Golden, R. M. and Goldman, S. R. (submitted). An Empirical Feasibility Study of the ARCADE System. This publication provides a good overview of the ARCADE system methodology.
Golden, R. M. (2006). AUTOCODER Software Tutorial (Version 01-29-06). School of Behavioral and Brain Sciences. University of Texas at Dallas, Richardson, TX, 75083-0688. Powerpoint tutorial on using the AUTOCODER software for semi-automatically coding free response data as ordered sequences of SIMPLE propositions. Click here to register/download software!
Golden, R. M. (2006). ASMURF Software Tutorial (Version 01-29-06). School of Behavioral and Brain Sciences. University of Texas at Dallas, Richardson, TX, 75083-0688. Powerpoint tutorial on using the ASMURF software for semi-automatically coding free response data as ordered sequences of COMPLEX propositions. Click here to register/download software!
Golden, R. M. (2006). KDC Software Tutorial (Version 01-29-06). School of Behavioral and Brain Sciences. University of Texas at Dallas, Richardson, TX, 75083-0688. Powerpoint tutorial on using the KDC software for analyzing student free response data which has been coded as an ordered sequence of integers (each integer referring to a particular idea) as a categorical time-series. Click here to register/download software!
Golden, R. M. (2006). Technical Report: Knowledge Digraph Contribution Analysis (Version 01-29-06). School of Behavioral and Brain Sciences (GR4.1), University of Texas at Dallas, Richardson, TX 75083-0688. Technical report which presents the new KDC mathematical analysis theory as implemented in the KDC software package. The results of this technical report are based upon the results of Golden (2003).
Golden, R. M. (2006). Technical Report: Annotated Semantic Markov Utterance Random Fields for Information Extraction. (Version 01-29-06). School of Behavioral and Brain Sciences (GR4.1), University of Texas at Dallas, Richardson, TX 75083-0688. Technical report which presents the new ASMURF mathematical theory as implemented in the ASMURF software package.
Golden, R. M. (2003). Discrepancy risk model selection test theory for comparing possibly misspecified or nonnested models. Psychometrika, 68, 229-249. Provides the mathematical foundations which are necessary for the development of KDC theory. Develops an asymptotic statistical theory for parameter estimation and model selection for categorical time-series analysis. Presents a new statistical test for comparing models which may be possibly misspecified or non-nested.
Goldman, S. R., Golden, R. M., & Van den Broek, P. (in press). Why are computational models of text comprehension useful? In F. Schmalhoefer & C. A. Perfetti (Eds.), Higher Level Language Processes in the Brain: Inference and Comprehension Processes. Mahwah, NJ: Erlbaum Overview of the role of computational models in text comprehension research.
This material is based upon work supported by the National Science Foundation under Grant No. 0113669. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.