Learning analytics (LA), like much of machine learning, assumes the training and test datasets come from the same distribution. Therefore, LA models built on past observations are (implicitly) expected to work well for future observations. However, this assumption does not always hold in practice because the dataset may drift. Recently,…

Generative AI tools (GenAI) are increasingly used for academic tasks, including qualitative data analysis for the Scholarship of Teaching and Learning (SoTL). In our practice as academic developers, we are frequently asked for advice on whether this use for GenAI is reliable, valid, and ethical. Since this is a new field, we have not been able to…

Artificial intelligence (AI) encompasses the science and engineering behind creating intelligent machines capable of tasks that typically rely on human intelligence, such as learning, reasoning, decision-making, and problem-solving. By analyzing vast amounts of data, identifying patterns, and making predictions that were once impossible, AI has…

This study addresses the opportunities presented by AI applications in education and the ethical issues brought about by this technology. AI in education holds excellent potential in personalized learning, automated assessment and feedback, and monitoring and analyzing student performance. However, using these technologies also raises ethical…

Predictive analytics is widely used in various domains, including education, to inform decision-making and improve outcomes. However, many predictive models are proprietary and inaccessible for evaluation or modification by researchers and practitioners, limiting their accountability and ethical design. Moreover, predictive models are often opaque…

As algorithmic decision making is increasingly deployed in every walk of life, many researchers have raised concerns about fairness-related bias from such algorithms. But there is little research on harnessing psychometric methods to uncover potential discriminatory bias inside decision-making algorithms. The main goal of this article is to…

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.…

This article explores the efficacy of AI used for teaching and learning tools. First, it examines three critical aspects of AI use in teaching and learning: AI complexity, algorithmic transparency, and AI bias. Second, it reviews recent literature that investigates the benefits and challenges of implementing AI within college classrooms. It…

Quantum computing is the beginning of a new age for diverse industries, and educational technologies will significantly benefit from such quantum developments. This is a novel approach, applying quantum algorithms to enhance educational technologies, with no previous studies addressing the integration of quantum computing for personalized…

The last decade has seen a rise in big data approaches, including in the humanities, whereby large quantities of data are collected and analysed. In this paper, we discuss long-form audio recordings that result from individuals wearing a recording device for many hours. Linguists, psychologists and anthropologists can use them, for example, to…

Digitalization needs to be storied for me to become critical of and creative with its functionings. In today's algorithmic condition, knowledge production and learning are complex posthuman entanglements: the human as materially affective has become fabricated hybrids of organism and machine. Storying is seen as simultaneous processes of…

The field of Data Science has seen rapid growth over the past two decades, with a high demand for people with skills in data analytics, programming, statistics, and ability to visualize, predict from, and otherwise make sense of data. Alongside the rise of various artificial intelligence (AI) and machine learning (ML) applications, we have also…

The use of algorithms and automation of public services is not new, but in recent years there has been a step change in processing power and a decrease in the price of these technologies, which means we are seeing more widespread use. These advances are reframing our perception of what matters in ways that impact the ethical dimensions of…

The manuscript outlines the development of an undergraduate course titled "Generative Artificial Intelligence for Business," aimed at equipping students with the knowledge and skills necessary to leverage generative AI technologies in various business contexts. The course framework covers fundamental concepts of generative AI, including…

One trending theme within research on learning and teaching is an emphasis on artificial intelligence (AI). While AI offers opportunities in the educational arena, blindly replacing human involvement is not the answer. Instead, current research suggests that the key lies in harnessing the strengths of both humans and AI to create a more effective…