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Vassa Grichko; Betsy Schamber; Kari Termansen; David Barker; Shanice Hall; David Swank; Erin Lehmann – Impacting Education: Journal on Transforming Professional Practice, 2025
Universal guidelines for AI's use in the context of higher education remains unestablished. Despite this, doctoral students utilized AI to help in forming research ideas and with editing manuscripts. Thereby, the socialization of doctoral students into ethical AI use became imperative. This action research study had faculty and EdD students test…
Descriptors: Artificial Intelligence, Ethics, Guidelines, Doctoral Dissertations
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Héctor Galindo-Domínguez; Nahia Delgado; María-Victoria Urruzola; Jose-María Etxabe; Lucía Campo – Journal of Computer Assisted Learning, 2025
Background: With the integration of artificial intelligence into educational processes, its impact remains to be discovered. Objective: The aim of the present study was to determine whether, after a 7-month intervention in which a subject of artificial intelligence was taught, students improved their psychological needs for competence, autonomy…
Descriptors: Artificial Intelligence, Adolescents, Student Motivation, Technology Uses in Education
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Yin Kiong Hoh – American Biology Teacher, 2025
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…
Descriptors: Artificial Intelligence, Biological Sciences, Computer Software, Algorithms
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Yan Jiang; Lillie Ko-Wong; Ivan Valdovinos Gutierrez – Educational Researcher, 2025
In this essay, we explored the feasibility of utilizing artificial intelligence (AI) for qualitative data analysis in equity-focused research. Specifically, we compare thematic analyses of interview transcripts conducted by human coders with those performed by GPT-3 using a zero-shot chain-of-thought prompting strategy. Our results suggest that…
Descriptors: Artificial Intelligence, Feasibility Studies, Data Analysis, Interviews
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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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Yusuf Kartal; Munise Seckin-Kapucu – Journal of Education in Science, Environment and Health, 2024
Understanding the nature of science is an essential component of scientific literacy. In a technology and media-oriented environment, text-processing algorithms and various artificial learning approaches are crucial and continue to develop. Latent Dirichlet Allocation is a topic modeling algorithm that has been used frequently for many years to…
Descriptors: Artificial Intelligence, Scientific Principles, Documentaries, Algorithms
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Yi Xue – Education and Information Technologies, 2024
The new era of generative artificial intelligence has sparked the blossoming academic fireworks in the realm of education and information technologies. Driven by natural language processing (NLP), automated writing evaluation (AWE) tools become a ubiquitous practice in intelligent computer-assisted language learning (CALL) environments. Based on…
Descriptors: Literature Reviews, Meta Analysis, Bibliometrics, Artificial Intelligence
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Nodir Adilov; Jeffrey W. Cline; Hui Hanke; Kent Kauffman; Lisa Meneau; Elva Resendez; Shubham Singh; Mike Slaubaugh; Nichaya Suntornpithug – Journal of Education for Business, 2024
This article develops an index to measure the level of susceptibility of courses to cheating using ChatGPT (Chat Generative Pre-trained Transformer), an advanced text-based artificial intelligence (AI) language model. It demonstrates the application of the index to a sample of business courses in a mid-sized university. The study finds that the…
Descriptors: Artificial Intelligence, Cheating, Risk Assessment, Measurement
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Anagha Ani; Ean Teng Khor – Education and Information Technologies, 2024
Predictive modelling in the education domain can be utilised to significantly improve teaching and learning experiences. Massive Open Online Courses (MOOCs) generate a large volume of data that can be exploited to predict and evaluate student performance based on various factors. This paper has two broad aims. Firstly, to develop and tune several…
Descriptors: MOOCs, Classification, Artificial Intelligence, Prediction
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Mouna Ben Said; Yessine Hadj Kacem; Abdulmohsen Algarni; Atef Masmoudi – Education and Information Technologies, 2024
In the current educational landscape, where large amounts of data are being produced by institutions, Educational Data Mining (EDM) emerges as a critical discipline that plays a crucial role in extracting knowledge from this data to help academic policymakers make decisions. EDM has a primary focus on predicting students' academic performance.…
Descriptors: Prediction, Academic Achievement, Artificial Intelligence, Algorithms
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