SLS - Sustainable Learning of Statistics

Background

Higher education systems all over the world increasingly emphasise the importance of high-quality learning that can be used in real life and work contexts. When discussing the issue of quality of learning, two intertwined challenges arise. The first is that people frequently forget what they have learned and their learning appears to evaporate. The second challenge is that people learn but cannot apply their knowledge except in the context where they learned it. They have trouble using it in new situations. Successfully overcoming these two challenges is the mark of high-quality learning—that is, learning that enables students to deal with novel situations in powerful ways now and in the future. We call such learning ‘sustainable learning’, which refers to the general meaning of sustainability: the propensity of something to continue and grow over time.

Our concern in this project is the learning of statistics: the science of learning from data and the science that is measuring, controlling and communicating uncertainty. In today’s data-rich world, statistics has become one of the most central topics of study. It is found in most disciplines, and almost all post-graduates programmes provide courses handling quantitative data. We want to study how post-graduates’ students learn about statistical aspects of the world around them affects their sustainable learning of statistics.

Purpose and aims

The purpose of this project is to investigate how sustainable learning in the domain of statistics can be enhanced, particularly statistics taught in postgraduate research methods courses. We use the variation theory (VT) of learning (Marton, 2015) to pursue the following aims:

1. To provide a theoretical and practical case for how sustainable learning in the domain of Statistics can be enhanced; and
2. To test the conjectures of the VT of learning and contribute to its theoretical development.

We investigate the assumption that teaching statistics - when the necessary conditions for powerful learning are met - will increase the potential for sustainable learning. Such necessary conditions are those that allow learners to experience necessary patterns of variation and invariance in critical aspects of the object of learning, which is the competence of being able to use statistical skills in new contexts now and in the future.

Significance

The significance of this project can be summarised in five points:

1. VT has so far been mainly used to study the relationship between learning and teaching from the point of view of teaching; in this project, the same relationship will be studied but from the point of view of learning. Thus, we hope that the findings of this project will have as much to tell students, as VT has been able to tell teachers.
2. This project deals with a complex object of learning which aims to empower students to use statistical experien­ces in new contexts and settings, now and in the future. Thus, the findings of this project should have even more to tell teachers than VT has been able to tell them so far.
3. Our aim is not just to improve the learning of core statistical concepts but to see how students use such learning in the context of statistical problem solving and novel situations. Therefore, this project will be significant for statistics education research.
4. Most of the previous studies inspired by VT were in the contexts of primary or secondary school level. Investigating VT conjectures in a new discipline and new level (higher education) should widen the sphere of VT.
5. Facing and overcoming the challenge of bridging the two different contexts (VT and variation in statistics) should widen our understanding of students’ learning both within the theory and within statistics education.