Student modeling can help guide the behavior of a cognitive tutor system and provide insight to researchers on understanding how students learn. In this context, Bayesian Knowledge Tracing (BKT) is one of the most popular knowledge inference models due to its predictive accuracy, interpretability and ability to infer student knowledge. However,…

The present article considers a fundamental question in evaluation research: "By how much do program effects vary across sites?" The article first presents a theoretical model of cross-site impact variation and a related estimation model with a random treatment coefficient and fixed site-specific intercepts. This approach eliminates…

In many surveys, the data comprise a large number of categorical variables that suffer from item nonresponse. Standard methods for multiple imputation, like log-linear models or sequential regression imputation, can fail to capture complex dependencies and can be difficult to implement effectively in high dimensions. We present a fully Bayesian,…

This final report of a National Institute of Education project explores Bayesian statistical analysis as a paradigm for educational impact studies, particularly studies on the education of the disadvantaged. The position of the report is that much of what is wrong with educational research can be attributed to the use of an inappropriate model for…

Evaluation is discussed as an information-gathering process. Currently popular evaluation programs are reviewed in relation to decision making and various approaches that seem to contribute to the decision utility of evaluation (e.g. classical approaches, Bayesian approaches, adaptive designs, and model-based evaluations) are described. (Author/AL)

This study examined the appropriateness of the use of criterion referenced tests as a means of controlling an individual student's advancement to the next level of instruction or retention in the current unit in the PLATO Air Force Base Computer-Based Education project at Chanute. The study was also concerned with program evaluation, which…

Methods for predicting specific college course grades, based on small numbers of observations, were investigated. These methods use collateral information across potentially diverse institutions to obtain refined within-group parameter estimates. One method, referred to as pooled least squares with adjusted intercepts, assumes that slopes and…

Two methods of using collateral information from similar institutions to predict college freshman grade average were investigated. One central prediction model, referred to as pooled least squares with adjusted intercepts, assumes that slopes and residual variances are homogeneous across selected colleges. The second model, referred to as Bayesian…

The validity of American College Testing Program (ACT) test scores and self-reported high school grades for predicting grades in specific college freshman courses was studied. Specific course grades are typically used to place students in remedial, standard, or advanced classes. These placement decisions, in turn, have immediate implications for…