Data reasoning is an essential component of scientific reasoning, as a component of evidence evaluation. In this paper, we outline a model of scientific data reasoning that describes how data sensemaking underlies data reasoning. Data sensemaking, a relatively automatic process rooted in perceptual mechanisms that summarize large quantities of…

Education researchers often study count variables, such as times a student reached a goal, discipline referrals, and absences. Most researchers that study these variables use typical regression methods (i.e., ordinary least-squares) either with or without transforming the count variables. In either case, using typical regression for count data can…

Heterogeneity in response styles can affect the conclusions drawn from rating scale data. In particular, biased estimates can be expected if one ignores a tendency to middle categories or to extreme categories. An adjacent categories model is proposed that simultaneously models the content-related effects and the heterogeneity in response styles.…

This dissertation comprises three papers that propose, discuss, and illustrate models to make improved inferences about research questions regarding student achievement in education. Addressing the types of questions common in educational research today requires three different "extensions" to traditional educational assessment: (1)…

Dealing with alternative causes is necessary to avoid making inaccurate causal inferences from covariation data. However, information about alternative causes is frequently unavailable, rendering them unobserved. The current article reviews the way in which current learning models deal, or could deal, with unobserved causes. A new model of causal…

Explains a model that can be used for debriefing after a highly interactive training activity such as role playing or simulation games. Elements of the model include (1) general decompression; (2) factual information from the activity; (3) inferences; (4) transfer, i.e., from the activity to real world situations; (5) generalizations; and (6)…

Provides general background on basic concepts of systems theory. Discusses applications of systems theory to computational and inferential chemistry in molecular and reaction systems, systems analysis, and synthesis. Describes methodology for studying chemical systems by computer and gives advantages of an integrated computational environment. (JM)