Big data, big changes? The technologies and sources of data used in science classrooms

Abstract

With improving technology and monitoring efforts, the availability of scientific data is rapidly expanding. The tools that scientists and engineers use to analyse data are changing in response. At the same time, science education standards have shifted to emphasize the importance of students making sense of data in science classrooms. However, it is not yet known whether these exciting new datasets and tools are used science classrooms, and what it would take to facilitate their use. To identify opportunities, research is needed to capture the data practices currently performed in classrooms, and the roles of technology for student learning. Here, we report findings from a survey conducted in the United States of 330 science teachers on the data sources, practices and technologies common to their classroom. We found that teachers predominantly involve their students in analysing relatively small data sets that they collect. In support of this work, teachers tend to use the technologies that are available to them—namely, calculators and spreadsheets. In addition, we found that a subset of teachers used a wide variety of data sources of varying complexity. We discuss what these findings suggest for practice, research and policy, with an emphasis on supporting teachers based on their needs. Practitioner notes What is already known about this topic Collecting and analysing data are central to the practice of science, and these skills are taught in many science classrooms at the pre‐collegiate (grades K‐12) level. Data are increasingly important in society and STEM, and types and sources of data are rapidly expanding. These changes have implications for science teachers and students. What this paper adds We found that the predominant data source science teachers use is student‐collected, small data sets. Teachers use digital tools familiar and available to them: spreadsheets and calculators. Teachers perceive the cost and time it would take to learn to use digital tools to analyse data with their students as key barriers to adopting new tools. Despite the predominance of small, student‐collected data analysed using spreadsheets or calculators, we also found notable variability in the data sources and digital tools some teachers used with their students. Implications for practice and/or policy Many of the changes called for in science education standards and reform documents, regarding how students should collect and analyse data, have not yet been fully realized in pre‐collegiate classrooms. Science teacher educators and science education researchers should build curricula and develop digital tools based on which kinds of data sources and digital tools teachers presently use, while encouraging more complex data useage in the future.

High school biology teachers’ integration of computational thinking into data practices to support student investigations

“…When teachers did identify automation in lesson plans, they primarily incorporated it using spreadsheets to visualize data, similar to the findings of Rosenberg et al (2022). For example, the biology teachers frequently used spreadsheets in their lessons to help students create graphs (visualize) in order to look for trends.…”

“…Over time and repeated engagement, students may be able to distinguish how the phenomena they are studying relate to data representations (Laina & Wilkerson, 2016). Rosenberg et al (2022) noted that although teachers often use digital tools such as calculators and spreadsheets for students to analyze and make representations, there are more tools that can be used in classrooms to promote more sophisticated data analysis. Given how students can benefit from the use of certain aspects of data practices such as pattern recognition, there are opportunities to support student data practices with computational thinking.…”

Data science education across the disciplines: Underexamined opportunities for K‐12 innovation

“…Data collection and analysis are common practices in science classrooms. Rosenberg et al (2022) conducted a study to explore the data sources and tools that K-12 science teachers used in their classrooms. In terms of tools (and technologies), the study showed that teachers mainly chose to use general tools, namely Google Sheets and calculators.…”

Editorial: “Digital tools, innovation and competitiveness: lessons for the digital transition”

“…The global shock caused by COVID-19 created many challenges and risks for countries and regions. Digital tools showed their potential to provide innovations solutions for the unexpected turbulences caused by the pandemic, from digital tools for education (Mahmud et al , 2022; Rosenberg et al , 2022; Weilage and Stumpfegger, 2022; Yu, 2022) and innovative tools for the management of global value chains (Butollo et al , 2022; Cusumano et al , 2019; De Propris and Pegoraro, 2019; European Commission, 2023a; Yeung, 2021), to artificial intelligence (AI) and internet of things (IoT) for the health care (Ienca and Vayena, 2020; Lytras et al , 2009; Ordóñez de Pablos et al , 2022; Pretorius and Coyle, 2021; Zhang et al , 2015), for example. The transition toward a digital and green economy brings new challenges but also opportunities for the creation of jobs and boost competitiveness.…”