Despite the growing use of large language models (LLMs) in educational contexts, there is no evidence on how these can be operationalized by students to generate custom datasets suitable for teaching and learning. Moreover, in the context of network science, little is known about whether LLMs can replicate real-life network properties. This study…

Much has been written about how to improve the fairness of AI tools for decision-making but less has been said about how to approach this new field from the perspective of philosophy of education. My goal in this paper is to bring together criteria from the general algorithmic fairness literature with prominent values of justice defended by…

The proliferation of digital learning platforms has revolutionized the generation, accessibility, and dissemination of educational resources, fostered collaborative learning environments and producing vast amounts of interaction data. Machine learning (ML) algorithms have emerged as powerful tools for analyzing these complex datasets, uncovering…

The increasing integration of Artificial Intelligence (AI) in educational settings is transforming the role of school leaders, reshaping how decisions are made, and introducing both opportunities and challenges. This paper presents the findings of a scoping review that synthesises the current literature on AI's impact on educational leadership.…

While high-accuracy machine learning (ML) models for predicting student learning performance have been widely explored, their deployment in real educational settings can lead to unintended harm if the predictions are biased. This study systematically examines the trade-offs between prediction accuracy and fairness in ML models trained on the…

Background: Metacognitive processes have been linked to the development of conceptual knowledge in STEM courses, but previous work has centered on the regulatory aspects of metacognition. Purpose: We interrogated the relationship between epistemic metacognition and conceptual knowledge in engineering statics courses across six universities by…

Internet users are bombarded with information and need strategies to evaluate its trustworthiness. Expert fact-checkers rely on lateral reading, which involves investigating sources, finding better coverage, and tracing information back to original contexts. This study contrasted college students' preference for and use of lateral reading to…

Intelligent Voice Assistants (IVAs) have become integral to many users' daily lives, using advanced algorithms to automate various tasks. Nevertheless, many users do not understand the underlying algorithms and how they work, posing potential risks to the competent and self-determined use of IVAs. This work develops three online training modules…

Combining observational and experimental data for causal inference can improve treatment effect estimation. However, many observational data sets cannot be released due to data privacy considerations, so one researcher may not have access to both experimental and observational data. Nonetheless, a small amount of risk of disclosing sensitive…

Virtual reality (VR) has emerged as a transformative educational tool, enabling immersive learning environments that promote student engagement and understanding of complex concepts. However, despite the growing adoption of VR in education, there remains a significant gap in research exploring how generative artificial intelligence (AI), such as…

This study investigates the effectiveness of a culturo-techno-contextual approach (CTCA) in teaching flowcharts and algorithms to junior secondary school students. Despite their importance in programming, these concepts are often difficult for students to grasp. The study involved 196 students (average age 12) who were divided into experimental…

Video summarization is a method of deducing the content of video content for generating a summary in video format. The generated summary should have the significant segments of raw video. Recently, the content of video has been rapidly increasing, thus automatic video summarization is beneficial for individuals who want to keep time and learn more…

Entrance awards are financial incentives offered to admitted students at or near the time of admission. These awards are a frequently used tool to enhance yield rates among post-secondary institutions, sometimes among specifically-targeted populations. The impacts of these awards have been studied in many different contexts, using a variety of…

Structural equation models offer a valuable tool for delineating the complicated interrelationships among multiple variables, including observed and latent variables. Over the last few decades, structural equation models have successfully analyzed complete and right-censored survival data, exemplified by wide applications in psychological, social,…

It is of critical importance to be aware of the historical discrimination embedded in the data and to consider a fairness measure to reduce bias throughout the predictive modeling pipeline. Given various notions of fairness defined in the literature, investigating the correlation and interaction among metrics is vital for addressing unfairness.…