The purpose of this literature review is to explicate the facets of mathematical problem solving taxonomies in relation to mathematical modeling. Subsequently, components and learning benefits of mathematical modeling are discussed. Examples of mathematical problems are embedded in the discussion and pragmatic applications to mathematical…

This study investigated the extent to which various latent class models adequately described elementary rule-governed mathematical behaviors. Children were given a fraction concepts test. Results supported the adoption of a set of three-class models including a mastery class, a nonmastery class, and a transitional class to describe the data.…

Staddon and Motheral derived a mathematical model of responding in concurrent variable-interval--variable-interval schedules. Their derivation ignores a fundamental aspect of the concurrent schedule contingency. A reinforcer can occur following two consecutive responses on the same schedule or following a switch between the two schedules.…

Heyman's major criticism (TM 504 810) of Staddon and Motheral's reinforcement maximization model is that it does not consider "local" and "interchangeover" interresponse times separately. We show that this separation may not be necessary. Heyman's apparent gain in comprehensiveness may not be worth the added complexity.…

Discusses the relationship of fidelity and learning in computer simulation. Highlights include a review of previous research; a discussion of transfer of learning; a taxonomy for fidelity analysis with four different types of computer-based instructional simulations; and implications for instructional design and research. (41 references)…

It has been 25 years since the publication of J. B. Carroll's (1963) seminal work on the model of school learning (MSL) and its subsequent identification by B. S. Bloom (1968) as the theoretical basis underlying mastery learning. Carroll's model of school learning is a theoretical formulation asserting that the degree of learning attained on a…

A general model for a quantitative description of individual growth in learning was developed. Published data in a variety of areas and data on learning sequences in a classroom were processed through the model. Findings suggest that the general growth model governs growth phenomena. (Author/RD)