Large language models (LLMs) are increasingly adopted in educational contexts to provide personalized support to students and teachers. The unprecedented capacity of LLM-based applications to understand and generate natural language can potentially improve instructional effectiveness and learning outcomes, but the integration of LLMs in education…

Since 2018, institutions of higher education have been aware of the "enrollment cliff" which refers to expected declines in future enrollment. This paper attempts to describe how prepared institutions in Ohio are for this future by looking at trends leading up to the anticipated decline. Using IPEDS data from 2012-2022, we analyze trends…

The global pandemic has brought about significant changes in education, which have led to concerns regarding fairness and accessibility in a technology-driven learning environment. This article focuses on the use of Artificial Intelligence (AI) in education and examines the potential for bias in AI-powered tools. By using the example of a…

This paper reviews algorithmic or artificial intelligence (AI) bias in education technology, especially through the lenses of speculative fiction, speculative and liberatory design. It discusses the causes of the bias and reviews literature on various ways that algorithmic/AI bias manifests in education and in communities that are underrepresented…

Traditional information literacy skills (e.g., effectively finding and evaluating information) need to be updated due to the rapidly changing information ecosystem and the growing dominance of online platforms that use algorithms to control and shape information. This article proposes additions to the current ACRL "Framework for Information…

The American College Personnel Association recognized the increased prominence of digital technologies in student affairs work, developing a technology competency area that includes foundational, intermediate, and advanced objectives for data use. However, as the role of technology use in student affairs practice rapidly changes, it is…

Cyberbullying is the use of digital communication tools and spaces to inflict physical, mental, or emotional distress. This serious form of aggression is frequently targeted at, but not limited to, vulnerable populations. A common problem when creating machine learning models to identify cyberbullying is the availability of accurately annotated,…