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…

Collaborative learning provides learners with significant opportunities to collaborate on solving problems and creating better products. There has been a growing utilization of adaptive and intelligent systems to support productive learning while promoting collaborative practices. One of the core capabilities of these adaptive and intelligent…

For large-scale assessments, data are often collected with missing responses. Despite the wide use of item response theory (IRT) in many testing programs, however, the existing literature offers little insight into the effectiveness of various approaches to handling missing responses in the context of scale linking. Scale linking is commonly used…

The purpose of this article is to discuss the innovation and development of university education management informationization construction in the context of big data. Through a comprehensive comparison of innovative and traditional university education management information systems, it reveals the advantages of the innovative model in terms of…

With an increasingly diverse UK population and differences in outcomes and experiences, educational psychologists (EPs) need actively to adhere to and promote principles of equality and equity. Although there is limited engagement with social justice issues in the professional and ethical guidelines in the UK, there has been a growing body of…

Two commonly used approaches to capturing information about teachers are random probability surveys and teacher panels. This paper reviews the strengths and limitations of these two approaches in the context of capturing information about the teacher workforce. A case study is then presented drawing upon recent teacher survey data collections in…

This study examines prospective elementary teachers' growth and development of competencies, conceptions, and perceptions of mathematical modelling in a mathematics content course for elementary teachers. A series of lessons were implemented that engaged students in the modelling process through modelling tasks. The goal was to capture prospective…

Data from a moderately-selective state university in the Midwest is used to cross-examine the most appropriate data analytical techniques for predicting versus explaining college student persistence decisions. The current research provides an overview of the relative benefits of models specializing in prediction versus explanation with particular…

Colleges are increasingly turning to predictive analytics to identify "at-risk" students in order to target additional supports. While recent research demonstrates that the types of prediction models in use are reasonably accurate at identifying students who will eventually succeed or not, there are several other considerations for the…

This volume centres the notion of "chance" in education as a key concept in contemporary education -- relating to aspects like accountability, datafication, or international large-scale assessments -- and discusses the impact that the historical desire to "tame" this notion has had on present-day educational policy and…

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…