Reliability and attribute-based scoring in cognitive diagnostic assessment

Journal of Educational Measurement

Volumn 46, Issue 3, 2009, Pages 293-313

  Gierl, Mark J ^a   Cui, Ying ^a   Zhou, Jiawen ^a  

^a UNIVERSITY OF ALBERTA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 69749107348     PISSN: 00220655     EISSN: 17453984     Source Type: Journal    
DOI: 10.1111/j.1745-3984.2009.00082.x     Document Type: Article

References (23)

1. American Educational Research Association, American Psychological Association, and National Council on Measurement in Education (1999). Standards for Educational and Psychological Testing. Washington, DC : American Educational Research Association.
2. Cui, Y., Leighton, J. P., Gierl, M. J., & Hunka, S. (2006, April). A person-fit statistic for the attribute hierarchy method: The hierarchy consistency index. Paper presented at the annual meeting of the National Council on Measurement in Education, San Francisco.
3. de la Torre, J., & Douglas, J. (2004). Higher-order latent trait models for cognitive diagnosis. Psychometrika, 69, 333 353.
4. Fischer, G. H. (1973). The linear logistic test model as an instrument in educational research. Acta Psychologica, 37, 359 374.
5. Gierl, M. J. (2007). Making diagnostic inferences about cognitive attributes using the rule space model and attribute hierarchy method. Journal of Educational Measurement, 44, 325 340.
6. Gierl, M. J., Cui, Y, & Hunka, S. (in press). Using connectionist models to evaluate examinees' response patterns on tests. Journal of Modern Applied Statistical Methods.
7. Gierl, M. J., Leighton, J. P., & Hunka, S. (2007). Using the attribute hierarchy method to make diagnostic inferences about examinees' cognitive skills. In J. P. Leighton & M. J. Gierl (Eds. Cognitive diagnostic assessment for education: Theory and applications (pp. 242 274). Cambridge, UK : Cambridge University Press.
8. ©. Journal of Technology, Learning, and Assessment, 6 (6 1 53.
9. Gierl, M. J., Zheng, Y., & Cui, Y. (2008). Using the attribute hierarchy method to identify and interpret the cognitive skills that produce group differences. Journal of Educational Measurement, 45, 65 89.
10. Gierl, M. J., & Zhou, J. (2008). Computer adaptive-attribute testing: A new approach to cognitive diagnostic assessment. Zeitschift für Psychologie - Journal of Psychology, 216, 29 39.
11. Junker, B. W., & Sijtsma, K. (2001). Cognitive assessment models with few assumptions and connections with nonparametric item response theory. Applied Psychological Measurement, 25, 258 272.
12. Leighton, J. P., & Gierl, M. J. (2007). Defining and evaluating models of cognition used in educational measurement to make inferences about examinees' thinking processes. Educational Measurement: Issues and Practice, 26 (2 3 16.
13. Leighton, J. P., Gierl, M. J., & Hunka, S. (2004). The attribute hierarchy model: An approach for integrating cognitive theory with assessment practice. Journal of Educational Measurement, 41, 205 236.
14. Nichols, P. D., & Smith, P. L. (1998). Contextualizing the interpretation of reliability data. Educational Measurement: Issues and Practice, 17 (3 24 36.
15. Pellegrino, J. W., Baxter, G. P., & Glaser, R. (1999). Addressing the "two disciplines" problem: Linking theories of cognition and learning with assessment and instructional practices. In A. Iran-Nejad & P. D. Pearson (Eds. Review of Research in Education (pp. 307 353). Washington, DC : American Educational Research Association.
16. Roussos, L., DiBello, L., Stout, W., Hartz, S., Henson, R., & Templin, J. (2007). The fusion model skills diagnostic system. In J. P. Leighton & M. J. Gierl (Eds. Cognitive diagnostic assessment in education: Theory and applications (pp. 275 318). Cambridge, UK : Cambridge University Press.
17. Tatsuoka, K. K. (1983). Rule space: An approach for dealing with misconceptions based on item response theory. Journal of Educational Measurement, 20, 345 354.
18. Tatsuoka, K. K. (1990). Toward an integration of item-response theory and cognitive error diagnosis. In N. Fredrickson, R. L. Glaser, A. M. Lesgold, & M. G. Shafto (Eds. Diagnostic monitoring of skills and knowledge acquisition (pp. 453 488). Hillsdale, NJ : Erlbaum.
19. Tatsuoka, K. K. (1991). Boolean algebra applied to the determination of the universal set of knowledge states (Research Report 91-2-ONR). Princeton, NJ : Educational Testing Service.
20. Tatsuoka, K. K. (1995). Architecture of knowledge structures and cognitive diagnosis: A statistical pattern recognition and classification approach. In P. D. Nichols, S. F. Chipman, & R. L. Brennan (Eds. Cognitively diagnostic assessment (pp. 327 359). Hillsdale, NJ : Erlbaum.
21. Templin, J. L., & Henson, R. A. (2006). Measurement of psychological disorders using cognitive diagnosis models. Psychological Methods, 11, 287 305.
22. von Davier, M. (2007). Hierarchical general diagnostic models (Research Report No. RR-07-19). Princeton, NJ : Educational Testing Service.
23. Wang, C., & Gierl, M. J. (2007, April). Investigating the cognitive processes underlying student performance on the SAT Critical Reading subtest. Paper presented at the annual meeting of the National Council on Measurement in Education, Chicago.