A practical approach to overcoming biases in comparing student performance in higher education

Abstract

In times of rankings and performance benchmarks, data on average marks of higher education students are very common internationally and are often used as quality indicators in practice. We discuss the principles behind the distribution of average marks of students. These principles need to be taken into account when calculating the percentile of (the average mark of) a student. An informative percentile is obtained only if the average mark is compared to a distribution of averages that have been calculated based on the same number of credit points obtained by the student. We provide an empirical example from a university in Germany, which shows that percentile information can differ considerably when based upon different samples. Our findings indicate that the approach proposed in this study may not only be the most efficient approach for ranking students to be implemented into university practice, but may also contribute to a much more objective and credible grade reporting system for student performance.

Keywords:

• Student performance
• average mark
• percentile
• ranking
• overcoming bias

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Kai Pastor graduated in Information Systems at Chemnitz University of Technology and joined the academic staff at Johannes Gutenberg University in Mainz with a research interest in meta-modeling and information systems development. Today his main activities are in the management of teaching, examinations, and academic recognition.

Dr. Thorsten Schank is a Professor of Applied Statistics and Econometrics at the Johannes Gutenberg University of Mainz. His research interests include empirical labour economics and he often works with large scale micro-level data-sets. He currently focusses on topics like the minimum wage, the gender quota, the effect of the gas price on the labour market and persistence in the social welfare system.

Dr. Klaus Wälde is a Professor of Economics at the Johannes Gutenberg University in Mainz. His publications and research interests focus on labour markets, Covid-19 and wealth distributions. He has a particular interest in linking psychological thinking and economic model building. Conceptionally, he works on dynamics of distributions joint with colleagues from mathematics.

Dr. Olga Zlatkin-Troitschanskaia has been Professor of Business and Economics Education at Johannes Gutenberg University Mainz (JGU), Germany, since 2006. She has implemented and directed numerous large-scale research projects on modeling and measuring student knowledge, skill development and learning outcomes in higher and vocational education at both national and international level.