Among community college leaders and others interested in reforms to improve student success, there is growing interest in adopting machine learning (ML) techniques to predict credential completion. However, ML algorithms are often complex and are not readily accessible to practitioners for whom a simpler set of near-term measures may serve as…

Predicting the students' performance has become a challenging task due to the increasing amount of data in educational systems. In keeping with this, identifying the factors affecting the students' performance in higher education, especially by using predictive data mining techniques, is still in short supply. This field of research is usually…

The 3-year graduation rate is a rarely measured metric in higher education compared to its 4- or 6- year graduation rate counterparts. For the first time in college (FTIC) students to graduate in three years, they must come with certain skills, abilities, plans, supports, or motivations. This project considers two distinct but interrelated ways of…

The accountability of colleges and universities is a high priority for those making policy decisions. The purpose of this study was to determine institutional characteristics predicting retention rates, graduation rates and transfer-out rates using publicly available data from the US Department of Education. Using regression analysis, it was…

A recent resurgence in logical-rule theories of categorization has motivated the development of a class of models that predict not only choice probabilities but also categorization response times (RTs; Fific, Little, & Nosofsky, 2010). The new models combine mental-architecture and random-walk approaches within an integrated framework and…

The development of a typology of community college students is a topic of long-standing and growing interest among educational researchers, policy-makers, administrators, and other stakeholders, but prior work on this topic has been limited in a number of important ways. In this paper, I develop a behavioral typology based on students'…

To provide cross-validation data for the Child Abuse Potential Inventory, classification rates were determined for 220 physical child abusers and matched control subjects. Using all protocols, a discriminant analysis indicated the Abuse scale correctly classified 85.4% of the subjects, with 82.7% of the abusers and 88.2% of the control subjects…

Predictive discriminant analysis involves a technique used in multivariate classification, i.e., in predicting membership in well-defined groups for units on which multiple measures are available. The validation (assessment) of group membership predictions pertains to two problems: estimating true proportions of correct classifications (i.e., hit…

Correlations between the two screening tests and between the screening and criterion measures were inconsistent with prediction rates based on classificational screening test scores. On the basis of correlational validity coefficients, relationships between measures in this study would have been overestimated. (Author/SBH)

This study investigated the mediating effects of learning a memory strategy on second-graders' performance of a memory task and their self-efficacy for the task. Specifically, second-graders were taught a strategy for organizing words into categories to increase their ability to remember lists of words. Their predictions of how many words they…

Three estimates of the probabilities of correct classification in predictive discriminant analysis were computed using mathematical formulas, resubstitution, and external analyses: (1) optimal hit rate; (2) actual hit rate; and (3) expected actual hit rate. Methods were compared using Monte Carlo sampling from two data sets. (Author/GDC)

Presents a mathematical-categorization model using multiple-step chains of reasoning (CORs) and memory for examples. In 5 experiments, 144 undergraduates memorized descriptions of fictional people, then made predictions from incomplete descriptions using 1-, 2-, or 3-step CORs. The multiple-step context model with one- and two-step inference…

The issues in the interpretation of discriminant analyses presented are restricted to the typical uses of discriminant analysis by behavioral science researchers. Because behavioral researchers use computer programs packages, the issues discussed deal with information obtainable from the package discriminant analysis programs. The following issues…

Classification accuracies of models for predicting later high school dropouts from data available in student records for grades 4 through 8 were examined for 503 dropouts and 282 persisters (nondropouts) in Florida. Separate prediction models for each grade level have practical importance; implications for dropout prediction are discussed. (SLD)

A battery of 11 nonverbal tests were administered to a sample of 2,362 non-prior service enlistees who had been selected to one of seven technical schools. The usefulness of additional aptitudinal and educational data was also investigated. The number of significant relationships between certain nonverbal tests and final technical school grade…