Written with faculty in mind, "Assessment by Design" is a practical resource that will also be useful to student affairs staff and administrators dedicated to using assessment to improve learning in curricular and co-curricular settings. This book presents the Cycle of Assessment as a framework that supports assessment in service of…

Building a better data culture can be the path to better results and greater equity in schools. But what do we mean by data? Your students are not just statistics. They aren't simply a set of numbers or faceless dots on a proficiency scale. They are vibrant collections of experiences, thoughts, perspectives, emotions, wants, and dreams. And taken…

While there are many different types of education data, policymakers and education leaders often place heavy emphasis on data from large-scale quantitative measures, such as annual state assessments. But data from these sources alone do not provide a complete picture of learning and are often not well suited to informing improvements at the local…

Adaptive teachers use student data to guide instruction. Learn about using an anecdotal record form to support adaptive teaching. In this article, the authors describe how teachers can use learning trajectories to make adaptive decisions to meet the needs of their students. They provide an example using the U .S. Math Recovery Council's learning…

The authors provide novice teachers with a step-by-step introduction to linguistic analysis, a tool to identify gaps between English learners' proficiency levels and the language demands of their coursework in the content areas.

Education can be transformed if we eradicate our fixation on big data like standardized test scores as the supreme measure of equity and learning. Instead of the focus being on "fixing" and "filling" academic gaps, we must envision and rebuild the system from the "student" up--with classrooms, schools and systems…

The process of analyzing student data to determine an appropriate instructional decision is crucial for student academic growth. This article details how teachers can make data-driven decisions to carefully design writing instruction. Steps are presented for teachers to follow throughout the data driven decision-making process in order to meet…

Currently, dynamic structural equation modeling (DSEM) and residual DSEM (RDSEM) are commonly used in testing intensive longitudinal data (ILD). Researchers are interested in ILD mediation models, but their analyses are challenging. The present paper mathematically derived, empirically compared, and step-by-step demonstrated three types (i.e.,…

The demand for qualified analytics professionals remains high with forecasts showing a continued need over the next few years. While this demand necessitates instruction in analytics in the classroom, many students find analytics concepts to be complicated and boring. This teaching brief describes a novel approach to teaching analytics through…

Students need to know how to discern patterns and make decisions using visual information in our modern economy. However, there are few sources of real-world information available to instructors that give students access to visualizations to help develop their skills in interpreting complex situations using diverse data sources. This article…

Analyzing and interpreting data is essential to the practice of scientists and is also an essential science and engineering practice for science teaching and learning. Although working with data has benefits for student learning, it is also challenging, particularly with respect to aspects of work with data that are not yet very common in schools,…

The responsibilities of a general physical educator can be challenging and at times overwhelming. Whether teaching a full day of general physical education, or inclusive physical education classes that include a student or multiple students with disabilities, the expectation is that all students will be provided age and developmentally appropriate…

Data collected in many biology laboratory classes are on ratio or interval scales where the size interval between adjacent units on the scale is constant, which is a critical requirement for analysis with parametric statistics such as t-tests or analysis of variance. In other cases, such as ratings of disease or behavior, data are collected on…

Every application of integration by parts can be done with a tabular method. The trick is to identify and consider each new integral in the table before deciding how to proceed. This paper supplements a classic introduction to integration by parts with a particular tabular method called Row Integration by Parts (RIP). Approaches to tabular methods…

With sport now fully immersed in the era of big data, there is a need for sport managers who are data literate and, therefore, capable of collecting, managing, evaluating, and applying data to the range of problems and scenarios encountered by industry personnel. However, many in the sport management academy remain unacquainted with the…