Anonymous assessment, introduced to higher education over the last twenty-five years to reduce attainment gaps, is a now common place. This paper suggests some ways in which anonymous assessment could be reconceptualised. We argue that there is scant empirical evidence of anonymity having worked in reducing attainment gaps in higher education. It…

The integration of artificial intelligence (AI) into engineering education is essential for fostering innovation, strategic thinking and interdisciplinary skills in the intelligent era. On this basis, this study aims to track and visually represent the research outputs associated with AI applications in engineering education, providing insights…

As artificial intelligence (AI) continues to be widely integrated into global economic, social, and environmental governance, its role in promoting sustainable entrepreneurship has garnered increasing scholarly attention. This research aims to uncover the predictors affecting students' pro-environmental personal norms (EPNs) and subjective norms…

In contemporary societies, the processes of transindividuation by which knowledges are transformed into cycles and rhythms of metastability have been dramatically short-circuited. In turn, this has provoked the spiritual misery and pseudo-fabulations so prevalent all around us, including our educational contexts. For Stiegler, this is nothing…

In the twenty-first century, it has become increasingly important for educators to familiarise themselves with "Artificial Intelligence (AI)", given its growing influence in various fields, including education. This study examines AI literacy among Ghanaian basic school teachers and investigates gender differences in AI literacy. This…

Predicting academic performance in Educational Data Mining has been a significant research area. This involves utilizing machine learning techniques to analyze data from educational settings. Predicting student academic performance is a complex task due to the influence of multiple factors. This research uses supervised machine-learning approaches…

Generative artificial intelligence (AI) has the potential to revolutionize social science research. However, researchers face the difficult challenge of choosing a specific AI model, often without social science-specific guidance. To demonstrate the importance of this choice, we present an evaluation of the effect of alignment, or human-driven…

Identifying valid and reliable instruments measuring attitudes toward Artificial Intelligence (AI) and examining attitudinal gaps are becoming increasingly important as they may inform ethical and appropriate development, adoption, and regulation of AI technologies. In this study, we validated the 4-item AI Attitude Scale (AIAS-4) in a large…

This research considers the opportunities for using AI in HRM to raise the effectiveness of personnel management processes based on corporate social responsibility and the reduction of the divide between the market of university education and the job market. The authors combine the concept of the divide between the university education market and…

Students exhibit diverse cognitive styles, necessitating tailored educational approaches. However, the integration of Generative AI (GenAI) tools into design education presents challenges in accommodating the diverse cognitive styles of Industrial Design (ID) students. This study aims to identify students' cognitive styles in a GenAI environment,…

Evidence suggests custom chatbots are superior to commercial generative artificial intelligence (GenAI) systems for text-based anatomy content inquiries. This study evaluates ChatGPT-4o's and Claude 3.5 Sonnet's capabilities to interpret unlabeled anatomical images. Secondarily, ChatGPT o1-preview was evaluated as an AI rater to grade AI-generated…

As Artificial Intelligence (AI) keeps advancing, Generation Alpha and future generations are more likely to cope with situations that call for critical thinking by turning to AI and relying on its guidance without sufficient critical thinking. I defend this worry and argue that it calls for educational reforms that would be designed mainly to (a)…

The debate over halting artificial intelligence (AI) development stems from fears of malicious exploitation and potential emergence of destructive autonomous AI. While acknowledging the former concern, this paper argues the latter is exaggerated. True AI autonomy requires education inherently tied to ethics, making fully autonomous AI potentially…

Knowledge tracing (KT) models predict how students will perform on future interactions, given a sequence of prior responses. Modern approaches to KT leverage "deep learning" techniques to produce more accurate predictions, potentially making personalized learning paths more efficacious for learners. Many papers on the topic of KT focus…

Evaluating the performance of Large Language Models (LLMs) is a critical yet challenging task, particularly when aiming to avoid subjective assessments. This paper proposes a framework for leveraging subjective metrics derived from the class textual materials across different semesters to assess LLM outputs across various tasks. By utilizing…