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Showing 1 to 15 of 84 results Save | Export
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Swamy, Vinitra; Radmehr, Bahar; Krco, Natasa; Marras, Mirko; Käser, Tanja – International Educational Data Mining Society, 2022
Neural networks are ubiquitous in applied machine learning for education. Their pervasive success in predictive performance comes alongside a severe weakness, the lack of explainability of their decisions, especially relevant in humancentric fields. We implement five state-of-the-art methodologies for explaining black-box machine learning models…
Descriptors: Artificial Intelligence, Academic Achievement, Grade Prediction, MOOCs
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Weikang Lu; Chenghua Lin – Asia-Pacific Education Researcher, 2025
Based on the UTAUT model, many studies have analyzed the factors influencing the use of artificial intelligence by teachers and students, but the conclusions are not uniform. This study chose high quality studies and encoded them to do meta analysis. After heterogeneity testing, sensitivity analysis and publication bias test, it has been found…
Descriptors: Meta Analysis, Technology Integration, Computer Software, Artificial Intelligence
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Rishwinder Singh Baidwan; Radhika; Rakesh Kumar – Journal of Educational Technology, 2024
Artificial intelligence technology has become widely used in many industries, including healthcare, agriculture, banking, social security, and home furnishings, due to the rise and development of this discipline. One of the newest areas of technology in the education industry is AI in Education, where extensive research supports instructional…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Models
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Shabnam Ara S. J.; Tanuja Ramachandriah; Manjula S. Haladappa – Online Learning, 2025
Predicting learner performance with precision is critical within educational systems, offering a basis for tailored interventions and instruction. The advent of big data analytics presents an opportunity to employ Machine Learning (ML) techniques to this end. Real-world data availability is often hampered by privacy concerns, prompting a shift…
Descriptors: Learning Analytics, Privacy, Artificial Intelligence, Regression (Statistics)
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Adelina Asmawi; Md. Saiful Alam – Discover Education, 2025
In the evolving techno-educational landscape, it is crucial to reimagine transformative pedagogies based on techno-teacher collaboration to revolutionize teaching effectiveness and efficiency. Although the cutting-edge generative AI tool, Chat GPT, is speculated to be a revolutionary CALL (computer-assisted language learning) tool for teaching…
Descriptors: Reading Instruction, Teaching Methods, Computer Assisted Instruction, Instructional Effectiveness
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Joalise Janse van Rensburg – Discover Education, 2024
The ability to think critically is an important and valuable skill that students should develop to successfully solve problems. The process of writing requires critical thinking (CT), and the subsequent piece of text can be viewed as a product of CT. One of the strategies educators may use to develop CT is modelling. Given ChatGPT's ability to…
Descriptors: Critical Thinking, Writing Instruction, Computer Software, Artificial Intelligence
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Hon Keung Yau; Ka Fai Tung – Turkish Online Journal of Educational Technology - TOJET, 2025
This study explores the development and evaluation of a chatbot model designed to facilitate learning within a department of a university. The project aims to enhance the learning experience by incorporating customized data into the chatbot's knowledge base, enabling personalized and context-aware interactions. The research investigates the…
Descriptors: Instructional Effectiveness, Artificial Intelligence, Computer Software, Technology Integration
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Te Hu; Zongmin Fu; Niya Wang; Jinbin Gui; Qinghe Song; Xiaofan Qian – Education and Information Technologies, 2025
Digital image processing is an integral part of the computer vision field. However, traditional digital image processing teaching methods mainly focus on theoretical knowledge, lacking practical teaching content. To address this issue, this article proposes a project-based learning (PBL) model that consists of four key stages: project proposal,…
Descriptors: Student Projects, Active Learning, Models, Computer Uses in Education
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Venkatasubramanian, Venkat – Chemical Engineering Education, 2022
The motivation, philosophy, and organization of a course on artificial intelligence in chemical engineering is presented. The purpose is to teach undergraduate and graduate students how to build AI-based models that incorporate a first principles-based understanding of our products, processes, and systems. This is achieved by combining…
Descriptors: Artificial Intelligence, Chemical Engineering, College Students, Teaching Methods
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Leif Sundberg; Jonny Holmström – Journal of Information Systems Education, 2024
With recent advances in artificial intelligence (AI), machine learning (ML) has been identified as particularly useful for organizations seeking to create value from data. However, as ML is commonly associated with technical professions, such as computer science and engineering, incorporating training in the use of ML into non-technical…
Descriptors: Artificial Intelligence, Conventional Instruction, Data Collection, Models
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Jionghao Lin; Wei Tan; Lan Du; Wray Buntine; David Lang; Dragan Gasevic; Guanliang Chen – IEEE Transactions on Learning Technologies, 2024
Automating the classification of instructional strategies from a large-scale online tutorial dialogue corpus is indispensable to the design of dialogue-based intelligent tutoring systems. Despite many existing studies employing supervised machine learning (ML) models to automate the classification process, they concluded that building a…
Descriptors: Classification, Dialogs (Language), Teaching Methods, Computer Assisted Instruction
Tiffany Barnes; Sarah Burriss; Joshua Danish; Samantha Finkelstein; Megan Humburg; Ally Limke; Ole Molvig; Heidi Reichert – Community for Advancing Discovery Research in Education (CADRE), 2024
Research and development work in artificial intelligence in education (AIED) is wide ranging and rapidly growing to support all areas of science, technology, engineering, and mathematics (STEM) teaching and learning. At the risk of hyperbole, this is potentially the most fundamentally game-changing technology for education to emerge since the…
Descriptors: Ethics, Artificial Intelligence, Educational Research, Technology Uses in Education
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Ehren Helmut Pflugfelder; Joshua Reeves – Journal of Technical Writing and Communication, 2024
The use of generative artificial intelligence (GAI) large language models has increased in both professional and classroom technical writing settings. One common response to student use of GAI is to increase surveillance, incorporating plagiarism detection services or banning certain composing activities from the classroom. This paper argues such…
Descriptors: Technical Writing, Artificial Intelligence, Supervision, Teaching Methods
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Tanjea Ane; Tabatshum Nepa – Research on Education and Media, 2024
Precision education derives teaching and learning opportunities by customizing predictive rules in educational methods. Innovative educational research faces new challenges and affords state-of-the-art methods to trace knowledge between the teaching and learning ecosystem. Individual intelligence can only be captured through knowledge level…
Descriptors: Artificial Intelligence, Prediction, Models, Teaching Methods
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Hongyu Xie; He Xiao; Yu Hao – International Journal of Web-Based Learning and Teaching Technologies, 2024
Modern e-learning system is a representative service form in innovative service industry. This paper designs a personalized service domain system, optimizes various parameters and can be applied to different education quality evaluation, and proposes a decision tree recommendation algorithm. Information gain is carried out through many existing…
Descriptors: Artificial Intelligence, Electronic Learning, Individualized Instruction, Models
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