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Showing 1 to 15 of 533 results Save | Export
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Xueqiao Zhang; Chao Zhang; Jianwen Sun; Jun Xiao; Yi Yang; Yawei Luo – IEEE Transactions on Learning Technologies, 2025
Large language models (LLMs) have significantly advanced smart education in the artificial general intelligence era. A promising application lies in the automatic generalization of instructional design for curriculum and learning activities, focusing on two key aspects: 1) customized generation: generating niche-targeted teaching content based on…
Descriptors: Artificial Intelligence, Instructional Design, Technology Uses in Education, Cognitive Ability
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De Ruyck, Olivia; Conradie, Peter; Van Hove, Stephanie; All, Anissa; Baccarne, Bastiaan; De Marez, Lieven; Saldien, Jelle – International Journal of Technology and Design Education, 2023
Interactions between humans and smart products (i.e. digital components integrated in physical Internet of Things devices) are becoming more complex and less visible. Yet designers lack tools to capture these interactions and incorporate them into their design. In this paper we present the Human-Computer-Context Interaction (HCCI) tool that helps…
Descriptors: Man Machine Systems, Industrial Arts, Design, Internet
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Aidan Doyle; Pragnya Sridhar; Arav Agarwal; Jaromir Savelka; Majd Sakr – Journal of Computer Assisted Learning, 2025
Background: In computing education, educators are constantly faced with the challenge of developing new curricula, including learning objectives (LOs), while ensuring that existing courses remain relevant. Large language models (LLMs) were shown to successfully generate a wide spectrum of natural language artefacts in computing education.…
Descriptors: Computer Science Education, Artificial Intelligence, Learning Objectives, Curriculum Development
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Andrea Hicks; Wissam Kontar – Journal of Civil Engineering Education, 2024
Engineering programs must produce graduates who are able to consider multicriteria decisions including ethical implications during engineering practice. Teaching students in a meaningful manner to consider these multifaceted decisions was investigated through the usage of disasters and primary coverage of infrastructure disasters. Students…
Descriptors: Engineering Education, Emergency Programs, Natural Disasters, Ethics
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Chan, Jenny Yun-Chen; Nagashima, Tomohiro; Closser, Avery H. – Cognitive Science, 2023
Given the recent call to strengthen collaboration between researchers and relevant practitioners, we consider participatory design as a way to advance Cognitive Science. Building on examples from the Learning Sciences and Human-Computer Interaction, we (a) explore "what," "why," "who," "when," and…
Descriptors: Cognitive Science, Learning Processes, Man Machine Systems, Cooperation
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Tianjiao Zhao; Jiayi Jia; Tianfei Zhu; Junyu Yang – International Journal of Technology and Design Education, 2024
Designers are always pursuing design with suitable emotions. Effective emotional fusion not only produces a good user experience but also extends the product lifecycle. The decoding of design emotion and the use of design emotion language should run through the entire design process. In this study, we propose a new emotion-embedded design flow…
Descriptors: Psychological Patterns, Design, Artificial Intelligence, Databases
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Ronak R. Mohanty; Peter Selly; Lindsey Brenner; Shantanu Vyas; Cassidy R. Nelson; Jason B. Moats; Joseph L. Gabbard; Ranjana K. Mehta – IEEE Transactions on Learning Technologies, 2025
Immersive extended reality (XR) technologies, including augmented reality (AR), virtual reality, and mixed reality, are transforming the landscape of education and training through experiences that promote skill acquisition and enhance memory retention. These technologies have notably improved decision making and situational awareness in public…
Descriptors: Technology Integration, Artificial Intelligence, Safety Education, Instructional Design
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Chahna Gonsalves – Journal of Learning Development in Higher Education, 2025
Generative AI (GenAI) is transforming higher education. It has already challenged the validity of traditional assessment methods and revealed concerns about the authenticity and reliability of conventional approaches. This opinion piece proposes an expanded theoretical framework for contextual learning, incorporating practical, situational,…
Descriptors: Artificial Intelligence, Higher Education, Evaluation Methods, Technology Uses in Education
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Gerti Pishtari; María Jesús Rodríguez-Triana; Luis P. Prieto; Adolfo Ruiz-Calleja; Terje Väljataga – Journal of Computer Assisted Learning, 2024
Background: In the field of Learning Design, it is common that researchers analyse manually design artefacts created by practitioners, using pedagogically-grounded approaches (e.g., Bloom's Taxonomy), both to understand and later to support practitioners' design practices. Automatizing these high-level pedagogically-grounded analyses would enable…
Descriptors: Electronic Learning, Instructional Design, Active Learning, Inquiry
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Wenqiang Dai; Qiongyao Liu; Yuemin Gao; Wenjing Liu; Shaojuan Ouyang – International Journal of Web-Based Learning and Teaching Technologies, 2025
The traditional curriculum design methods suffer from issues like outdated content and limited instructional approaches. To address these, this article proposes an optimized curriculum design system that integrates CAD and neural network models. This system enables intelligent curriculum content generation, introduces CAD-assisted instructional…
Descriptors: Curriculum Design, Computer Assisted Design, Artificial Intelligence, Computer Uses in Education
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Miroslava Petrova; Claas Kuhnen – Design and Technology Education, 2025
Integration of Artificial Intelligence (AI) in the design process is a growing area of research interest. Three years after its public launch in 2022, AI has already established itself as the most disruptive tool revolutionizing how designers conceptualize, iterate and innovate. As AI technologies continue to evolve, it is pertinent that design…
Descriptors: Artificial Intelligence, Computer Software, International Cooperation, Institutional Cooperation
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Giulia Cosentino; Jacqueline Anton; Kshitij Sharma; Mirko Gelsomini; Michail Giannakos; Dor Abrahamson – British Journal of Educational Technology, 2025
As AI increasingly enters classrooms, educational designers have begun investigating students' learning processes vis-à-vis simultaneous feedback from active sources--AI and the teacher. Nevertheless, there is a need to delve into a more comprehensive understanding of the orchestration of interactions between teachers and AI systems in educational…
Descriptors: Artificial Intelligence, Learning Processes, Instructional Design, Design
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Gümüs, Muhammed Murat; Kayhan, Osman; Korkmaz, Özgen; Altun, Halis; Yilmaz, Nihat – International Online Journal of Primary Education, 2023
This study aims to create a rubric based on the pedagogical properties of educational robots for pre-school students and determine the compliance level with educational robot sets. In this sense, the study is considered a first and significant step toward selecting robots based on pedagogical-driven factors. For this aim, a mixed-method research…
Descriptors: Classification, Educational Technology, Robotics, Preschool Education
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De Garrido, Luis – Creativity Research Journal, 2022
The main objective of this paper is the conceptual design of a computational AI system that emulates human creativity. To do this, extensive research has been done on recent discoveries about the neural bases of human creativity. As a result, eleven neurocognitive factors have been identified on which the tremendous creative capacity of the human…
Descriptors: Artificial Intelligence, Brain, Creativity, Program Design
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Amanda Konet; Ian Thomas; Gerald Gartlehner; Leila Kahwati; Rainer Hilscher; Shannon Kugley; Karen Crotty; Meera Viswanathan; Robert Chew – Research Synthesis Methods, 2024
Accurate data extraction is a key component of evidence synthesis and critical to valid results. The advent of publicly available large language models (LLMs) has generated interest in these tools for evidence synthesis and created uncertainty about the choice of LLM. We compare the performance of two widely available LLMs (Claude 2 and GPT-4) for…
Descriptors: Data Collection, Artificial Intelligence, Computer Software, Computer System Design
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