• Ph.D. in Measurement, Evaluation, and Data Science, University of Alberta, 2021
• M.Ed. in Educational Measurement, Beijing Normal University, 2017
• B.S. in Psychology, Beijing Normal University, 2014

• Educational Data Mining
• Learning Analytics
• Computer-Based Assessments for Learning
• Data Science in Education

• Assistant Professor, University of Macau, 09/2021-present

For an updated list of publications, please visit my Google Scholar Profile at https://scholar.google.com/citations?user=thZfGfEAAAAJ&hl=en

Referred Journal Articles

• Chen, F., Lu, C., Cui, Y., & Gao, Y. (2023). Learning outcome modeling in computer-based assessments for learning: A sequential deep collaborative filtering approach. IEEE Transactions on Learning Technologies, 16(2), 243–255. https://doi.org/10.1109/TLT.2022.3224075
• Cui, Y., Chen, F., Lutsyk, A., Leighton, J. P., & Cutumisu, M. (2023). Data literacy assessments: A systematic literature review. Assessment in Education: Principles, Policy & Practice, 30(1), 76–96. https://doi.org/10.1080/0969594X.2023.2182737
• Chen, F., Sakyi, A., & Cui, Y. (2022). Identifying key contextual factors of top performers in digital reading through a machine learning approach. Journal of Educational Computing Research, 60(7), 1763–1795. https://doi.org/10.1177/07356331221083215
• Gao, Y., Cui, Y., Bulut, O., Zhai, X., & Chen, F. (2022). Examining adults’ web navigation patterns in multi-layered hypertext environments. Computers in Human Behavior, 129, 107142. https://doi.org/10.1016/j.chb.2021.107142
• Zhao, J. L., Chen, F., & Jia, X. M. (2021). The development and validation of the doctoral student identity scale. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2021.688948
• Chen, F., Sakyi, A., & Cui, Y. (2021). Linking student, home, and school factors to reading achievement: The mediating role of reading self-efficacy. Educational Psychology. https://doi.org/10.1080/01443410.2021.1953445
• Shin, J., Chen, F., Lu, C., & Bulut, O. (2021). Analyzing students’ performance in computerized formative assessments to optimize teacher’s test administration decisions using deep learning frameworks. Journal of Computers in Education. https://doi.org /10.1007/s40692-021-00196-7
• Chen, F., & Cui, Y. (2020). LogCF: Deep collaborative filtering with process data for enhanced learning outcome modeling. Journal of Educational Data Mining, 12(4), 66– https://doi.org/10.5281/zenodo.4399685
• Chen, F., Cui, Y., & Chu, M-W. (2020). Utilizing game analytics to inform and validate digital game-based assessment with evidence-centered game design: A case study. International Journal of Artificial Intelligence in Education, 30, 481– https://doi.org/10.1007/s40593-020-00202-6
• Chen, F., & Cui, Y. (2020). Utilizing student time series behaviour in learning management systems for early prediction of course performance. Journal of Learning Analytics, 7(2), 1–17. https://doi.org/10.18608/jla.2020.72.1
• Cui, Y., Chen, F., & Shiri, A. (2020). Scale up predictive models for early detection of at-risk students: A feasibility study. Information and Learning Sciences, 121(3/4), 97– https://doi.org/10.1108/ILS-05-2019-0041
• Chen, F., & Cui, Y. (2020). Investigating the relation of perceived teacher unfairness to science achievement by hierarchical linear modeling in 52 countries and economies. Educational Psychology, 40(3), 273– https://doi.org/10.1080/01443410.2019.1652248
• Chen, F., Yang, H., Bulut, O., Cui, Y., & Xin, T. (2019). Examining the relation of personality factors to substance use disorder by explanatory item response modeling of DSM-5 symptoms. PLoS ONE, 14(6), e0217630. https://doi.org/1371/journal.pone.0217630
• Cui, Y., Chen, F., Shiri, A., & Fan, Y. (2019). Predictive analytic models of student success in higher education: A review of methodology. Information and Learning Sciences, 120(3/4), 208– https://doi.org/10.1108/ILS-10-2018-0104
• Cui, Y., Chu, M-W., & Chen, F. (2019). Analyzing student process data in game-based assessments with Bayesian knowledge tracing and dynamic Bayesian network. Journal of Educational Data Mining, 11(1), 80– https://doi.org/10.5281/zenodo.3554751
• Yang, H., Chen, F., Liu, X., & Xin, T. (2019). An item response theory analysis of DSM-5 heroin use disorder in a clinical sample of Chinese adolescents. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2019.02209
• Chen, F., Liu, Y., Xin, T., & Cui, Y. (2018). Applying the M₂ statistic to evaluate the fit of diagnostic classification models in the presence of attribute hierarchies. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2018.01875
• Chen, F., Yan, Y., & Xin, T. (2017). Developing a learning progression for number sense based on the rule space model in China. Educational Psychology, 37, 128–144. https://doi.org/10.1080/01443410.2016.1239817
• Chen, F., Zhang, S., Guo, Y., & Xin, T. (2017). Applying the rule space model to develop a learning progression for thermochemistry. Research in Science Education, 47, 1357-1378. https://doi.org/1007/s11165-016-9553-7
• Zhang, S., Du, J., Chen, P., Xin, T., & Chen, F. (2017). Using procedure based on item response theory to evaluate classification consistency indices in the practice of large-scale assessment. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2017.01676
• Ouyang, X., Xin, T., & Chen, F. (2016). Construct validity of the children’s coping strategies scale (CCSS): A bifactor model approach. Psychological Reports, 118, 199–218. https://doi.org/10.1177/0033294116628362
• Chen, F., Xin, T., Liu, Y., Liu, T., & Tian, W. (2016). Model-data fit test methods and statistics for cognitive diagnostic models. Advances in Psychological Sciences, 24, 1946–1960. https://doi.org/3724/SP.J.1042.2016.01946 (in Chinese)
• Gao, Y., Chen, F., Xin, T., Zhan, P., Jiang Y. (2017). Applying psychometric models in learning progressions studies: Theory, method and breakthrough. Advances in Psychological Sciences, 25, 1623–1630. https://doi.org/3724/SP.J.1042.2017.01623 (in Chinese)
• Xu, J., Zhou, H., Li, W., Chen, F., & Zhang, W. (2014). Interviewer’s rating and influencing factors in structural interviews. Advances in Psychological Sciences, 22, 357–368. https://doi.org/3724/SP.J.1042.2014.00357 (in Chinese)

• Alberta Innovates Graduate Student Scholarship, Alberta Innovates, 2020
• Alberta Graduate Excellence Scholarship, University of Alberta, 2020
• Chinese Government Award for Outstanding Graduate Students Studying Abroad, China Scholarship Council, 2020
• Professor Mian Muhammad Afzal International Graduate Scholarship in Education, University of Alberta, 2018
• University of Alberta Doctoral Recruitment Scholarship, University of Alberta, 2017
• Honor of Outstanding Graduates, Beijing Normal University, 2017
• China National Scholarship, Ministry of Education, China, 2016
• Liyun Rank 1 Graduate Scholarship, Beijing Normal University, 2016
• Huawei Graduate Scholarship, Huawei Technologies Co., Ltd., 2016