Literature Index

In this report we present the results of an international research study on the training of researchers in mathematics education. The study was carried out by some members of The International Study Group on Theory of Mathematics Education.<br><br>The research consisted of developing a questionnaire which was mailed to numerous institutions all over the world, and the anlaysis of the answers which were received.<br><br>The main objective of the study was to collect international data about the training of researchers in mathematics education and to establish an information network about graduate programs in the field.<br><br>A total of about 150 questionnaires were sent out and 78 answers received. Fifteen of these answers came from universities that wish to participate in the network but which do not at present have a program.

The baby boom dataset contains the time of birth, sex, and birth weight for 44 babies born in one 24-hour period at a hospital in Brisbane, Australia. The data can be used to demonstrate that some common distributions -- the normal, binomial, geometric, Poisson, and exponential -- can be used to model real situations. Because the dataset is small and easily understood, it provides a useful classroom example for discussing these distributions.

The simplest forms of regression and correlation involve formulas that are incomprehensible to many beginning students. The application of these techniques is also often misunderstood. The simplest and most useful description of the techniques involves the use of standardized variables, the root mean square operation, and certain distance measures between points and lines. On the standardized scale, the simple linear regression coefficient equals the correlation coefficient, and the distinction between fitting a line to points and choosing a line for prediction is made transparent. The typical size of prediction errors is estimated in a natural way by summarizing the actual prediction errors incurred in the dataset by use of the regression line for prediction. The connection between correlation and distance is simplified. Despite their intuitive appeal, few textbooks make use of these simplifications in introducing correlation and regression.

During the Spring of 1995 a statistical experiment to assess the effects of two methods of teaching introduction to Computer programming concepts was developed. The experiment implemented two teaching approaches: traditional lecture vs. laboratory (tehcnology). Several performance measures were defined and then collected throughout the course, to assess student learning. Among them are: results from common tests, quizzes, and homework/projects. In this article we assess the effects of these two teaching approaches on students' learning, retention, and success rates. We analyze statistically the data collected, testing several hypotheses based on our teaching experience. Finally, we give several conclusions drawn on the analyses results.