Literature Index

Explores the need to teach undergraduate sociology majors about statistical methods. Identifies student based obstacles to the learning of statistics. Offers an instructional model that includes (1) warm up sessions; (2) organizational models; (3) application exercises; (4) pattern recognition; and (5) sociological meaning. Recommends the model as a basic design for the introductory statistics course.

This study attempts to identify the relevant mental model for hypothesis testing. Analysis of textbooks provided the identification of the declarative and procedural knowledge that constitute the relevant mental models in hypothesis testing. A cognitive task analysis of intermediates' and experts' mental models was conducted in order to identify the relevant mental models for teaching novices. Of interest were the steps taken to arrive at the solution and the representations that were used in the problem solving process. Results indicate that experts and intermediates differ in their conceptual understanding. In addition, diagrammatic problem representation was useful in for all particularly for the intermediates. On this basis, the intermediate models were deemed relevant for instructing novices. Two instructional strategies were investigated: presentation sequence (concepts and procedures taught separately or together) and presentation mode (diagrammatic vs. descriptive). Based on their findings, the researchers conclude that meaningful learning occurs when conceptual instruction is provided prior to the procedures, that is, when they are taught separately rather than concurrently, and when a diagrammatic strategy was utilized rather than a descriptive method. This facilitates development of representational ability for understanding hypothesis testing. In short, using separate and diagrammatic representation strategies are effective for teaching novices in the area of hypothesis testing. The researchers conclude that by developing relevant mental models through this type of instruction, the learner's knowledge can be more accessible (awareness of knowledge), functional (predict or explain), and improvable.

This paper will document four instruments devised to assess student understanding of statistical concepts. Two are intended for large scale administration and two are for individual interviews.

Students in graduate-level applied statistical courses should be trained to manipulate realistic data bases which are sufficiently large and complex that they provide verisimilitude with respect to thesis studies and other real-world applications. At the University of Maryland, we have been integrating data base manipulation into our intermediate-level statistics instruction for several years. This presentation concentrates on several issues related to the use of data bases in statistical instruction: appropriate course level; desirable characteristics of data bases; the role of mainframe and microcomputer statistical software; integration of data base manipulation skills into instruction on statistical topics; and grading practices.