This "Practitioner's Guide to Growth Models," commissioned by the Technical Issues in Large-Scale Assessment (TILSA) and Accountability Systems & Reporting (ASR), collaboratives of the "Council of Chief State School Officers," describes different ways to calculate student academic growth and to make judgments about the…

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…

Presents a method to improve client classification. Reviews clinical prediction models and statistical prediction issues. In classifying clients for remedial services, utility of the prediction scheme depends on gains accrued by its use over program base rates and relative cost. This assumes that differential treatments parallel diagnostic…

This paper discusses the principles underlying discriminant analysis and constructs a simulated data set to illustrate its methods. Discriminant analysis is a multivariate technique for identifying the best combination of variables to maximally discriminate between groups. Discriminant functions are established on existing groups and used to…

This overview of both quantitative and qualitative methods of educational forecasting is introduced by a discussion of a general typology of forecasting methods. In each of the following sections, discussion follows the same general format: a number of basic approaches are identified (e.g. extrapolation, correlation, systems modelling), and each…

Methodologies were proposed for combining background and aptitude and/or achievement information in an approach to the classification problem using the concept of under- and overachievement. The methodologies were applied to independent samples from four high school curricula. The results suggest that when past achievement and/or aptitudes were…