Top 2% Scientists Worldwide 2024 by Stanford University
The most recent edition of the World’s Top 2% Scientists, as determined by Stanford University, was unveiled in October 2024.
In the current year’s compilation, FED is proud to have 6 faculty members featured in the single-year ranking. We extend our heartfelt congratulations to these distinguished colleagues who have earned their places in the esteemed top 2% list!
Prof Xiufeng Liu
Prof Mingming Zhou
Prof Biying Hu
Prof Rui Yuan
Prof Shulin Yu
Prof Shing On Leung
FED Best Paper Award in AY 2024/2025
Tang, X., & Hammer, D. (2024). “I think of it that way and it helps me understand”: Anthropomorphism in elementary students’ mechanistic stories. Science Education, 108(3), 661-679. https://doi.org/10.1002/sce.21851
Zhou, N. (2024). Perceived parental career expectation and adolescent career development: The mediating role of adolescent career-planning and goal-setting self-efficacy and the moderating role of perceived parent–adolescent career congruence. Journal of Counselling Psychology, 71(6), 621-632. https://psycnet.apa.org/doi/10.1037/cou0000736
FED Best Paper Award in AY 2023/2024
Lin, X., & Powell, S. R. (2023). Exploring academic and cognitive skills impacting retention and acquisition of word-problem knowledge gained during or after intervention. Child Development, 94(6), e362–e376. https://doi.org/10.1111/cdev.13970
FED Best Paper Award in AY 2022/2023
Kam, C. C. S., & Meyer, J. P. (2022). Testing the Nonlinearity Assumption Underlying the Use of Reverse-Keyed Items: A Logical Response Perspective. Assessment. Advance online publication. https://doi.org/10.1177/10731911221106775
Yu, S., Zhang, Y., Liu, C., & Lee, I. (2022). From theory to practice: Understanding the long-term impact of an L2 writing education course on writing teachers. Language Teaching Research. Advance online publication. https://doi.org/10.1177/13621688221130852
FED Best Paper Award in AY 2021/2022
Ching, B. H. H., & Wu, H. X. (2021). Young children’s knowledge of fair sharing as an informal basis for understanding division: A latent profile analysis. Learning and Instruction, 73, Article 101460. https://doi.org/10.1016/j.learninstruc.2021.101460