By Leticia Perez, Cynthia McIntyre, and Frieda Reichsman As data become increasingly central to science, mathematics, and everyday decision-making, teachers need accessible ways to integrate authentic datasets into classroom instruction. Although vast public data repositories exist, locating, cleaning, and contextualizing real-world data remains a significant barrier for … [Read more...] about Data Biographies: A Tool for Integrating Real-World Data into Classrooms
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The ‘Perfect’ Regression: A Device for Demonstrating Spuriousness and Overfitting
By Joseph G. Eisenhauer Misinterpretation of regression results—particularly confusion between correlation, causation, and predictive power—remains a challenge in statistics education. This paper introduces the “perfect” regression as a pedagogical device for illustrating spurious correlation and overfitting. Using extreme cases with small samples and randomly generated … [Read more...] about The ‘Perfect’ Regression: A Device for Demonstrating Spuriousness and Overfitting
Graphing with Kids: Teaching the Superpower of Numbers and Data
By Cole Nussbaumer Knaflic Imagine a world in which numbers and data come alive to solve problems, spark curiosity, and tell captivating stories. In this world, math isn’t boring or intimidating—it’s vibrant and full of possibilities, unlocking colorful and creative ways to understand the world around us. This is the world of Daphne, the data-drawing dragon. Daphne … [Read more...] about Graphing with Kids: Teaching the Superpower of Numbers and Data
On the Pedagogy of Randomness: Effectively Teaching How Random Is Relative in High School
By Mark Louie Ramos, The Pennsylvania State University The idea that randomness is relative to the observer is a critical concept in statistical estimation and inference, but it is not typically discussed in K-12 statistics classes, nor in basic undergraduate statistics courses for nonstatistics majors. It is argued that prominently including this concept in statistical … [Read more...] about On the Pedagogy of Randomness: Effectively Teaching How Random Is Relative in High School
Integrating Data Science Practices into Informal Learning: A STEM Summer Camp Approach
By Marc T. Sager, Southern Methodist University; Saki Milton, Southern Methodist University; Candace Walkington, Southern Methodist University; and Anthony J. Petrosino, Southern Methodist University For teachers and practitioners, this paper offers a model for integrating accessible, equity-minded data science activities into informal learning programs. Readers will gain … [Read more...] about Integrating Data Science Practices into Informal Learning: A STEM Summer Camp Approach
Some Paradoxes: Puzzling or Poorly Presented?
By Mark Milanick, University of Missouri, Columbia; Isabella Wiebelt-Smith, Swarthmore College; and William Y. Jin, Swarthmore College This article explores the use of statistical paradoxes—specifically the Will Rogers Phenomenon, Simpson’s Paradox, False Positive Paradox, and the Birthday Problem—as teaching tools for middle and high school students. These paradoxes, often … [Read more...] about Some Paradoxes: Puzzling or Poorly Presented?
ASA/NCTM Joint Committee Members Share Favorite Resources, Ideas
Data-Driven Minds: Prepping Students for a Smarter Future How can teachers design data-centered classrooms to empower their students? What strategies and tools can help increase data literacy and data science in K–12 education? How do teachers bring a focus to data-centered instruction in their math classrooms? How can data science be related to music and cooking? These … [Read more...] about ASA/NCTM Joint Committee Members Share Favorite Resources, Ideas
How MAD Must We Be? A Robust Test for Identifying Meaningful Differences Using the Mean Absolute Deviation
By Jon Hasenbank and John Appiah Kubi, Grand Valley State University This article introduces a method for identifying statistically meaningful differences between two data sets using the mean absolute deviation, known as MAD and a measure of variability taught in middle school curricula under the Common Core State Standards, which parallel the recommendations of the Pre-K-12 … [Read more...] about How MAD Must We Be? A Robust Test for Identifying Meaningful Differences Using the Mean Absolute Deviation
Making Sense of Data Visualizations: A Toolkit for Supporting Student Discussions
By Emily Thrasher, Hollylynne Lee, Bruce Graham, Matthew Grossman, Gemma Mojica, NC State University 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 … [Read more...] about Making Sense of Data Visualizations: A Toolkit for Supporting Student Discussions
Encouraging Equitable Participation in Ethical Data Science Discussions
By Jordan T. Register, University of North Carolina at Charlotte This paper examines the instructional strategies and pedagogical moves designed to foster equitable engagement in an ethical data science course. This course, developed to explore the intersection of data science, ethics, and sociopolitical awareness, aims to prepare students from diverse backgrounds to become … [Read more...] about Encouraging Equitable Participation in Ethical Data Science Discussions