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Izuchukwu L. G. Ndukaihe; Chisom E. Ogbonnaya; Nwadiogo C. Arinze; Fabian O. Ugwu – Journal of College Student Retention: Research, Theory & Practice, 2025
Supervisor, co-worker, and customer-initiated incivility in the services industry dominate the literature. Incivility studies in academic institutions are beginning to emerge and students' initiated incivility has taken the center stage, whereas studies on lecturer-initiated incivility are lacking. This study, therefore, seeks to find out the…
Descriptors: Emotional Intelligence, Academic Persistence, Teacher Behavior, Antisocial Behavior
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Alex Lyman; Bryce Hepner; Lisa P. Argyle; Ethan C. Busby; Joshua R. Gubler; David Wingate – Sociological Methods & Research, 2025
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…
Descriptors: Artificial Intelligence, Computer Simulation, Open Source Technology, Social Science Research
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Anja Møgelvang; Simone Grassini – Discover Education, 2025
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…
Descriptors: Attitude Measures, Artificial Intelligence, College Students, Student Attitudes
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Tatiana A. Dugina; Natalia N. Nefedova; Olga V. Dybina; Alla A. Oshkina – Education in the Asia-Pacific Region: Issues, Concerns and Prospects, 2025
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…
Descriptors: Artificial Intelligence, Human Resources, Personnel Management, Higher Education
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Huiting Liu; Xiyuan Zhang; Jiangping Zhou; Yuancong Shou; Yang Yin; Chunlei Chai – International Journal of Technology and Design Education, 2025
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,…
Descriptors: Cognitive Style, Design, Artificial Intelligence, Technology Uses in Education
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Lord J. Hyeamang; Tejas C. Sekhar; Emily Rush; Amy C. Beresheim; Colleen M. Cheverko; William S. Brooks; Abbey C. M. Breckling; M. Nazmul Karim; Christopher Ferrigno; Adam B. Wilson – Anatomical Sciences Education, 2025
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…
Descriptors: Artificial Intelligence, Anatomy, Identification, Man Machine Systems
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Ron Aboodi – Educational Theory, 2025
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)…
Descriptors: Critical Thinking, Artificial Intelligence, Educational Benefits, Barriers
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Alexander M. Sidorkin – Educational Theory, 2025
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…
Descriptors: Artificial Intelligence, Criticism, Ethics, Safety
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Bogdan Yamkovenko; Charlie A. R. Hogg; Maya Miller-Vedam; Phillip Grimaldi; Walt Wells – International Educational Data Mining Society, 2025
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…
Descriptors: Algorithms, Artificial Intelligence, Models, Prediction
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Haoze Du; Richard Li; Edward Gehringer – International Educational Data Mining Society, 2025
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…
Descriptors: Artificial Intelligence, Performance, Evaluation, Automation
Mary Kalantzis; Bill Cope – Harvard Educational Review, 2025
In this supplement to the reprint of "A Pedagogy of Multiliteracies: Designing Social Futures," Mary Kalantzis and Bill Cope revisit the foundational ideas of the New London Group thirty years after the article's publication. They explore how the multiliteracies framework has evolved over time in response to changes in technology, media,…
Descriptors: Multiple Literacies, Social Media, Artificial Intelligence, Justice
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Niklas Humble – European Journal of Education, 2025
Artificial Intelligence (AI) has been highlighted as a potentially disruptive force across several industries and in higher education. Research has suggested that education and upskilling of citizens should adopt a broad approach, not only focusing on experts, for better nationwide AI readiness. This study investigates the content of AI policies…
Descriptors: Higher Education, Educational Policy, Artificial Intelligence, Universities
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Yanchao Yang; Zhe Shi; Yilin Wang; Yang Lu – Turkish Online Journal of Educational Technology - TOJET, 2025
As China joined the World Trade Organization (WTO) and its national strength continued to grow, enthusiasm for learning Chinese has been heating up globally. Chinese language education has gradually integrated into the education systems of more countries, becoming a significant focus of attention and study. However, despite the increasing demand…
Descriptors: Artificial Intelligence, Chinese, Second Language Learning, Oral Language
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Mark A. Runco – Journal of Creative Behavior, 2025
This article examines theories which suggest that authentic learning requires creativity. The connection between creativity and learning has been recognized for quite some time. Several of the theories examined herein are decades old. The older theories include Piaget's and Dewey's, and less obviously the humanistic theory of self-actualization.…
Descriptors: Authentic Learning, Creativity, Brain, Artificial Intelligence
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Patrick Gaudreau; Patrick Racine; Laurence Boileau; Benjamin Schellenberg – Social Psychology of Education: An International Journal, 2025
Mindset theory proposes that perfectionism is associated with a fixed mindset, but little research has studied this question. First, we reviewed the published literature (k = 8). Contrary to popular advice previously communicated to the public, perfectionistic standards were positively linked to an incremental theory and a growth mindset (rather…
Descriptors: Personality Traits, Psychological Patterns, Resilience (Psychology), Goal Orientation
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