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Khalid Arar; Ahmed Tlili; Lori Schunka; Soheil Salha; Anna Saiti – Leadership and Policy in Schools, 2025
The intersection of Artificial Intelligence (AI) and educational leadership has garnered significant attention in recent years due to advancements in knowledge technology and digital literacy. Despite growing interest from scholars and policymakers over the past decade, a comprehensive review of AI in the context of educational leadership and…
Descriptors: Artificial Intelligence, Educational Administration, Technology Uses in Education, Technology Integration
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Awol Endris; Ahmed Tlili; Ronghuai Huang; Lin Xu; TingWen Chang; Sanjaya Mishra – Leadership and Policy in Schools, 2025
Governments and private sectors are now putting in place the needed resources and infrastructure to harness the power of emerging technologies in education. One of these technologies is Artificial Intelligence (AI) which gained increasing attention due to its potential to enhance learning and teaching experiences, hence achieving better learning…
Descriptors: Policy Formation, Artificial Intelligence, Technology Uses in Education, Sustainable Development
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Mirjam Sophia Glessmer; Rachel Forsyth – Teaching & Learning Inquiry, 2025
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…
Descriptors: Artificial Intelligence, Research Methodology, Data Analysis, Scholarship
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Joaquín Rodríguez-Ruiz; Inmaculada Marín-López; Raquel Espejo-Siles – Education and Information Technologies, 2025
The present study aimed to analyse if self-control, self-esteem and self-efficacy are related to the use of artificial intelligence tools. These tools are being incorporated to educational practices, but there is a lack of empirical evidence about the relation between artificial intelligence use by students and their personal and psychological…
Descriptors: Artificial Intelligence, Self Control, Self Esteem, Self Efficacy
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Kangkang Li; Chengyang Qian; Xianmin Yang – Education and Information Technologies, 2025
In learnersourcing, automatic evaluation of student-generated content (SGC) is significant as it streamlines the evaluation process, provides timely feedback, and enhances the objectivity of grading, ultimately supporting more effective and efficient learning outcomes. However, the methods of aggregating students' evaluations of SGC face the…
Descriptors: Student Developed Materials, Educational Quality, Automation, Artificial Intelligence
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Atharva Naik; Jessica Ruhan Yin; Anusha Kamath; Qianou Ma; Sherry Tongshuang Wu; R. Charles Murray; Christopher Bogart; Majd Sakr; Carolyn P. Rose – British Journal of Educational Technology, 2025
The relative effectiveness of reflection either through student generation of contrasting cases or through provided contrasting cases is not well-established for adult learners. This paper presents a classroom study to investigate this comparison in a college level Computer Science (CS) course where groups of students worked collaboratively to…
Descriptors: Cooperative Learning, Reflection, College Students, Computer Science Education
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Todd Cherner; Teresa S. Foulger; Margaret Donnelly – TechTrends: Linking Research and Practice to Improve Learning, 2025
The ethics surrounding the development and deployment of generative artificial intelligence (genAI) is an important topic as institutions of higher education adopt the technology for educational purposes. Concurrently, stakeholders from various organizations have reviewed the literature about the ethics of genAI and proposed frameworks about it.…
Descriptors: Artificial Intelligence, Natural Language Processing, Decision Making, Models
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Alberto Gandolfi – International Journal of Artificial Intelligence in Education, 2025
In this paper, we initially investigate the capabilities of GPT-3 5 and GPT-4 in solving college-level calculus problems, an essential segment of mathematics that remains under-explored so far. Although improving upon earlier versions, GPT-4 attains approximately 65% accuracy for standard problems and decreases to 20% for competition-like…
Descriptors: Artificial Intelligence, Reliability, Problem Solving, Mathematics Skills
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Mark Feng Teng – European Journal of Education, 2025
The present study explored EFL students' perceptions and experiences in utilising ChatGPT to seek feedback for writing. The present study also examined how levels of metacognitive awareness (MA) influenced these perceptions and experiences. Utilising a mixed-method research design, the study collected data from a total of 40 EFL undergraduates…
Descriptors: English (Second Language), Student Attitudes, Feedback (Response), Writing (Composition)
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Felicity F. Frinsel; Fabio Trecca; Morten H. Christiansen – Cognitive Science, 2024
In language learning, learners engage with their environment, incorporating cues from different sources. However, in lab-based experiments, using artificial languages, many of the cues and features that are part of real-world language learning are stripped away. In three experiments, we investigated the role of positive, negative, and mixed…
Descriptors: Feedback (Response), Language Acquisition, Mathematical Linguistics, Role Theory
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Sourajit Ghosh; Md. Sarwar Kamal; Linkon Chowdhury; Biswarup Neogi; Nilanjan Dey; Robert Simon Sherratt – Education and Information Technologies, 2024
Students are the future of a nation. Personalizing student interests in higher education courses is one of the biggest challenges in higher education. Various AI and ML approaches have been used to study student behaviour. Existing AI and ML algorithms are used to identify features for various fields, such as behavioural analysis, economic…
Descriptors: Engineering Education, Artificial Intelligence, College Students, Student Interests
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Ming Liu; Jingxu Zhang; Lucy Michael Nyagoga; Li Liu – IEEE Transactions on Learning Technologies, 2024
Student question generation (SQG) is an effective strategy for improving reading comprehension. It helps students improve their understanding of reading materials, metacognitively monitor their comprehension, and self-correct comprehension gaps. Internet technologies have been used to facilitate SQG process through intensive peer support. However,…
Descriptors: Reading Comprehension, Questioning Techniques, Educational Technology, Artificial Intelligence
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Elvis Ortega-Ochoa; Marta Arguedas; Thanasis Daradoumis – British Journal of Educational Technology, 2024
Artificial intelligence (AI) and natural language processing technologies have fuelled the growth of Pedagogical Conversational Agents (PCAs) with empathic conversational capabilities. However, no systematic literature review has explored the intersection between conversational agents, education and emotion. Therefore, this study aimed to outline…
Descriptors: Empathy, Artificial Intelligence, Databases, Dialogs (Language)
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Duraisamy Akila; Harish Garg; Souvik Pal; Sundaram Jeyalaksshmi – Education and Information Technologies, 2024
Online education has been expected to be the future of learning; it will never replace the value of traditional classroom experiences fully. Technical problems have less impact on offline education, which gives students more freedom to plan their time and stick to it. In addition, teachers cannot observe their students' behavior and activities…
Descriptors: In Person Learning, Student Behavior, Attention, Artificial Intelligence
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Thanh Thuy Do; Golnoosh Babaei; Paolo Pagnottoni – Measurement: Interdisciplinary Research and Perspectives, 2024
Complex Machine Learning (ML) models used to support decision-making in peer-to-peer (P2P) lending often lack clear, accurate, and interpretable explanations. While the game-theoretic concept of Shapley values and its computationally efficient variant Kernel SHAP may be employed for this aim, similarly to other existing methods, the latter makes…
Descriptors: Artificial Intelligence, Risk Management, Credit (Finance), Prediction
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