Statistics

Designing and Implementing Data Lessons in Secondary Education

Cadre-Admin — Thu, 29 Jan 2026 13:36:18 +0000

Designing and Implementing Data Lessons in Secondary Education

This study examines how secondary teachers incorporated the six-phase Data Investigation Process (Lee et al., 2022) into classroom lessons following a professional learning experience. Analysis of 13 lesson plans, interviews, and survey responses revealed that while most lessons addressed multiple phases, few supported full engagement across all six. Framing the Problem was the most consistently attended-to phase, often grounded in authentic contexts and clear investigative questions. In contrast, Explore and Visualize was less developed, frequently limited by specific learning goals constraints. Lessons that integrated technology, especially CODAP, were more likely to support deeper student exploration and reasoning. Findings underscore the need for thoughtful instructional design.

Cadre-Admin Thu, 01/29/2026 - 08:36

https://uni-muenster.sciebo.de/s/G4Czt8A6BL4oygf?dir=/&editing=false&openfile=t…

Discussing Data Visualizations: A Toolkit for Supporting Students

Cadre-Admin — Thu, 29 Jan 2026 04:03:22 +0000

Discussing Data Visualizations: A Toolkit for Supporting Students

This paper explores a comprehensive framework to develop students’ data literacy by guiding them in making sense of complex data visualizations. With the growing complexity and prevalence of data visualizations in media, it’s crucial to equip students with the skills to critically analyze and engage with these visual forms of data. This toolkit emphasizes the importance of fostering data habits of mind, rather than mere computational proficiency, and encourages students to consider what a visualization is conveying, how it was created, and why it was created.

Cadre-Admin Wed, 01/28/2026 - 23:03

https://www.statisticsteacher.org/2024/12/09/data-visualizations/

Thinking Through the Data Investigation Process

Cadre-Admin — Thu, 29 Jan 2026 03:57:06 +0000

Thinking Through the Data Investigation Process

In this document, we identify key considerations to guide thinking and actions for data investigations, where the goal of an investigation is to answer a statistical question within a context to communicate approaches and solutions to a problem based on evidence. This process is composed of six phases: Frame the Problem, Consider and Gather Data, Process Data, Explore & Visualize Data, Consider Models, and Communicate & Propose Action.

Cadre-Admin Wed, 01/28/2026 - 22:57

https://cdn.instepwithdata.org/ThinkingDataInvestigationProcess.pdf

The Data Investigation Process Classroom Poster

Cadre-Admin — Wed, 28 Jan 2026 20:28:39 +0000

The Data Investigation Process Classroom Poster

When assisting students in a data investigation, it can be useful to help them develop key ways of thinking and dispositions that are helpful in developing expertise in conducting data investigations like a statistician or data scientist. It can be useful for students to see a reminder of this process and key considerations. This poster version of the Data Investigation Process that can be used in your classroom for this purpose.

Cadre-Admin Wed, 01/28/2026 - 15:28

https://cdn.instepwithdata.org/DataInvestigationProcessPoster.pdf

The Data Investigation Process

Cadre-Admin — Wed, 28 Jan 2026 20:03:40 +0000

The Data Investigation Process

Today, the ability to make sense of data is essential. K-12 students need educational experiences that can assist them in developing data literacy for global citizenry, and career and college pathways related to statistics and data science (e.g., Engel, 2017; Gould, 2017). Statistics and practices with data are included in standards and goals across the K-12 curriculum. Science puts a heavy emphasis on reasoning from and with data to understand scientific phenomena. English and Social Studies include ensuring data and appropriate visualizations are used to support arguments as well as to understand historical trends, and often inequities, in social structures of our world. Mathematics curricula emphasize measurement data and graphic displays in elementary grades and a strong focus on statistics and probability from grades 6-12. Throughout K-12, students should develop a practice of using data in investigations of real-world phenomena through processes that will prepare them to be data-literate citizens and open doors for data-intensive career pathways in sciences, technology, engineering, journalism, medicine, sports analytics, business, mathematics, statistics, and data science.

Cadre-Admin Wed, 01/28/2026 - 15:03

https://cdn.instepwithdata.org/DataInvestigationProcess.pdf

Data Investigation Processes: Connected, Iterative, and Cyclic

Cadre-Admin — Wed, 28 Jan 2026 19:52:05 +0000

Data Investigation Processes: Connected, Iterative, and Cyclic

Developing the ability to do data science and make sense of the data science work done by others involves building skills and knowledge that span across all phases of a data life cycle and draw on many subject areas. Science tends to put a heavy emphasis on reasoning from and with data to understand scientific phenomena. English and Social Studies incorporate the use of data and data visualizations as evidence to support arguments, interpret information, and evaluate claims in social structures of our world. Mathematics has emphasized working with measurement data, graphical representations, and developing statistical and probabilistic reasoning. Throughout K-12, students should develop a practice of using data in investigations of real-world phenomena through processes that will prepare them to be data-literate citizens and open doors for data-intensive career pathways in sciences, technology, engineering, journalism, medicine, sports analytics, business, data science, and so many more.

