Background: The data revolution in education has led to more data collection, more randomized controlled trials (RCTs), and more data collection within RCTs. Often following IES recommendations, researchers studying program effectiveness gather data on how the intervention was implemented. Educational implementation data can be complex, including…

Background: Randomized controlled trials (RCTs) give unbiased estimates of average effects. However, positive effects for the majority of students may mask harmful effects for smaller subgroups, and RCTs often have too small a sample to estimate these subgroup effects. In many RCTs, covariate and outcome data are drawn from a larger database. For…

The COVID-19 pandemic caused tremendous upheaval in schooling. In addition to its devasting effects on students' academic development, the disruptions to schooling had important consequences for researchers conducting effectiveness studies on educational programs during this era. Given the likelihood of future large-scale disruptions, it is…

This study aimed to address the state of data driven decision practices within the Division of Student Affairs at South County College. Framed by an exploratory qualitative case study, this project conducted semi-structured interviews of directors of student affairs and a document analysis of annual reports of the seven departments that constitute…

While some engineering students develop proper critical thinking skills, most engineering students do not. Engineers must critically think to tackle various problems on the job, but many schools do not properly instill critical thinking in engineering students. With engineers working on multiple tasks in little time, a knowledge of critical…

Universities are increasingly interested in providing courses that equip students with data science skills and engage experiential learning, particularly in the social sciences. However, these courses can be costly to implement and time-consuming for instructors to develop. This article describes an integrative learning model for teaching…

The public schools of Arkansas, open enrollment public charter schools, and education service cooperatives, 2022-2023 actual and 2023-2024 budgeted, is presented here. The rankings of selected items of the public schools of Arkansas, 2022-2023 actual, are also included. The school districts are listed according to Local Education Agency (LEA)…

At the school level statistics begins with exploratory data analysis, or EDA. Statistical learning goes on to include statistical inference, which will be discussed in the second part of this article. In this article, the author will talk about EDA and CODAP. EDA can be thought of as looking for patterns in data using graphs and simple statistics…

In this chapter, we explore the obligations for individuals and institutions that emerge from the newfound insights that are enabled through learning analytics. While ethical concerns are raised through learning analytics, a misplaced trend is a "do nothing" approach as a way to assure we "do no harm." We suggest that this is a…

The potential benefits of the growing amount of available educational data have not been fully realized, especially for principals, who play a key role in deriving insight from data to inform school improvement. The purpose of this mixed methods study was to describe experiences of principals using data analysis tools in a K-12 system. With a…

The purpose of this study is to examine the abstracts in 6th International Preschool Education Congress abstract book in terms of research subject, method, model, sample type, data collection tools, data analysis techniques, validity and reliability. This study is a qualitative study and was conducted using document analysis, which is one of the…

Background/Context: Teachers' practice of interim assessment data use is subject to an array of individual, social, and organizational contextual factors. While contemporary research situates interim assessments within teachers' broader practice of data use, teachers do not make sense of interim assessment data in isolation. This…

Constructing scientific arguments is an important practice for students because it helps them to make sense of data using scientific knowledge and within the conceptual and experimental boundaries of an investigation. In this study, we used a text mining method called Latent Dirichlet Allocation (LDA) to identify underlying patterns in students…

The analysis of multiple data streams is a long-standing practice within educational research. Both multimodal data analysis and temporal analysis have been applied successfully, but in the area of collaborative learning, very few studies have investigated specific advantages of multiple modalities versus a single modality, especially combined…

We are experiencing a significant shift in management practices--moving from intuition, experience, and gut-feeling driven decision-making to one that is driven by data, evidence, and computational sciences. This shift, which is often called the "analytics revolution," is not only changing the business landscape from a practical…