The statistical problem-solving process is key to the statistics curriculum at the school level, post-secondary, and in statistical practice. The process has four main components: formulate questions, collect data, analyze data, and interpret results. The Pre-K-12 Guidelines for Assessment and Instruction in Statistics Education (GAISE) emphasizes…

Being able to understand, interpret, and critically evaluate data is necessary for all individuals in our society. Using the PreK-12 Guidelines for Assessment and Instruction in Statistics Education-II (GAISE-II; Bargagliotti et al., 2020) curriculum framework, the current paper outlines five evidence-based recommendations that teachers can use to…

Introducing kindergarten children to the engineering design process (EDP) is an important objective of early STEM education. Studies indicate that children often miss the crucial steps of testing and optimising during the EDP and do not persist in making solutions better. The present study explores how children's goal awareness, self-evaluation…

This article explores 6th-grade students' modelling with data in generating models for selecting an Australian swimming team for the (then) forthcoming 2016 Olympics, using data on swimmers' times at various previous events. We propose a modelling framework comprising four components: working in shared problem spaces between mathematics and…

This paper presents "the DataBuzz Project." "DataBuzz" is a high-tech, mobile educational lab, which is housed in a 13-meter electric bus. Its specific goal is to increase the data literacy of different segments of society in the Brussels region through inclusive and participatory games and workshops. In this paper, we will…

The development of a student's ability to make data-driven decisions has become a focus in higher education (Schield 1999; Stephenson and Caravello 2007). Data literacy, the ability to understand and use data to effectively inform decisions, is a fundamental component of information competence (Mandinach and Gummer 2013; Stephenson and Caravello,…

Data are becoming increasingly important in science and society, and thus data literacy is a vital asset to students as they prepare for careers in and outside science, technology, engineering, and mathematics and go on to lead productive lives. In this paper, we discuss why the strongest learning experiences surrounding data literacy may arise…

There is much agreement among chemical education researchers that expertise in chemistry depends in part on the ability to coordinate understanding of phenomena on three levels: macroscopic (observable), sub-microscopic (atoms, molecules, and ions) and symbolic (chemical equations, graphs, etc.). We hypothesize this "level-coordination…

Many students enter high school with some science knowledge and experience doing investigations but often know little about the nature of science (NOS) or how the knowledge is developed (i.e., science practices). As science teachers, we need to get students excited about science as quickly as possible with activities that introduce the practices…

A process for analyzing log files collected from open-ended learning environments is developed and tested on a virtual lab problem involving reaction stoichiometry. The process utilizes a set of visualization tools that, by grouping student actions in a hierarchical manner, helps experts make sense of the linear list of student actions recorded in…

Background: Historically, significant advances in scientific understanding have followed advances in measurement and observation. As the resolving power of an instrument increased, so have gains in the understanding of the phenomena being observed. Modern interactive systems are potentially the new "microscopes" when they are…

In the face of multicollinearity, researchers face challenges interpreting canonical correlation analysis (CCA) results. Although standardized function and structure coefficients provide insight into the canonical variates produced, they fall short when researchers want to fully report canonical effects. This article revisits the interpretation of…

The purpose of this study was to analyze how school psychologists engaged in problem analysis during problem-solving consultation. Five aspects of the problem analysis process were examined: 1) the types of questions participants asked during problem identification, 2) the types of data participants requested, 3) the frequency of requests for each…

Data literacy is recognized as a critically important skill in today's society, but thinking with and about data is often ignored in K-12 curricula. The Thinking With Data (TWD) project advocates that data literacy is a skill that should be addressed in an interdisciplinary manner. This article provides an overview of the TWD curriculum for middle…

Presents an instructional framework for real-world, problem-based studies that can be used in a variety of settings. Discusses background knowledge, problem exposition, data collection and analysis, data synthesis and solution presentation, and career information. (JRH)