One significant impact of the COVID-19 pandemic for educators in forensic science was adapting what is traditionally a very applied field to a virtual learning environment. Because of this, science classes with a practical laboratory component had to implement significant adjustments to ensure that student learning objectives were still met,…

The protection of personal data and privacy are important issues closely related to use of social media, information and communication technologies, and the Internet in the area of education. The treatment of academic information and use of tools and programs for instruction, communication, and learning have revealed the handling of a significant…

Novice programmers often struggle on assignments, and timely help, such as a hint on what to do next, can help students continue to progress and learn, rather than giving up. However, in large programming classrooms, it is hard for instructors to provide such real-time support for every student. Researchers have, therefore, put tremendous effort…

Interactive learning environments can generate massive learning behavior data and the support of learning behavior big data can ensure the completeness of data analysis and robustness of relationship verification. In this study, learning behaviors are divided into training set and testing set, BP neural network and recurrent Elman network are…

The objective of this study is to contribute to the increasing database regarding the effects of school leadership on teachers' data usage by investigating the relationship between the technological leadership behaviors of school principals and data-driven decision-making at their schools based on the mediating and moderating effects of the…

This paper aims to critique approaches to qualitative coding that carry a bottom-up or inductive thinking. Despite the wide contributions of this epistemology to the social sciences, this paper contends that contemporary research and methodological debates have inadequately explored different epistemologies for coding. As such, this paper proposes…

There is a broad impetus across policy and institutional domains to expand public engagement and involvement with emerging technology research and innovation. Yet innovative theory, methods, and practices to critically explore algorithmic system controversies and democratic possibilities are still in nascent form. In this paper, we bring together…

In this article, we investigate the community-driven science happening organically in elite athletics as a means of engaging a community of learners--collegiate athletes, many of whom come from underrepresented groups--in STEM. We aim to recognize the data literacy practices inherent in sports play and to explore the potential of "critical…

Robust indicators are important for identifying disadvantaged pupils in education, and for ensuring that they are rightly receiving relevant state-funded assistance. This paper compares the quality and completeness of data from England on student eligibility for free school meals (FSM) based on an administrative census, with more all-encompassing…

The COVID-19 pandemic prompted a sudden rethinking of how music was taught and learned. Prior to the pandemic, the web-based digital audio workstation Soundtrap emerged as a leading platform for creating music online. The present study examined the growth of Soundtrap's usage during the COVID-19 pandemic. Using machine-learning methods, we…

Data visualization is an important tool for communicating research results. This manuscript discusses a method that instructors can use to introduce political science students to visualizations and discusses strategies that instructors can share with students about how to create high-quality visualizations. These strategies can help students make…

The goal of this chapter is to propose a cyclical process of how teachers can use multimodal multichannel data of cognitive, affective, metacognitive, motivational, and social processes to assist with the understanding of their own and their students' self-regulated learning (SRL), and their subsequent instructional decision making. What…

The various empirical models built for enrollment management, operations, and program evaluation purposes may have lost their predictive power as a result of the recent collective impact of COVID restrictions, widespread social upheaval, and the shift in educational preferences. This statistical artifact is known as model drifting, data-shift,…

Growing societal concern about a crisis in the wellbeing of young people has prompted a range of responses from governments and corporations, predicated on an ideal of the resilient, self-reliant individual. Behavioural economists, data scientists and educational technology companies now offer a variety of psychological interventions based on…

Eight years of data from Grand Valley State University Libraries show a positive correlation between in-class library instruction and student reenrollment the following fall semester. Using consistent statistical methods over time, controlling for confounding factors, and using a large population (N>16,000 annually) and strict protocols that…