented at the annual meeting of the National Council on Measurement in Education, San Francisco, CA.Google Scholar
  13. Spray, J. A. & Reckase, M. D. (1994, April). The selection of test items for decision making with a computer adaptive test. Paper presented at the annual meeting of the National Council on Measurement in Education, New Orleans, LA.Google Scholar
  14. Spray, J. A. & Reckase, M. D. (1996). Comparison of SPRT and sequential Bayes procedures for classifying examinees into two categories using a computerized test. Journal of Educational and Behavioral Statistics, 21, 405–414.Google Scholar
  15. van der Linden, W. J. (1998). Bayesian item selection criteria for adaptive testing. Psychometrika, 63, 201–216.MATHCrossRefMathSciNetGoogle Scholar
  16. Vos, H. J. (1999). Applications of Bayesian decision theory to sequential mastery testing. Journal of Educational and Behavioral Statistics, 24, 271–292.Google Scholar
  17. Vos, H. J. (2002). Applying the minimax principle to sequential mastery testing. In A. Ferligoj and A. Mrvar (Eds.), Developments in social science methodology. Metodoloski zvezki, 18, Ljubljana: FDV.Google Scholar
  18. Wainer, H. (Ed.), (2000). Computerized adaptive testing. A primer (2nd ed.). Hilsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  19. Wald, A. (1947). Sequential analysis. New York: Wiley.MATHGoogle Scholar
  20. Warm, T. A. (1989). Weighted maximum likelihood estimation of ability in item response theory. Psychometrika,54, 427–450.CrossRefMathSciNetGoogle Scholar
  21. Weiss, D. J. & Kingsbury, G. G. (1984). Application of computerized adaptive testing to educational problems. Journal of Educational Measurement, 21, 361–375.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Theo J. H. Eggen
    • 1
  1. 1.Cito Institute for Educational MeasurementArnhemThe Netherlands

Personalised recommendations