Analysis of programming process data has become popular in computing education research and educational data mining in the last decade. This type of data is quantitative, often of high temporal resolution, and it can be collected non-intrusively while the student is in a natural setting. Many levels of granularity can be obtained, such as…

"Fix Injustice, Not Kids and Other Principles for Transformative Equity Leadership" offers a deep dive into the leadership values, commitments, and practices that help educational leaders create and sustain equitable schools and districts. Drawing from their extensive equity and inclusion work with schools, Paul Gorski and Katy Swalwell…

This article reviews how National Assessment of Educational Progress (NAEP) has come to collect and analyze data about cognitive and behavioral processes (process data) in the transition to digital assessment technologies over the past two decades. An ordered five-level structure is proposed for describing the uses of process data. The levels in…

The rise of data collection in the public and private sectors has presented policymakers with an unprecedented opportunity to leverage vast amounts of data to create more efficient systems, improve program performance, and drive equitable outcomes. Empowering policymakers and practitioners with functional access to accurate data has the potential…

Technologies and teaching practices can provide a rich log data, which enables learning analytics (LA) to bring new insights into the learning process for ultimately enhancing student success. This type of data has been used to discover student online learning patterns, relationships between online learning behaviors and assessment performance.…

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…

Internet-of-Things (IoT) research has primarily focused on identifying IoT devices' organizational risks with little attention to consumer perceptions about IoT device risks. The purpose of this study is to understand consumer risk perceptions for personal IoT devices and translate these perceptions into guidance for future research directions. We…

Statistical tables associated with named probability distributions and their families, such as the standard normal, Student's t, and chi-square tables, among others, have been utilized for years and are still widely used today, especially for mathematics and statistics education. While such tables can be found in many statistics textbooks and even…

Focusing on systematic observation, one of the most potent methods of studying teaching quality, represents one of the numerous contributions of Daryl Siedentop to the profession. While he had a clear focus on issues of validity and reliability concerning systematic observation, over the past decades, attention to such issues appears to have…

The Brazilian government has adopted measures that aim to influence students' spatial mobility. The extent and success of such measures require detailed knowledge of the mobility determinants. Gravity models are the appropriate tool for analyzing the flows of college students from their place of origin to their destination. To analyze the…

Most disability research is conducted in high-income countries, despite much of the world's population living in low- and middle-income countries. Given the flexible nature of qualitative research, studies using this methodology have the potential to provide important insights into how disability is perceived across the globe. The aim of the…

This volume is largely about nontraditional data; this paper is about a nontraditional visualization: classification trees. Using trees with data will be new to many students, so rather than beginning with a computer algorithm that produces optimal trees, we suggest that students first construct their own trees, one node at a time, to explore how…

Background: Many learners struggle to productively self-regulate their learning. To support the learners' self-regulated learning (SRL) and boost their achievement, it is essential to understand the cognitive and metacognitive processes that underlie SRL. To measure these processes, contemporary SRL researchers have largely utilized think aloud or…

Background: Learning analytics (LA) collects, analyses, and reports data from the learning environment, to provide evidence of the effects of a particular learning design. Learning design (LD) outlines the conceptual framework for a meaningful interpretation of Learning analytics data. Objectives: The study aims to identify the most relevant…

Data about compensation received by employees in Illinois' 48 public community colleges are gathered by the Illinois Community College Board (ICCB). Data in the Fiscal Year 2023 Salary Report, which derive from the ICCB Faculty, Staff, and Salary (C1) Data and Supplementary Faculty, Staff, and Salary Information, reflect the census date of October…