Zhongjun Wang is a Professor at the School of Materials and Metallurgy, University of Science and Technology Liaoning, China. He has long-term engaged in teaching and scientific research in the fields of metal materials, including magnesium alloy advanced preparation technology and heat treatment technology of steel materials. He has taught the core professional course Engineering Materials for many years, accumulating rich higher education teaching experience in engineering majors.
He also serves as the Group Leader of the Teaching Supervision Group in the Teaching Quality Office of University of Science and Technology Liaoning. His interdisciplinary research focuses on intelligent higher education quality assurance, generative artificial intelligence empowered teaching supervision, as well as teaching quality monitoring and evaluation system construction in universities. He is committed to exploring the innovative application of artificial intelligence technology in higher education teaching governance, constructing integrated models of intelligent teaching supervision, and conducting comparative research on teaching supervision systems worldwide.
Zhongjun Wang is a Professor at the School of Materials and Metallurgy, University of Science and Technology Liaoning, China. He has long-term engaged in teaching and scientific research in the fields of metal materials, including magnesium alloy advanced preparation technology and heat treatment technology of steel materials. He has taught the core professional course Engineering Materials for many years, accumulating rich higher education teaching experience in engineering majors.
He also serves as the Group Leader of the Teaching Supervision Group in the Teaching Quality Office of University of Science and Technology Liaoning. His interdisciplinary research focuses on intelligent higher education quality assurance, generative artificial intelligence empowered teaching supervision, as well as teaching quality monitoring and evaluation system construction in universities. He is committed to exploring the innovative application of artificial intelligence technology in higher education teaching governance, constructing integrated models of intelligent teaching supervision, and conducting comparative research on teaching supervision systems worldwide.