Data is ubiquitous and inseparable from the human experience. It constantly informs and transforms interactions, decisions, and understanding. If the total amount of all the data created daily was printed on paper, it would fill a library the size of 110 Libraries of Congress. As a senior research consultant for an education market research and…

What if there was a better way to collect and interpret assessment data that could strengthen the link between teaching and learning? "Student Assessment: Better Evidence, Better Decisions, Better Learning" is the innovative guide to show you how it is done and done right. This unique book offers a new assessment model focused on…

In the 2023 report "Colorado's Longitudinal Data Landscape. Report to the Education Committees of the Colorado House of Representatives and the Colorado Senate. Statute: 23-1-141," the Colorado Department of Higher Education (CDHE) provided a detailed overview of Colorado's long history of efforts to support more connected, longitudinal…

The problem in this study was that first- and second-grade teachers are not using relevant and timely data, specifically running records, analysis of oral reading errors, self-correction rates, and word accuracy, as well as the student zone of proximal development (ZPD) in guided reading instruction. The purpose of this qualitative case study was…

This chapter explores the potential of integrating conversational AI tools such as ChatGPT with data visualization (DV) tools such as Power BI in higher education settings. A brief history of chatbots is summarized and challenges and opportunities in higher education are outlined. The highlights include AI's prospects for enhancing data-informed…

This paper explores co-design in Japanese education for deploying data-driven educational technology and practice. Although there is a growing emphasis on data to inform educational decision-making and personalize learning experiences, challenges such as data interoperability and inconsistency with teaching goals prevent practitioners from…

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…

The purpose of this study was to explore how teachers engaged in data use for instructional decision making. A grounded theory research design was used to analyze interviews of 10 special education teachers. Special education teachers were asked to complete an online survey and were interviewed with questions to reveal their experiences with…

Data-based decision-making has been a frequently used policy and practice intervention used in schools to help inform the decision-making processes of educational practitioners, with the aim of improving student outcomes. Interim benchmark assessments are designed by commercial test developers to support educators in this framework. In fact, the…

This quantitative study investigates the predictive power of machine learning (ML) models on degree completion among adult learners in higher education, emphasizing the enhancement of data-driven decision-making (DDDM). By analyzing three ML models - Random Forest, Gradient-Boosting machine (GBM), and CART Decision Tree - within a not-for-profit,…

Data-based decision making (DBDM) is a process of using student data to inform instructional decisions and intensify intervention for students whose data indicate inadequate academic and behavioral progress. Data teams, an important structure for DBDM, are a collaborative group of school faculty who meet to systematically analyze student data,…

This study investigates how 11- to 12-year-old students construct data-based decision trees using data cards for classification purposes. We examine the students' heuristics and reasoning during this process. The research is based on an eight-week teaching unit during which students labeled data, built decision trees, and assessed them using test…

This dissertation discusses the relationship between teacher sensemaking, attributions, and instructional adjustments prompted in response to student performance data. Through this qualitative observation study, this paper explores the varying perspectives of teachers, including their level of assessment literacy, and the dynamics of their…

Students cannot experience the full potential benefits of an intervention unless they are receiving the intervention. This is the second installment in a three-part series on intervention fidelity designed to highlight the importance of ensuring classroom supports are implemented as intended. This article provides guidance related to measuring and…

One of the most significant issues in education, as defined by the U.S. Department of Education Office of Accountability (2018), is disproportionality in exclusionary discipline. Disproportionality is defined as the over- and under-representation of racial/ethnic minorities in relation to their overall enrollment (Ahram et al., 2011). Currently,…