The goal of this work is to provide instructors with detailed information about their classes at each assignment during the term. The information is both on an individual level and at the aggregate level. We used the large number of grades, which are available online these days, along with data-mining techniques to build our models. This enabled…

An approach to simultaneous optimization of assignments of subjects to treatments followed by an end-of-mastery test is presented using the framework of Bayesian decision theory. Focus is on demonstrating how rules for the simultaneous optimization of sequences of decisions can be found. The main advantages of the simultaneous approach, compared…

A decision-theoretic procedure is outlined which provides a framework within which Bayesian statistical methods can be employed with criterion-referenced tests to improve the quality of decision making in objectives based instructional programs. (Author/DEP)

The theoretical rationales and procedures of five adaptive computer-based instruction models were reviewed: the mathematical model, the regression model, the Bayesian probabilistic model, the testing and branching model, and artificially intelligent instructional systems. Each model is assessed for contrast of methods and forms, identifiable…

Computer-based adaptive instructional strategies for concept learning were investigated. Selection of the number of examples according to on-task information was more efficient than pretask or pretask plus on-task information. A response-sensitive strategy was preferable to a response-insensitive strategy to determine the presentation order of…