Online data repositories as educational resources? A learning environment covering formal and informal inferential statistics ideas in scientific inquiry

Abstract

Statistical ideas play a vital role in scientific investigations. For students enrolling in physics-related courses at university, the need to interpret data is set from the start. Analysing graphical representations of data is seen as one way to acquaint students with statistical thinking without relying on pre-knowledge about formal statistics for applying more sophisticated methods like multiple regression. We designed a learning environment, which supports students in understanding the exploratory analysis of multivariate datasets as well as the concept of multiple regression. For phase one of the learning path, we work with exploratory data analysis using the software TinkerPlots, which has several major advantages in contrast to conventional software. Only in phase two formal inferential statistics is applied. We have chosen a context-oriented approach for this learning environment, using the particulate matter concentration in an Austrian city as topic. By providing data from online data repositories in a simplified way, students get the opportunity to work with real data. The amount of this data exceeds the number of measurements collected in typical training labs in an authentic and feasible way. In this article, the design of the intervention and a range of results originating from the triggered learning paths will be presented and discussed. To sum it up, we illustrate advantages and opportunities of the use of innovative software, online data repositories and informal statistics for a first introduction of methods of formal statistics like multiple regression.