This paper contributes to a growing body of research on the increasing datafication of schooling, which has become a salient topic in comparative education and education policy research. Specifically, we address the rising scholarly concern about the meaning of (comparing) contexts as bounded localities facing an increasingly fluid and generative…

Over the course of 18 months, teams at the University of Chicago and Stanford University joined with other leaders across the United States and world to consider the issue of the types of mathematics used in the classroom. It quickly became clear that all students--starting from the youngest in prekindergarten to those in college--need to learn…

The need for geoscience students to develop a quantitative skillset is ever increasing. However, this can be difficult to implement in university-style lecture courses in a way that is both manageable for the instructor and does not involve lengthy, potentially repetitive, question sheets for the students. Here, a method for teaching dimensional…

Background: Dataset skills are used in STEM fields from astronomy to zoology. Few fields explicitly teach students the skills to analyze datasets, and yet the increasing push for authentic science implies these skills should be taught. Purpose: The overarching motivation of this work is to understand authentic science learning of STEM dataset…

Scientific computing and computer literacy are increasingly important skills for chemistry students to learn, but despite this need, there is an absence of chemistry-specific texts available for teaching the subject. This article introduces a freely available textbook released under a Creative Commons license for use in an undergraduate scientific…

Narrow reading has the potential to reduce vocabulary load and to provide rich opportunities for developing collocation knowledge, but these benefits rely on narrow reading increasing lexical repetition within a text. Hence, interest in narrow reading has been limited by the relatively small lexical effect of narrowing reading by topic (Nation,…

Statistical modeling continues to gain prominence in the secondary curriculum, and recent recommendations to emphasize data science and computational thinking may soon position algorithmic models into the school curriculum. Many teachers' preparation for and experiences teaching statistical modeling have focused on probabilistic models.…

Kaggle is a data modeling competition service, where participants compete to build a model with lower predictive error than other participants. Several years ago they released a simplified service that is ideal for instructors to run competitions in a classroom setting. This article describes the results of an experiment to determine if…

In the past 10 years, new data science courses and programs have proliferated at the collegiate level. As faculty and administrators enter the race to provide data science training and attract new students, the road map for teaching data science remains elusive. In 2019, 69 college and university faculty teaching data science courses and…

This technical brief is part of an ongoing series the Center for Learner Equity (CLE) launched in 2015 that examines the enrollment and experiences of students with disabilities in different school settings. Using the 2017-2018 Civil Rights Data Collection (CRDC) data released earlier this year, this brief focuses on the number and percentages of…

Early childhood is a crucial stage in a child's life, and aspects of the environment in the physical, social-emotional, cognitive, and health and safety domains all play important roles in shaping children's development during these early years. Having a valid and reliable measure of the quality of these aspects of children's care settings is…

As information literacy and data-driven program evaluations have become growing obsessions within academic institutions, how might liberal arts and humanities programmes engage students in both critical and creative explorations of contemporary human-data relations? Inspired by the variety of metaphors that currently shape human-data relations and…

Longitudinal data analysis has received widespread interest throughout educational, behavioral, and social science research, with latent growth curve modeling currently being one of the most popular methods of analysis. Despite the popularity of latent growth curve modeling, limited attention has been directed toward understanding the issues of…

The timing of events (e.g., how long it takes a child to exhibit a particular behavior) is often of interest in developmental science. Multilevel survival analysis (MSA) is useful for examining behavioral timing in observational studies (i.e., video recordings) of children's behavior. We illustrate how MSA can be used to answer 2 types of research…

Each year, policymakers, educators, and the general public engage in debates around the statewide average teacher pay figure that the North Carolina Department of Public Instruction (DPI) publishes on its website and reports to the National Education Association. These debates take up the important consideration of whether or not teachers are…