Many important voices--including The National Council for Teachers of Mathematics (NCTM), the Dana Center's Launch Years initiative, and others--advocate for expanding the traditional course offerings in high school mathematics and statistics to include courses such as the Introduction to Data Science (IDS). To date, the research on the IDS course…

Language sample analysis (LSA) is valuable clinical tool and an important component of comprehensive language assessment. However, LSA is underutilized in real-world practice. SLPs have identified time constraints, insufficient training, and lack of confidence in LSA skills as barriers to regular LSA implementation. Communication science and…

In K-12 computing education, there is a need to identify and teach concepts that are relevant to understanding machine learning technologies. Studies of teaching approaches often evaluate whether students have learned the concepts. However, scant research has examined whether such concepts support understanding digital artefacts from everyday life…

Milner (2012) defines opportunity gaps as the uncontrollable factors such as race, language, or economic status that can impact students' success in schools. Rather than placing focus on students' achievement, examinations of opportunity gaps emphasize the systems and structures that may contribute to disparities in student outcomes. The…

Algorithmic systems such as Learning Analytics (LA) are driving the datafication and algorithmization of education. In this research, we focus on the appropriateness of LA systems from the perspective of parents and students in secondary education. Anchored in the contextual integrity framework (Nissenbaum, "Washington Law Review, 79,"…

Partnership models have been effective across many areas of higher education such as involving students as teaching and learning consultants, in course design and redesign, and as co-instructors. However, there are few systems-level (i.e., entire programs or institutions) examples of partnership work and virtually none in systems-level assessment.…

This study investigates the development and implementation of a big data-driven English ecological classroom teaching model, aiming to reform university English instruction in alignment with contemporary technological advancements. The conventional teaching framework, often limited to textbooks and in-class activities, has been shown to…

Remote technology has been widely incorporated into health professions education. For procedural skills training, effective feedback and reflection processes are required. Consequently, supporting a self-regulated learning (SRL) approach with learning analytics dashboards (LADs) has proven beneficial in online environments. Despite the potential…

The main goal of this study was to evaluate the impact of an animation and visualization of data structures (AVDS) tool on both perceptions and objective test performance. The study involved a rigorous experiment that assessed the usability, acceptability, and effectiveness of the AVDS tool in solving exercises. A total of 78 participants…

Smart cities surveil through ubiquitous and intrusive data collection via networked sensors. Smart city efforts are also frequently imagined as primarily top-down and male visions of the future in service of economic benefit. The smart campus presents a new dimension of smart city urbanism as an identified gap in literature. In the following…

In recent years, there has been growing interest in the use of data-driven learning (DDL) in L2 writing instruction. This paper examined whether and to what extent DDL activities could enhance the writing complexity, accuracy, and fluency (CAF) of 30 Thai EFL learners. The presentation of DDL in this study was hands-on concordancing with the…

This article reports on a multi-method study of a high school course in data science, finding that students who take data science take more mathematics courses than those who do not, there are more under-represented students in data science than is typical for other advanced mathematics courses; that the students who take data science are more…

A professional practice is a type of internship, a practicum, that encompasses a supervised hands-on training experience for students to develop and identify the core and enabling competencies required in a professional environment. It also allows them to identify the developed and underdeveloped skills that are important in the labour environment…

The School Climate Measure (SCM) is a comprehensive measure of school climate that has demonstrated significant psychometric support and available free of charge. The goal of this research-informed commentary is to provide readers with necessary knowledge to make an informed decision of the appropriateness of the SCM for use in their school or…

Use of university students' educational data for learning analytics has spurred a debate about whether and how to provide students with agency regarding data collection and use. A concern is that students opting out of learning analytics may skew predictive models, in particular if certain student populations disproportionately opt out and biases…