Developing a New Model of Using Artificial Intelligence and Postmodern Arts in Visual Arts and Design Courses (VADC) among University Students | Zendy

Abeer S Almogren | Zendy

Open Access

Developing a New Model of Using Artificial Intelligence and Postmodern Arts in Visual Arts and Design Courses (VADC) among University Students

Author(s) -

Abeer S Almogren

Publication year - 2025

Publication title -

ieee access

Language(s) - English

Resource type - Magazines

SCImago Journal Rank - 0.587

H-Index - 127

eISSN - 2169-3536

DOI - 10.1109/access.2025.3594262

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

In response to the evolving landscape of artistic expression and technological advancements, educators are faced with the challenge of developing a contemporary model that engages and raises awareness among students about the integration of Artificial Intelligence (AI) and Postmodern arts such as “Ceramics, sculpture, painting, drawing, and Arabic calligraphy” within Visual Arts and Design Courses (VADC). Thus, this research aims to develop a new model to explore the innovative integration of AI and Postmodern arts within VADC offered to Saudi university students. This research employs the Technological Pedagogical Content Knowledge (TPACK) framework and utilizes quantitative approaches to gain a comprehensive understanding of the current state of visual arts and design education. Data were collected through surveys distributed to 307 university students enrolled in VADC at four universities in Saudi Arabia. Through the utilization of structural equation modeling (SEM), the article analyses the complex relationships between ten variables such as subjective norm, outcome expectations, self-efficacy, artistic personality, job availability, attitudes toward studying VADC, perceived behavioral control, awareness of studying VADC, importance of VADC, and students’ academic performance in VADC. The findings contribute to the development of a new instructional model that addresses the identified gaps in VADC and makes high theoretical and scientific contributions. By conducting 18 hypotheses tests and combining the strengths of quantitative analyses of ten factors, the results show that twelve hypotheses were accepted and six hypotheses were rejected. Additionally, the findings of this research provide a reason why these six hypotheses were rejected and offer a comprehensive understanding of the challenges and opportunities associated with integrating AI and Postmodern arts into the curriculum in higher education institutions.

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