Explores whether flexible nonlinear models (including neural networks and genetic algorithms) can reveal otherwise unexpected patterns of relationship in typical school-productivity data. Applying three types of algorithms alongside regression modeling to school-level data in 183 elementary schools proves the hypothesis and reveals new directions…

When learning is taking place, students test their hypotheses and evaluate them, and modify their current theories on the basis of new information. This phenomenon is known as "hypothesis testing view" or "theory changes." Many students change their rules to another while they are taking a test. This study introduced a new…

Recent developments in dichotomous factor analysis based on multidimensional item response models (Bock and Aitkin, 1981; Muthen, 1978) provide an effective method for exploring the dimensionality of questionnaire items. Implemented in the TESTFACT program, this "full information" item factor analysis accounts not only for the pairwise…

Guiding principles for using sliding fee scales are presented in this paper in an effort to help states plan new child care initiatives, coordinate or strengthen existing programs, and improve sliding fee scales for current programs. Introductory comments urge states to adopt a single sliding fee scale for all their child care programs. The report…

This volume contains tables of item analysis results obtained by following procedures associated with the Rasch Model for those reading tests used in the Anchor Test Study. Appendix I gives the test names and their corresponding analysis code numbers. Section I (Basic Item Analyses) presents data for the item analysis of each test in a two part…