Research on the Educational Application of Generative Artificial Intelligence Images in the Design of Semiotics Learning Models

被引:0
|
作者
Hsiao, Ming-Yu [1 ]
Zhang, Simo [1 ]
机构
[1] Chaoyang Univ Technol, Coll Design, Taichung 413, Taiwan
关键词
Design Semiotics; Design with Generative AI Images; AI Educational Applications; AI Teaching Methods;
D O I
10.1145/3637907.3637947
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Generative Artificial Intelligence (AI) has emerged as a novel technology with profound implications for education and deep learning, particularly due to its advancements in image generation. This progress has had a disruptive impact on the design industry, where designers are increasingly embracing generative AI images as innovative tools and techniques to enhance design ideation and creative expression. Integrating generative AI images into design education has become an inevitable trend, as it guides students in developing a deeper understanding of design aesthetics. However, the current application of generative AI images in design education lacks innovative use grounded in design theory. Therefore, the incorporation of generative AI images within the framework of design theory becomes crucial to interpret and refine design processes and design thinking. This research aims to explore the application of generative AI images in design semiotics, utilizing design theory as its foundation. By integrating design processes and incorporating design case studies, the study seeks to analyze how generative AI images can be effectively applied in design semiotics. Ultimately, the research strives to establish a pedagogical approach for the application of generative AI image-based design semiotics.
引用
收藏
页码:8 / 15
页数:8
相关论文
共 50 条
  • [31] Understanding and Supporting Thinking and Learning With Generative Artificial Intelligence
    Agnoli, Sam
    Rapp, David N.
    JOURNAL OF APPLIED RESEARCH IN MEMORY AND COGNITION, 2024, 13 (04) : 495 - 499
  • [32] Application of Generative Artificial Intelligence in Film Image Production
    Zhao X.
    Zhao X.
    Computer-Aided Design and Applications, 2024, 21 (S27): : 15 - 28
  • [33] Generative artificial intelligence for de novo protein design
    Winnifrith, Adam
    Outeiral, Carlos
    Hie, Brian L.
    CURRENT OPINION IN STRUCTURAL BIOLOGY, 2024, 86
  • [34] Generative artificial intelligence for small molecule drug design
    Kanakala, Ganesh Chandan
    Devata, Sriram
    Chatterjee, Prathit
    Priyakumar, Udaykumar Deva
    CURRENT OPINION IN BIOTECHNOLOGY, 2024, 89
  • [35] Determining aspects of artificial intelligence in educational research
    Molina-Isaza, Liliana Esther
    PRAXIS-COLOMBIA, 2024, 20 (03): : 602 - 620
  • [36] LEARNING SENSITIVE IMAGES USING GENERATIVE MODELS
    Cheung, Sen-Ching Samson
    Wildfeuer, Herb
    Nikkhah, Mehdi
    Zhu, Xiaoqing
    Tan, Wai-tian
    2018 25TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2018, : 4128 - 4132
  • [37] Artificial Intelligence: A Boon or a Bane for Educational Leaders in Educational Research
    Watkins, Steven
    JOURNAL OF LEADERSHIP STUDIES, 2018, 12 (03) : 74 - 75
  • [38] Introduction to Artificial Intelligence and Machine Learning in Pathology and Medicine: Generative and Nongenerative Artificial Intelligence Basics
    Rashidi, Hooman H.
    Pantanowitz, Joshua
    Hanna, Matthew G.
    Tafti, Ahmad P.
    Sanghani, Parth
    Buchinsky, Adam
    Fennell, Brandon
    Deebajah, Mustafa
    Wheeler, Sarah
    Pearce, Thomas
    Abukhiran, Ibrahim
    Robertson, Scott
    Palmer, Octavia
    Gur, Mert
    Tran, Nam K.
    Pantanowitz, Liron
    MODERN PATHOLOGY, 2025, 38 (04)
  • [39] Analyzing Machine Learning Models Based on Explainable Artificial Intelligence Methods in Educational Analytics
    Minullin, D. A.
    Gafarov, F. M.
    AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS, 2024, 58 (SUPPL3) : S115 - S122
  • [40] Discriminative, generative artificial intelligence, and foundation models in retina imaging
    Ruamviboonsuk, Paisan
    Arjkongharn, Niracha
    Vongsa, Nattaporn
    Pakaymaskul, Pawin
    Kaothanthong, Natsuda
    TAIWAN JOURNAL OF OPHTHALMOLOGY, 2024,