The emergence of generative artificial intelligence (GenAI) has reignited long-standing debates about technology's role in education. While GenAI potentially offers personalized learning, adaptive tutoring, and automated support, it also raises concerns about algorithmic bias, de-skilling educators, and diminishing human connection. This…

Support vector classifiers are one of the most popular linear classification techniques for binary classification. Different from some commonly seen model fitting criteria in statistics, such as the ordinary least squares criterion and the maximum likelihood method, its algorithm depends on an optimization problem under constraints, which is…

Purpose: This paper investigates the digital information practices of Afro-Latino youth, focusing on their engagement with mental health content on TikTok. It aims to understand how racial and ethnic identity dimensions shape their information behaviors in digital spaces. Design/methodology/approach: Employing qualitative methods, the study…

Purpose: This study aims to explore children's cognitions about data flows online and their understandings of algorithms, often referred to as algorithmic literacy or algorithmic folk theories, in their everyday uses of social media and YouTube. The authors focused on children ages 8 to 11, as these are the ages when most youth acquire their own…

Purpose: The purpose of this conceptual paper is to describe how the affinity space concept has been used to frame learning via social media, and call for and discuss a refresh of the affinity space concept to accommodate changes in social media platforms and algorithms. Design/methodology/approach: Guided by a sociocultural perspective, this…

Background: Primary care providers are qualified to treat, diagnose, and manage common mental health issues like anxiety and depression. Anxiety and depression are common among college age students, with the average age of onset occurring in one's late teens to early 20s. Screening tools are commonly used to recognize patients who may be at risk…

In this article, the authors explore how the 3C Model can be used to integrate other curriculum areas with mathematics, namely digital technologies. To illustrate the model, they provide a practical example of a teaching sequence. T he 3C Model is designed to create opportunities for applying reasoning and problem-solving skills and learning…

With the advancements in technology and the growing demand for online education, Virtual Learning Environments (VLEs) have experienced rapid development in recent years. This demand was especially evident during the COVID-19 pandemic. The incorporation of new technologies in VLEs provides new opportunities to better understand the behaviors of…

Educational disparities between traditional and non-traditional student groups in higher distance education can potentially be reduced by alleviating social identity threat and strengthening students' sense of belonging in the academic context. We present a use case of how Learning Analytics and Machine Learning can be applied to develop and…

Scholars have long recognized that reading in digital spaces requires unique skills, strategies, and competencies in comparison to those needed for reading printed text. In recent years, the ubiquity of social media and algorithmically targeted content has radically changed the nature of online reading and meaning making. Technological changes…

In cyber security education, hands-on training is a common type of exercise to help raise awareness and competence, and improve students' cybersecurity skills. To be able to measure the impact of the design of the particular courses, the designers need methods that can reveal hidden patterns in trainee behavior. However, the support of the…

Logistic regression models have traditionally been used to identify the factors contributing to students' conceptual understanding. With the advancement of the machine learning-based research approach, there are reports that some machine learning algorithms outperform logistic regression models in terms of prediction. In this study, we collected…

Purpose: This study leverages social network analysis (SNA) to visualise the way students interacted with online resources and uses the data obtained from SNA as features for supervised machine learning algorithms to predict whether a student will successfully complete a course. Design/methodology/approach: The exploration and visualisation of the…

With the development of education technology, Smart classroom has evolved to version 2.0. Currently, the meta-analysis literature on the effects of smart classroom-based instruction on academic achievement ignores the impact of technological changes and time on the effect sizes. This study incorporated the impact of technological changes and time,…

Storylines exist about the types of learners who participate and excel in mathematics. To understand how AI chatbots participate in such storylines, we examined ChatGPT's feedback to different learners' mathematical writing in an exploratory study. Learners included academic labels, like gifted and special education, and race/ethnicity, like Black…