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Xue, Song


  • Source: Scopus
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Personal profile


Song Xue is a PhD student in the School of Education and Social Work. His supervisor is Prof. Keith Topping (the first supervisor) and Dr Liz Lakin (the second supervisor). His tentative doctoral thesis title is developing the Pre-service science teachers’ modelling competence through technology-supported model scenarios.


He graduated in two disciplines prior to entering the faculty at the University of Dundee: Chemistry (BSc) and Education (MA) in China and received the National Teaching Chemistry Certificate in grades 10-12. His research interests are science education, the nature of the scientific model, modelling-based teaching and learning, developing various technology-supported modelling instruction to promote students (K-12 and preservice teachers) learning/teaching science.


Currently, he is engaging in two research projects. One is an international research project, namely MII-STEM: “Science Education in Southeast Asia: Teacher Training for Quality Education in STEM (Hanoi National University, Vietnam/Kasetsart University, Thailand/S.A. Tirtayasa University, Indonesia)”, which aims to improve the quality of teacher education in STEM (Science, Technology, Engineering and Mathematics) across Southeast Asia. The detail information can be found by following website: Song is also a research and teaching assistant at Zhejiang Normal University, where he focuses on how technology-based modelling curricula shape the students’ teachers in science education.


Contact details:


Twitter: @Song83640802

Education/Academic qualification

Master of Education, Zhejiang Normal University

1 Sep 20171 Jun 2019

Award Date: 1 Jun 2019

Ohio State University

1 Dec 20181 Mar 2019

Award Date: 1 May 2019

National Kaohsiung Normal University

1 Feb 20181 Jun 2018

Award Date: 1 Jun 2018

Bachelor of Science, Shanghai Normal University

1 Sep 20131 Jun 2017

Award Date: 1 Jun 2017


  • LB1603 Secondary Education. High schools
  • Model and Modelling
  • Science Studies
  • Assessment
  • Mixed quantitative and qualitative methods


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