Student Performance in Introductory Accounting: A Multi-Sample, Multi-Model Analysis

Abstract

Using prior literature as a starting point, three predictive models are developed to explain the variation in student performance in the first college accounting course. The use of multiple samples provides the opportunity to validate certain measures and to examine the stability of predictive models over time in the same academic institution. The use of multiple models contributes to our understanding of the potential for model misspecification in this line of research. The study includes an examination of the structure of student attitudes toward accounting and need for achievement through the use of exploratory and confirmatory factor analysis. The study evaluates the unique contribution of attitudes toward accounting and need for achievement to course performance. Bivariate correlations and three regression models are used to evaluate eight hypotheses about student characteristics and their association with course grades. Other student characteristics tested include intention to major in accounting, prior accounting education, hours of outside work at a job, academic aptitude, and overall college academic performance. Finally, the incremental contribution of gender on each of the models is analyzed. Results indicate that student attitudes toward accounting and need for achievement, plus several other characteristics, have only moderate explanatory power for course performance. Consistent with prior literature, college academic performance and academic aptitude are found to be the most prominent characteristics for explaining student performance in the first accounting course. Gender makes virtually no incremental contribution to the explanation of student performance. Teaching and research implications are discussed.