Abstract

How students plan and conduct experimental inquiry has been a major focus in science education research. However, experimental inquiry is not representative for all scientific investigations. So, a focus on experimental inquiry can cause the impression that there is a “single scientific method”. We are currently developing learning environments that focus on another type of inquiry using environmental data from an online data repository. We call this scientific investigation by data exploration. Due to the increased variability in environmental data, ideas of inferential statistics are of extreme importance because causal relationships cannot be directly derived. Hence, the focus of our learning environment is to support students’ skills which are relevant for performing scientific investigations by data exploration. The main goal during the intervention for the students is to identify factors influencing the particulate matter concentration in an Austrian city. In this article, we report the evaluation of our intervention with a cohort of 27 secondary school students. The evaluation shows that students regard particulate matter as a highly interesting. Furthermore, students self-report a high intrinsic motivation during the intervention and feel more informed about the environmental issue of particulate matter after the intervention. However, a few starting points for further improvement of the learning environment were identified and are discussed in this article.

Highlights

  • Interpreting and drawing inferences from data plays a crucial role in today’s everyday life

  • Several studies have shown that students frequently struggle with skills related to the interpretation and usage of statistical information [5], reasoning based on empirical evidence [6], approaches to statistical investigations [7], understanding of variability in data [8,9,10] and extracting important information from graphical representations [11, 12]

  • We describe the learning environment as it has been used with 36 secondary school students from Austria

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Summary

Introduction

Interpreting and drawing inferences from data plays a crucial role in today’s everyday life. In the context of science education, we developed a learning environment using environmental data from an online data repository which is supposed to support secondary school students’ skills in the afore mentioned aspects. In our approach we do situate the learning in a certain context, but the students are actors in a given scenario During the intervention, they take the role of experts in the “department for air monitoring” of the municipal government and their goal is to identify and reason about factors which influence the particulate matter concentration in their city [13]. There is a need to facilitate students’ ability to interpret empirical data without the use of formal inferential statistics For this purpose, we introduce the concept of scientific investigations by data exploration using already given datasets. Informal statistical inference or informal inferential reasoning has received increased attention [15] when it comes to interpreting empirical data in a meaningful way

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