Assessment of tertiary students’ learning of statistical modelling

Abstract

In this paper, we report on the learning of statistical modelling in a second-year statistics module through the assessment of a problem that required a Monte Carlo simulation. On the forefront of the 4th industrial revolution is science, technology, engineering and mathematics subjects, where mathematical statistics plays a key role in topics such as machine learning and predictive analysis. Students often find statistical modelling difficult, where obstructions in the modelling process could lead towards a dead-end. For this reason, assessment of learning, for learning and as learning in statistics education seems necessary. General pillars of good assessment practice is considered in this study, as well as guidelines for the development of students’ conceptual understanding of the content, such as, statistical reasoning, statistical thinking and statistical literacy. Therefore, this study was conducted to provide educators with information of student achievement of desired student learning outcomes. Based on an analysis of the reports collected individually and through voluntary group work, descriptive statistics are presented. These results are discussed in relation with assessment measures and provides a basis for teaching and learning statistics.