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…

The research is a descriptive correlational study that investigates new methods for the creation of innovation for institutions. The research addresses the need for organizations to generate a novel form of innovation for their competitiveness and survival. These novel methods in the generation of innovation include using an organization's big…

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…

Those asked to make valid decisions with data don't have the technical knowledge to understand nuance around data quality, assessment aims, and statistical limitations that influence how they should interpret the data. This reality is what Greg Thompson, Leslie Rutkowski, and David Rutkowski call the validity paradox. Educators can surmount this…

Adapting interventions based on learner progress is paramount to the effectiveness of interventions in special education and applied behavior analysis. Although there is some research on effective methods for training practitioners to make general instructional decisions (e.g., modify an intervention) based on graphed performance data, research on…

Collecting data for the purpose of decision making has become an integral part of the landscape of education in the United States over the past decade. Many educators are swamped with such an overwhelming amount of information that it can be difficult to sort and analyze, leaving them floundering under wave after wave of data. The SWIS facilitator…

The COVID-19 pandemic negatively affected the quality of data from educational testing programs. These data were previously used for many important purposes ranging from placing students in instructional programs to school accountability. In this article, we draw from the research design literature to point out the limitations inherent in…

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,…