Missing data presents a significant challenge in Educational Data Mining (EDM). Imputation techniques aim to reconstruct missing data while preserving critical information in datasets for more accurate analysis. Although imputation techniques have gained attention in various fields in recent years, their use for addressing missing data in…

ETS scientists developed a human-centered AI (HAI) framework that combines data on how students interact with assessments--such as task navigation and time spent--with their performance, providing deeper insights into student performance in large-scale assessments.

University students are increasingly using generative artificial intelligence (AI) tools in creative tasks. Drawing from the literature on AI-human interaction and team creativity, the present study developed a moderated mediating model regarding the effects of generative AI on team creativity. To validate the developed model, a questionnaire…

The increasing demand for privacy-preserving, ethically aligned synthetic data generation in education has highlighted the limitations of existing tabular data generators. Traditional approaches often sacrifice fairness or privacy in pursuit of predictive accuracy, rendering them unsuitable for high-stakes academic settings. In this paper, we…

Artificial intelligence (AI) is transforming the creative arts by generating unique artistic works. This research explores the impact of catastrophic forgetting on AI systems and its implications for artistic creativity. Catastrophic forgetting happens when AI forgets previously learned knowledge due to new learning. This poses a challenge for…

This chapter responds to the recent crisis surrounding developments in large language models (LLMs) and generative AI with a relational view of education informed by the emerging world-centered approach to education and a synthesis of personalist character formation with feminist care ethics. It proposes that the instinct to manage student use of…

Artificial intelligence (AI) transforms the ethical and moral subjectivity of teachers, positioning them to navigate the complex convergence of technological advancement, intellectual autonomy, and teacher identity. The purpose of this paper is to offer a conceptual model for how teachers' identities are constituted through AI prompt engineering.…

The rapid advancements in generative artificial intelligence have opened new avenues for enhancing various aspects of research, including the design and evaluation of survey questionnaires. However, the recent pioneering applications have not considered questionnaire pretesting. This article explores the use of GPT models as a useful tool for…

Educational materials advocating whole-body donation must be accurate, easy to read, and transparent, as one potential solution to the fact that the supply of donations is not keeping pace with educational demand, thereby disrupting anatomy education programs. The use of AI technologies to supplement communications with prospective donors and next…

The presence of social robots in children's daily environments has steadily increased. With the advancement of artificial intelligence (AI), social robots have influenced children's learning and development. This study innovatively utilized the Web of Science database and conducted a bibliometric analysis of 517 publications on social robots…

Quality questions, directed inquiry, and authentic literacy are important tools that enhance students' comprehension, knowledge, and application of what is taught. Learn how to phrase and pose good questions that will ignite inquiring minds and enrich student learning during classroom instruction. Author Erik M. Francis shares a framework for…

This paper examines how humans judge the capabilities of artificial intelligence (AI) to evaluate human attributes, specifically focusing on two key dimensions of human social evaluation: morality and competence. Furthermore, it investigates the impact of exposure to advanced Large Language Models on these perceptions. In three studies (combined N…

Computational learning theory studies the design and analysis of learning algorithms, and it is integral to the foundation of machine learning. In the modern era, classical computational learning theory is growingly unable to catch up with new practical demands. In particular, problems arise in the following aspects: i). "scalability":…

Artificial intelligence (AI) systems capable of generating creative outputs are reshaping our understanding of creativity. This shift presents an opportunity for creativity researchers to reevaluate the key components of the creative process. In particular, the advanced capabilities of AI underscore the importance of studying the internal…

The integration of artificial intelligence (AI) technologies into Learning Management Systems (LMS) represents a transformative advancement in contemporary education, enhancing personalization, efficiency, and interactivity. This study presents a systematic methodology for integrating AI technologies into the Moodle LMS. Moodle 4.5 was selected as…