Predicting student performance using educational data is a significant area of machine learning research. However, class imbalance in datasets and the challenge of developing interpretable models can hinder accuracy. This study compares different variations of the Synthetic Minority Oversampling Technique (SMOTE) combined with classification…

This chapter describes how any campus can use collaborative professional integration and three "data buckets" (pre-college, during-college, and post-college buckets) to disaggregate assessment evidence, interpret findings contextually, and focus attention on realistic actions to improve student performance in the areas of leverage over…

Internationally, there has been a policy push for using student data for instruction. Yet, research has noted few examples of actually understanding how this data-use practice takes place. This study presents a case of an instructional data team making sense of student data. The study shares data to show how teachers' process for using data to…

In this book, best-selling author Susan M. Brookhart helps teachers and administrators understand the critical elements and nuances of assessment data and how that information can best be used to inform improvement efforts in the school or district. Readers will learn: (1) What different kinds of data can--and cannot--tell us about student…

Purpose: This paper argues that in a well-organised school with strong leadership and vision coupled with a concerted effort to improve the teaching performance of each teacher, student achievement can be enhanced. The purpose of this paper is to demonstrate that while macro-effect sizes such as "whole of school" metrics are useful for…

There is extensive research on the benefits of making data-informed decisions, but research also contains evidence many educators incorrectly interpret student data. Meanwhile, the types of detailed labeling on over-the-counter medication have been shown to improve use of non-medication products, as well. However, data systems most educators use…

Enrollment is rising across the nation's community colleges, but completion rates remain untenably low. Reformers are focusing on the importance of using comprehensive, high-quality data on student progress and completion to bring about change. A core tenet of Achieving the Dream: Community Colleges Count has been to embed a culture of…

This document presents an interactive visual guide that explains what data are, how they help, and what people can do with them. It also offers ways to enact statewide policies that support effective data use.

Predicting the future is now in the hands of K12 administrators. While for years districts have collected thousands of pieces of student data, educators have been using them only for data-driven decision-making or formative assessments, which give a "rear-view" perspective only. Now, using predictive analysis--the pulling together of data over…

The purpose of this study was to determine how teacher perceptions of data and use of data-driven instruction affect student performance in English language arts (ELA). This study investigated teachers' perceptions of using data in the classroom and what supports they need to do so. The goal of the research was to increase the level of knowledge…

This editorial reviews recent studies of accountability policies using National Assessment of Educational Progress (NAEP) data and compares the use of aggregate NAEP data to the availability of individual-level data from NAEP. While the individual-level NAEP data sets are restricted-access and do not give accurate point-estimates of achievement,…