Cadre-Admin Wed, 01/28/2026 - 14:52

https://www.datascience4everyone.org/post/data-investigation-processes-connecte…

Designing Online Professional Learning to Support Advances in Teaching Strategies in Statistics and Data Science

Cadre-Admin — Wed, 28 Jan 2026 19:42:53 +0000

Designing Online Professional Learning to Support Advances in Teaching Strategies in Statistics and Data Science

This paper describes the design of an innovative online platform that has over 50 hours of learning experiences to support educators in further advancing their understandings and pedagogical skills in teaching statistics and data science to learners age 11-18+. Two frameworks are described that support effective classroom practices: a Data Investigation Process and Seven Dimensions of Teaching Statistics and Data Science. Examples of features and interface designs are included to illustrate how the frameworks work together to support teachers' learning in a cohesive way, even as they personalize their experience and engage in different learning pathways.

Cadre-Admin Wed, 01/28/2026 - 14:42

https://uni-muenster.sciebo.de/s/Dt99KYP89NFSxoa?dir=/&editing=false&openfile=t…

Seeing Our World Through Data: Sixth Graders Integrating Data Investigations in Collaborative Knowledge Building

Cadre-Admin — Tue, 29 Jul 2025 20:14:14 +0000

Seeing Our World Through Data: Sixth Graders Integrating Data Investigations in Collaborative Knowledge Building

Data science, as a multidisciplinary field, has gained considerable interest in K-12 education. Prior research has explored innovative ways to introduce data science to young learners, emphasizing not only the development of data skills but also the connection of data science to students’ authentic inquiries and critical actions. Building on this foundation, this study aims to achieve two complementary goals: integrating Knowledge Building, a well-established pedagogical approach, into K-12 data science education, and enhancing students’ epistemic agency through data practices in knowledge building. To achieve these goals, we engaged a class of 6th-grade students in building knowledge about global issues, supporting their exploration of public datasets related to these topics. Following the Knowledge Building framework, students collaborated to construct explanatory theories, analyzing public datasets to inform and refine their theoretical understandings. Findings revealed that, with appropriate pedagogical and technological supports, 6th-grade students were able to engage in a range of data practices when working with public datasets, derive meaningful interpretations of data visualizations, and contribute to theory-building discussions informed by their data investigations. This study highlights the potential of situating data science within students’ interdisciplinary engagement with authentic problems and demonstrates how supporting data practices can enhance their knowledge-building processes.

Chen, B., Ma, L., & Leung, V. Y. (2025). Seeing our world through data: Sixth graders integrating data investigations in collaborative knowledge building. Journal of Statistics and Data Science Education, 1–15. https://doi.org/10.1080/26939169.2025.2505431

Cadre-Admin Tue, 07/29/2025 - 16:14

https://www.tandfonline.com/doi/full/10.1080/26939169.2025.2505431

The Design and Implementation of a Bayesian Data Analysis Lesson for Pre-Service Mathematics and Science Teachers

Cadre-Admin — Sun, 29 Jun 2025 17:32:29 +0000

The Design and Implementation of a Bayesian Data Analysis Lesson for Pre-Service Mathematics and Science Teachers

With the rise of the popularity of Bayesian methods and accessible computer software, teaching and learning about Bayesian methods are expanding. However, most educational opportunities are geared toward statistics and data science students and are less available in the broader STEM fields. In addition, there are fewer opportunities at the K-12 level. With the indirect aim of introducing Bayesian methods at the K-12 level, we have developed a Bayesian data analysis activity and implemented it with 35 mathematics and science pre-service teachers. In this article, we describe the activity, the web app supporting the activity, and pre-service teachers’ perceptions of the activity. Lastly, we discuss future directions for preparing K-12 teachers in teaching and learning about Bayesian methods.

Dogucu, M., Kazak, S., & Rosenberg, J. M. (2024). The design and implementation of a Bayesian data analysis lesson for pre-service mathematics and science teachers. Journal of Statistics and Data Science Education, 33(2), 177–188. https://doi.org/10.1080/26939169.2024.2362148

Cadre-Admin Sun, 06/29/2025 - 13:32

https://www.tandfonline.com/doi/full/10.1080/26939169.2024.2362148

Teacher Cultivation of Classroom Statistical Modeling Practice: A Case Study

Cadre-Admin — Mon, 25 Nov 2024 21:25:18 +0000

Teacher Cultivation of Classroom Statistical Modeling Practice: A Case Study

This report characterizes forms of dialogic support that a sixth-grade teacher generated during whole-class and small-group conversations to help students develop a practice of statistical modeling. During four weeks of instruction, students constructed and revised models to account for variability and uncertainty across a variety of random processes, many of which they experienced first-hand. Data sources for the research included field notes and video recordings of classroom conversations involving the teacher. Analyses identified and characterized teacher assistance during classroom episodes in which the teacher fostered the emergence and development of fundamental aspects of statistical modeling practice. These aspects included a) establishing mappings between models of chance and the situations or processes being modeled, b) imagining outcomes as constituents of a long-run random process, c) evaluating model fit, and d) making model-based inferences. Throughout instruction, the teacher systematically helped students coordinate these distinctive aspects of modeling practice. The findings suggest how teacher practices can promote the sustained development of statistical reasoning as a dialogue between data and model, and more generally, how teacher assistance attuned to student thinking about aspects of a disciplinary practice can foster a student-centered phenomenology of that practice.

Wisittanawat, P. (Fai), & Lehrer, R. (2024). Teacher cultivation of classroom statistical modeling practice: A case study. Cognition and Instruction, 42(4), 505–547. https://doi.org/10.1080/07370008.2024.2397969

Cadre-Admin Mon, 11/25/2024 - 16:25

https://www.tandfonline.com/doi/full/10.1080/07370008.2024.2397969