朱孟潇
E-Mail：mxzhu@ustc.edu.cn
个人主页：http://staff.ustc.edu.cn/~mxzhu
主要研究方向：大数据分析、社会网络分析、计算社会科学、在线社交媒体分析、个性化学习与学习分析、智能教育与测评
朱孟潇，中国科学技术大学特任研究员，博导。2001年获得中科大科技英语（理）及计算机应用（工）学士学位，2004年获得中科大计算机科学硕士学位。2007年获得美国伊利诺伊大学香槟分校（University of Illinois Urbana-Champaign, UIUC）传播学硕士, 2012年获得美国西北大学（Northwestern University）工业工程与管理博士学位。2012至13年在美国罗格斯大学（Rutgers University）的传播学院和计算机学院，从事交叉学科的博士后研究工作。自2013年起至2020年，在美国教育考试中心（Educational Testing Service, ETS）担任研究科学家。于2020年12月全职回国工作，任中国科学技术大学人文与社会科学学院科技传播系任特任研究员，并担任管理科学与工程专业博导。将信息科学的技术与人文社会科学的理论和方法相结合，从社会科学研究的视角出发，从事大数据分析、个性化学习与分析、以及计算社会科学等方向的科研工作。主要研究方向包括，基于社交媒体与教育大数据的行为刻画研究，社会网络分析的方法与协同合作机制的研究，以及网络传播对科技和政策的影响等。相关研究成果，包括合著专著一本，国际会议、杂志论文及专著章节近30 篇；应邀参加国际会议并宣读论文30 余次，并曾主持和参与十多个大型科研项目。目前担任Network Science, Computers and Education, JEM, JCMC, CHB等多个国际学术期刊的审稿人。主持国家自然科学基金面上项目，科技部国家重点研发项目等多项国家级、省部级科研项目。获得多项省部级人才计划支持，并获得中科大 “学术领军人才培养计划” 支持。
主要论著：
Book
von Davier, A. A., Zhu, M., & Patrick, K. (2017). Innovative Assessment of Collaboration. Springer.
In Refereed Journals, Peer-Reviewed Conference Proceedings, and Book Chapters
[1] Zhu, M. (2021). Chapter 11. Social Networks Analysis. In A. A. von Davier, B. Mislevy, & J. Hao (Eds.), Computational Psychometrics: New Methods for a New Generation of Educational Assessment. Springer.
[2] Zhu, M., Liu, O. L., & Lee, H.-S. (2020). Using cluster analysis to explore students’ interactions with automated feedback in an online earth science task. The International Journal of Quantitative Research in Education, 5(2), 111-135.
[3] Zhu, M., Andrews-Todd, J., & Zhang, M. (2020). Application of Network Analysis in Understanding Collaborative Problem Solving Processes and Skills. In H. Jiao & R. W. Lissitz (Eds.), Innovative Psychometric Modeling and Methods (pp. 69–89). Charlotte, NC: Information Age Publisher.
[4] Zhu, M., Liu, O. L., & Lee, H.-S. (2020). The effect of automated feedback on revision behavior and learning gains in formative assessment of scientific argument writing. Computers & Education, 143, 103668.
[5] Zhu, M., & Todd, J. A. (2019). Understanding the Connections of Collaborative Problem Solving Skills in a Simulation-based Task through Network Analysis. In The Proceedings of the International Conference on Computer Supported Collaborative Learning (CSCL 2019). Lyon, France.
[6] Zhu, M., Zhang, M., & Deane, P. (2019). Analysis of Keystroke Sequences in Writing Logs. ETS Research Report Series (RR-19-11).
[7] Zhang, M., Zhu, M., Deane, P., & Guo, H. (2019). Identifying and Comparing Writing Process Patterns Using Keystroke Logs. In Quantitative Psychology: The 83nd Annual Meeting of the Psychometric Society, New York. New York: Springer.
[8] Zhu, M., & Zhang, M. (2017). Network analysis of conversation data for engineering professional skills assessment. ETS Research Report Series (RR-17-59).
[9] Zhu, M., Lee, H.-S., Wang, T., Liu, O. L., Belur, V., & Pallant, A. (2017). Investigating the impact of automated feedback on students’ scientific argumentation. International Journal of Science Education, 39(12), 1648–1668.
[10] Zhu, M., & Bergner, Y. (2017). Network Models for Teams with Overlapping Membership. In A. A. von Davier, M. Zhu, & P. Kyllonen (Eds.), Innovative Assessment of Collaboration. Springer.
[11] Zhu, M., Shu, Z., & von Davier, A. A. (2016). Using networks to visualize and analyze process data for educational assessment. Journal of Educational Measurement, 53(2), 190–211.
[12] Bergner, Y., Andrews, J. J., Zhu, M., & Gonzales, J. E. (2016). Agent-based modeling of collaborative problem solving. ETS Research Report Series (RR-16-27). Princeton, NJ.
[13] Zhu, M., Kuskova, V., Wasserman, S., & Contractor, N. (2016). Correspondence Analysis of Multirelational Multilevel Network Affiliations: Analysis and Examples. In E. Lazega & T. Snijders (Eds.), Multilevel Network Analysis for the Social Sciences - Theory, Methods and Applications. Springer. 145–172.
[14] Zhu, M., Bergner, Y., Zhang, Y., Baker, R., Wang, Y., Paquette, L., & Barnes, T. (2016). Longitudinal Engagement, Performance, and Social Connectivity : a MOOC Case Study Using Exponential Random Graph Models. In Proceeding of the 6th International Learning Analytics and Knowledge Conference (LAK ’16). Edinburgh, UK:ACM.
[15] Zhu, M., & Feng, G. (2015). An exploratory study using social network analysis to model eye movements in mathematics problem solving. In Proceeding of the 5th International Learning Analytics and Knowledge Conference (LAK ’15). Poughkeepsie, NY: ACM.
[16] Zhu, M., Huang, Y., & Contractor, N. S. (2013). Motivations for self-assembling into project teams. Social Networks, 35(2), 251-264.