The purpose of this paper is to present a cognltively-based and empirically-derived approach for the design of the RadTutor, a prototype computerized tutor to train radiology residents in diagnosing mammograms exhibiting breast diseases. A multitude of computer-based radiology training environments have recently been developed with the objective of supporting the acquisition of radiological expertise. In general, however, these systems have failed in several aspects including a failure to incorporate theoretical perspectives and empirical findings to the design of these systems. This paper outlines the conceptual framework for the development of the prototype which includes; (1) a discussion of the objectives and goals of the radiology residency training program, (2) a review and critique of existing computer-based radiology training environments, (3) a synthesis of an expert-novice study aimed at attaining a cognitive model of problem solving in mammogram interpretation (Azevedo, 1997), (4) a description of the results of analyses of authentic radiology resident teaching rounds, and (5) deriving instructional principles for the design of the mammography tutor.

This paper implements recent proposals for enhancing the learning of mathematics by developing statistics instruction and assessment for eighth grade students that c^italizes on the use of exemplars. The goal of instruction was for small groups to learn about statistics by engaging in hands-on activities as well as to ^ply their knowledge and skills by creating statistics projects tfiat involved designing, conducting, and presenting a mini-experimeni. Performance criteria which reflected the statistical concepts taught in the instruction were explained to students to ensure their understanding of the task (i.e., project). Groups were assigned to two treatments-exemplars and nonexemplars?Av'hich differed in the degree to which criteria modeled the processes of hypothesis generation, data collection, data analysis, and graphic representation. The effectiveness of elaborating on criteria through examples and text (i.e., exemplars) or just text (i.e., nonexemplars) for enhancing learning was examined. Both treatments demonstrated significant performance gains from pretest to posttest. However, students' understanding of representative sampling was significantly better as a result of receiving the exemplars treatment than the nonexemplars treatment. Making criteria more elaborate through examples of performance can thus enhance students' understanding of more abstfact statistical concepts such as sampling.

This symposium reports research concerned with developing tools and models for the analysis of cognitive processes in interactive learning situations. Results of several studies of natural, interactive task-oriented learning situations including face-to-face learning situations and learning over a network are compared. The results show how interactive, situated discourse is used to support processes of knowledge construction and problem solving within these learning environments.