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Narayan, R., Rodriguez, C., Araujo, J., Shaqlaih, A., & Moss, G. (2013). Constructivism—Constructivist Learning Theory. In B. J. Irby, G. Brown, R. Lara-Alecio, & S. Jackson (Eds.), The Handbook of Educational Theories (pp. 169-183). IAP Information Age Publishing.
https://psycnet.apa.org/record/2013-11995-015

has been cited by the following article:

• TITLE: Art Education and Generative AI: An Exploratory Study in Constructivist Learning and Visualization Automation for the Classroom

  AUTHORS: John V. Pavlik, Orianna M. Pavlik

  KEYWORDS: Generative Artificial Intelligence, Art, Art Education, Curricular Framework

  JOURNAL NAME: Creative Education, Vol.15 No.4, April 28, 2024

  ABSTRACT: Artificial intelligence (AI) presents significant implications for art and art education. This paper focuses on the domain of generative AI, or GAI. GAI is a form of AI that can create content, including visual and other forms of art, or art-like material. The research question we consider is: what are the implications of GAI for art education? Drawing upon constructivist learning theory, this paper asserts that GAI can provide educators an opportunity to engage students actively in the critical analysis of art or art-like material generated via AI through an experience-based approach. An exploratory method is employed to qualitatively examine this thesis. Implications and limitations of the approach are presented regarding the potential utilization of GAI to engage students in participatory art education learning experiences. GAI is conceptualized as a form or proxy for automation of visual art generation.