Literature Index

This chapter considers the assessment of probabilistic thinking and reasoning via informal monitoring as well as through formal tasks. Such assessment are considered in the context of the purposes of, and frameworks for, assessment. Specific tasks are examined as to whether they assess thinking and reasoning. Suggestions on improvement to the quality of the assessment instruments are made in light of research studies on the understanding of probability concepts. Alternative assessment strategies are suggested.

Conditional probability and Bayesian reasoning are important to psychology students because they are involved in the understanding of classical and Bayesian inference, regression and correlation, linear models, multivariate analysis and other statistical procedures that are often used in psychological research. A study of previous literature showed that there is considerable research on this topic, but no comprehensive questionnaires have been developed to globally assess students' understanding and misconceptions on these topics. At the University of Granada we started building a questionnaire, which takes into account the content of conditional probability taught in the Spanish universities to psychology students, as well as the biases and misconceptions described in the literature. In this work we will describe the process of developing the questionnaire and will report the results from a sample of 206 psychology students.

This chapter describes various methods for assessing statistical knowledge, understanding and skills. It covers traditional written forms of assessment, multiple-choice vs. open-ended questions, essays, practical work and projects, and oral assessments. It also discusses issues pertaining to the monitoring of on-going progress, groups that may be disadvantaged as the result of particular assessment methods, experiences of changing assessment methods, and the assessment of teachers.

In this paper we report the results from a major UK government-funded project, started in 2005, to review statistics within the school mathematics curriculum for students up to age 16. New teaching materials that explicitly use a problem-solving approach through other subjects have been developed. We will report extensive trialling of these, the development of corresponding new assessment regimes and how these work in the classroom. The new ways of assessing are particularly poignant since, in September 2006, the UK government announced that coursework is to be dropped for mathematics exams sat by 16-year-old. As a consequence, areas of the curriculum previously assessed by coursework, are now being ignored. We will provide some new and useful ways of assessing this content. Our findings have implications for teaching, learning and assessing statistics for students of the subject at all ages.