A model of the relationships among measures of affect, aptitude, and performance in introductory statistics

This study investigated a number of variables believed to influence the achievement of first-year undergraduate university students enrolled in an introductory statistics course. A sample of 166 participants completed a self-report inventory consisting of affective measures such as attitude toward learning statistics, motivational intensity, and anxiety experienced in their statistics course. In addition to measures of achievement in the course, we obtained measures of performance in previous mathematics and psychology university courses. We tested two structural equation models relating achievement in the course to variables in the inventory. The general structure of the models was based on Gardner's socio-educational model of second-language learning (1985). The results support the hypotheses that both motivation and aptitude contribute to the prediction of achievement in statistics as suggested by Lalonde and Gardner (1993). Furthermore, we found support for a direct link between anxiety and achievement in statistics.