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Generative AI for feedback and collaborative knowledge construction in preservice physics teacher education

Yuchen Jiang1, Xiu-Mei Feng1,*, Yuting Liu1, Yiting Wang1, Li Xie1,†, and Lei Bao2,‡

  • 1College of Physical Science and Technology, Central China Normal University, Wuhan, Hubei 430079, China
  • 2School of Biological Science and Medical Engineering, Research Center for Learning Science, Key Laboratory of Child Development and Learning Science (MOE), Southeast University, Nanjing 211189, China

  • *Contact author: xiumeifeng@mail.ccnu.edu.cn
  • †Contact author: shirlyxieli@ccnu.edu.cn
  • ‡Contact author: lei.bao@outlook.com

Faculty orientations shape adoption of AI in research and teaching

T. J. Atherton, I. Descamps, M. Webel, T. R. Holmes, C. L. Vizcarra, N. Sui, and J. J. Foley

Phys. Rev. Phys. Educ. Res. 22 020152 (2026)

Artificial intelligence in university physics education: a systematic review of empirical studies

Zhanara Malikova, Bayan Ualikhanova, Torebay Turmambekov, Bakytgali Rakhashev, and Dauletbay Berdaliyev

Front. Educ. 11 1964629 (2026)

What a stratospheric balloon teaches that a laboratory cannot

Gustavo Murillo Yepes, Octavio A Chon-Torres, Melissa Gutiérrez-Arias, María Paz Henao Bedoya, and Oscar Stiven Muñoz Ramirez

Eur. J. Phys. 47 055805 (2026)

Generative AI in Higher Education Instructional Design: A Systematic Review of AI Roles, Educator Competences, and Professional Development Approaches

Natalia D. Spyropoulou and Achilles D. Kameas

Computers 15 745 (2026)

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