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Zhu Zhu; Yingying Ren; An ran Shen – Education and Information Technologies, 2025
Current educational trends leverage artificial intelligence (AI) to provide high-quality teaching and enhance students' learning competitiveness. This study aimed to evaluate the acceptance of artificial intelligence generated content (AIGC) for assisted learning and design creation among art and design students. Based on an extended technology…
Descriptors: Artificial Intelligence, Computer Assisted Design, Computer Assisted Instruction, Art Education
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Ingri Strand; Liv Merete Nielsen – International Journal of Technology and Design Education, 2025
Laypeople's participation in the planning of built environments is dependent on their spatial literacy, and it is therefore important to develop this through general education. In Norway, architectural assignments in the subject of Art and crafts are aimed at enhancing spatial literacy, but not all activities are equally educative. The use of…
Descriptors: Artificial Intelligence, Physical Environment, Spatial Ability, Secondary School Students
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Fu, Wei; Li, Wei; Chen, Boyu; Zhang, Junjie; Xie, Qiong; Zhou, Lu; Zhang, Xuemei – Biochemistry and Molecular Biology Education, 2023
With the emergence of innovative technologies, including combinatorial chemistry, high-throughput screening, computer-aided drug design (CADD), artificial intelligence (AI) and big data, the importance of drug design in the field of drug discovery and development is increasing. Additionally, education in drug design plays an important role in the…
Descriptors: Chemistry, Pharmaceutical Education, Computer Assisted Design, Artificial Intelligence
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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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M. Esther Del Moral-Pérez; Nerea López-Bouzas; Jonathan Castañeda-Fernández – Journal of New Approaches in Educational Research, 2024
Transmedia skill, derived from the process of converting films into educational games using augmented reality and artificial intelligence, involves employing various languages and mediums to adapt an original narrative to another format. This transmedia practice presents an opportunity to cultivate diverse skills in teacher training by…
Descriptors: Media Adaptation, Educational Games, Computer Simulation, Artificial Intelligence
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Andy Nguyen; Anh Thi Duong; Diep Thi Bich Nguyen; Van Thi Thanh Lai; Belle Dang – Information and Learning Sciences, 2025
Purpose: The rapid advancement and widespread adoption of generative artificial intelligence (GenAI) in education have significantly impacted learning, teaching and assessment practices. This development has raised critical questions about necessary changes to learning design and traditional assessment methods for a society where GenAI becomes…
Descriptors: Artificial Intelligence, Instructional Design, Public Policy, Educational Policy
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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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Nusaibah Dakamsih; Mo’tasim-Bellah Alshunnag; Azel Alkayid – Educational Process: International Journal, 2025
Background/Purpose: This study investigates the pedagogical potential of AI-generated images to enhance student engagement and critical analysis in world literature curricula. Grounded in Reader-Response Theory, it explores how algorithmic visuals impact student interpretation, addressing a gap in understanding technology's role in fostering…
Descriptors: Undergraduate Students, Russian Literature, English Literature, Literary Genres
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Zeineb Mezghani; Ahmed Turki – International Journal of Adult Education and Technology, 2025
This study investigates the long-standing employability gap among Tunisian civil engineering graduates, where mismatching between university education and construction industry demands irks labor market readiness. Through a mixed-methods approach, entailing semi-structured interviews with 25 industry leaders and action research within a leading…
Descriptors: Foreign Countries, Employment Potential, Construction Industry, Engineering Education
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Shannon Sung; Xiaotong Ding; Rundong Jiang; Elena Sereiviene; Dylan Bulseco; Charles Xie – Journal of Geoscience Education, 2024
Engineering projects, such as designing a solar farm that converts solar radiation shined on the Earth into electricity, engage students in addressing real-world challenges by learning and applying geoscience knowledge. To improve their designs, students benefit from frequent and informative feedback as they iterate. However, teacher attention may…
Descriptors: Artificial Intelligence, Teaching Assistants, Energy, Engineering
Vo, Chuong-Dai Hong – Vocational Education Journal, 1996
The computer industry is growing at a phenomenal rate as technology advances and prices fall, stimulating unprecedented demand from business, government, and individuals. Higher levels of education will be the key to securing employment as organizations increasingly rely on sophisticated technology. (Author)
Descriptors: Artificial Intelligence, Computer Assisted Design, Computers, Data Processing Occupations
Jones, Mark K.; And Others – Educational Technology, 1990
Presents a knowledge representation model that was designed for instructional decision making. Topics discussed include classification models for instructional design; artificial intelligence; semantic networks; natural language; and data models, including network and hierarchical models. An example is given of knowledge analysis for a secondary…
Descriptors: Artificial Intelligence, Classification, Cognitive Structures, Computer Assisted Design