We perform two approaches of machine learning, logistic regressions and decision trees, to predict student dropout at the Karlsruhe Institute of Technology (KIT). The models are computed on the basis of examination data, i.e. data available at all universities without the need of specific collection. Therefore, we propose a methodical approach…

A heuristic approach to explaining of the Black-Scholes option pricing model in undergraduate classes is described. The approach draws upon the method of protocol analysis to encourage students to "think aloud" so that their mental models can be surfaced. It also relies upon extensive visualizations to communicate relationships that are…

There is evidence to suggest that the effects of behavioral interventions may be limited to specific types of individuals, but methods for evaluating such outcomes have not been fully developed. This study proposes the use of finite mixture models to evaluate whether interventions, and, specifically, group randomized trials, impact participants…

Discusses the concept of temperament interactions in the context of statistical interaction. Categorizes temperament interactions that involve temperament as an independent variable, as a dependent variable, or as both. Describes use of hierarchical multiple regression for the analysis of temperament interactions. (Author/CI)

The viability of Freeman's model, which uses three equations to analyze causative demand and supply determinants, is examined as a management tool for explaining and predicting enrollments and the job market using macro and micro cases. (MSE)

The use of high school transcipts, American College Testing Service composite scores, and first semester courses and grades of college freshmen is discussed as a way to statistically analyze the notion that high school college preparatory courses help students earn better grades in college than elective courses do. (MSE)