Curriculum Vitae
Lehong shi
PhD student, Learning, Design, and Technology
University of Georgia, Athens, GA
lehong.shi@uga.edu
Education
Aug. 2020 - Present Doctoral student in Learning, Design, and Technology
College of Education, University of Georgia, Athens, GA
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Sept. 2004 - Jun. 2006 M.S. in American History
Northeast Normal University, Changchun, China
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Sept. 2000 - Jun. 2004 B.S. in History
Northeast Normal University, Changchun, China
Teaching
Feb. 2021 - present Intern
Teaching with Technology
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Nov.2017 - Sept. 2018 Preschool teacher
Action Day Primary Plus, Mountain View, CA
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Sept.2016 - Sept. 2017 High School teacher
Shandong Zibo NO. 1 High School, China
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Dec.2015 - Aug. 2016. Bilingual School Teacher
Washington International School, Seattle, WA
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Jun.2006 - Sept. 2015 High School teacher
Shandong Zibo NO. 1 High School, China
Publication
Peer-review Journal Article
Zhai, X., Haudek, K., Shi, L., Nehm, R., Urban-Lurain, M. (2020). From substitution to redefinition: A framework of machine learning-based science assessment. Journal of Research in Science Teaching. 1-30. https://doi.org/10.1002/tea.21658 (SSCI)
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Zhai, X., Yin, Y., Pellegrino, J., Haudek, K., Shi, L. (2020). Applying machine learning in science assessment: A systematic review. Studies in Science Education. 56(1), 111-151.
https://doi.org/10.1080/03057267.2020.1735757 (SSCI)
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Zhai, X., Shi, L. (2020). Understanding how the perceived usefulness of mobile technology impacts physics learning achievement: A pedagogical perspective. Journal of Science Education and Technology. 1-15. https://doi.org/10.1007/s10956-020-09852-6 (SSCI)
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Zhai, X., Shi, L., Nehm, R. (2020). A Meta-Analysis of Machine Learning-based Science Assessments: Factors Impacting Machine-Human Score Agreements. Journal of Science Education and Technology.
https://doi.org/10.1007/s10956-020-09875(SSCI)
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Peer-Review Conference Proposal
Shi, L., Zhai., X. (2020). Understanding the perceived usefulness of mobile technology in physics learning: A pedagogical perspective. Paper presented to the 2020 annual conference of the National Association of Research in Science Teaching, Portland, OR (Conference canceled)
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Zhai, X., Haudek, K., Shi, L., Nehm, R., Urban-Lurain, M. (2020). A Framework to Conceptualize Machine Learning-based Science Assessments. Paper presented to the 2020 annual conference of the National Association of Research in Science Teaching, Portland, OR (Conference canceled)
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Shi, L., Kopcha, T.J.(Under review). Understanding the pedagogical role's moderator effect of mobile learning on students science achievement: a meta-analysis. Paper submitted to the 2021 annual conference of the Association for Educational Communications and Technology.
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Manuscript under Preparation
Shi, L., Kopcha, T.J., How Does Pedagogy Role Moderator Mobile Learning Effect on Student Science Achievement: a Meta-analysis.
Service
Journal Reviewer
2020 Journal of Science Education and Technology
Skills
Data analysis
Using Machine Learning to do data analysis, such as categorical data, continuous data, text data and image data.​
Using R, SPSS, Winsteps, Facets softwares to conduct various quantitative data analysis, such as meta-analysis, ANOVA, ANCOVA, Regression, Rasch analysis, Factor analysis, SEM.
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Softwares
Adobe Photoshop, iMovie, Audacity, Unity 3D, Blender
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Programing
R, Python, C#