A Non-technical Approach for Illustrating Item Response Theory

A Non-technical Approach for Illustrating Item Response Theory

Authors

  • Arizona State University
  • Arizona State University
  • Arizona State University

Keywords:

Item Response Theory, Assessment, Measurement, Classical Test Theory, Multimedia

Abstract

Since the introduction of the No Child Left Behind Act, assessment has become a pre-dominant theme in the US K-12 system. However, making assessment results understandable and usable for the K-12 teachers has been a challenge. While test technology offered by various vendors has been widely implemented, technology of training for test development seems to be underdeveloped. The objective of this presentation is to illustrate a well-designed interactive tutorial for understanding the complex concepts of Item Response Theory (IRT). The approach of this tutorial is to dissociate IRT from Classical Test Theory (CTT) because it is the belief of the authors that the mis-analogy between IRT and CTT could lead to misconceptions. Initial user feedback is collected as input for further refining the program.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Downloads

Published

2014-04-09

How to Cite

Ho Yu, C., Jannasch-Pennell, A., & DiGangi, S. (2014). A Non-technical Approach for Illustrating Item Response Theory. Journal of Applied Testing Technology, 9(2), 1–32. Retrieved from https://jattjournal.net/index.php/atp/article/view/48347

Issue

Section

Articles

References

Brown, J. R. (2004). Why thought experiments transcend empiricism? In Christopher Hitchcock (Ed.), Contemporary debates in philosophy of science (pp. 21-43). MA: Blackwell.

Doran, H. C. (2005). The information function for the one-parameter logistic model: Is it reliability? Educational and Psychological Measurement, 65, 759-769.

Embretson, S., & Reise, S. (2000). Item response theory for psychologists. Mahwah, N.J.: L.Erlbaum Associates.

Goertz, M., & Duffy, M. (2003). Mapping the landscape of high-stakes testing and accountability programs. Theory into Practice, 42, 4-11.

Linacre J. M., & Wright, B. D. (1994) Chi-Square Fit Statistics. Rasch Measurement Transactions, 8(2), 350.

Spearman, C. (1904). General intelligence: Objectively determined and measured. American Journal of Psychology, 15, 201-293.

Sweller, J., & Chandler, P. (1991). Evidence for cognitive load theory. Cognition and Instruction, 8, 351-362.

Thompson, B. (1994). Guidelines for the authors. Educational and Psychological Measurement 54, 837-847.

Thompson, B., & Vacha–Haase, T. (2000). Psychometrics is datametrics: The test is not reliable. Educational and Psychological Measurement, 60, 174–195.

Yu, C. H. (1993). Use and effectiveness of navigational aids in a hypertext system. Unpublished master's thesis, University of Oklahoma, Norman, OK.

Yu, C. H. (2006). SAS programs for generating Winsteps control files and web-based presentations. Applied Psychological Measurement, 30, 247-248.

Yu, C. H. (2007). A simple guide to the Item Response Theory. Retrieved May 1, 2007, from http://www.ssicentral.com/irt/resources.html

Loading...