Using connectionist models to evaluate examinees' response patterns to achievement tests

Journal of Modern Applied Statistical Methods

Volumn 7, Issue 1, 2008, Pages 234-245

  Gierl, Mark J ^a   Cui, Ying ^a   Hunka, Steve ^a  

^a UNIVERSITY OF ALBERTA   (Canada)

Author keywords

Attribute hierarchy method; Educational measurement; Multilayer perceptron; Neural network

Indexed keywords

EID: 77950354789     PISSN: 15389472     EISSN: 15389472     Source Type: Journal    
DOI: 10.22237/jmasm/1209615480     Document Type: Article

References (15)

1. Du Toit, M. (2003). IRT from SSI: BILOGMG, MULTILOG, PARSCALE, TESTFACT [Computer Programs], Lincolnwood, IL: Scientific Software.
2. Gällmo, O, & Carlström, J. (1995). Some experiments using extra output learning to hint multi layer perceptrons. In L. F. Niklasson, M. B. Boden (Eds.), Current trends in connections-Proceedings of the 1995 Swedish conference on connections (pp. 179-190). Mahwah, NJ: Erlbaum.
3. 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. Invited Paper appearing in Special Issue of IRT-Based Cognitive Diagnostic Models and Related Methods, Lou DiBello & William Stout (Guest Editors).
4. 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 in education: Theory and applications. (pp. 242-274). Cambridge, UK: Cambridge University Press.
5. ©. New York: College Examination Board.
6. ©. New York: College Examination Board.
7. Leighton, J. P., & Gierl, M. J. (Eds.) (2007a). Cognitive diagnostic assessment for education: Theory and Applications. Cambridge, UK: Cambridge University Press.
8. Leighton, J. P., & Gierl, M. J. (2007b). Defining and evaluating models of cognition used in educational measurement to make inferences about examinees' thinking processes. Educational Measurement: Issues and Practice, 26, 3-16.
9. 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.
10. Luecht, R. M. (2006, September). Assessment engineering: An emerging discipline. Paper presented in the Centre for Research in Applied Measurement and Evaluation, University of Alberta, Edmonton, AB, Canada.
11. McClelland, J. L. (1998). Connectionist models and Bayesian inference. In M. Oaksford & N. Chater (Eds.), Rational Models of Cognition. Oxford: Oxford University Press. 21-53.
12. Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986a). Learning representations by back-propagating errors. Nature, 323, 533-536.
13. Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986b). Parallel distributed processing (Vol. 1). Cambridge, MA: MIT Press.
14. rd Edition., pp. 263-331). New York: American Council on Education, Macmillian.
15. Wiley, T. (2006, May). Formative instruction and the quest for the killer application, Eduventures, Boston, MA.