Fu Chen

Fu Chen

Ph.D. Candidate in Measurement, Evaluation, and Data Science

University of Alberta

About me

I am currently a PhD candidate in Measurement, Evaluation, and Data Science at the University of Alberta. Before studying at U of A, I earned my bachelor’s and master’s degrees from Beijing Normal University, China. I have received training in psychology, psychometric measurement, and data science, and have been an active researcher in the areas of psychoeducational studies, predictive learning analytics, and cognitive modeling.

My primary focus of current research is on the intersection of psychometrics and data science. Specifically, I am interested in developing and applying novel computational methods (e.g., deep learning) to uncover and facilitate student learning using both product and process data on student interactions with digital learning environments. I am also interested in adapting data science techniques to address conventional measurement or assessment problems.

In the long term, I see myself engaged in a career devoted to active interdisciplinary research in developing and applying cutting-edge data science and psychometric techniques to decipher student learning or address complex assessment issues emerged in other settings (e.g., cognitive science, health, and business). I am looking forward to any potential collaborations.

Interests

  • Educational Data Mining
  • Learning Analytics
  • Educational Measurement

Education

  • Ph.D. in Measurement, Evaluation, and Data Science, May 2021 (expected)

    University of Alberta

  • M.Ed. in Educational Measurement, 2017

    Beijing Normal University

  • B.S. in Psychology, 2014

    Beijing Normal University

Selected Awards & Scholarships

Alberta Innovates Graduate Student Scholarship

The scholarship is a full scholarship for graduate students at three Alberta universities to undertake full-time research in the areas of Information and Communications Technology (ICT), Nanotechnology, and Omics.

Alberta Graduate Excellence Scholarship

The scholarship recognizes and incents the best and the brightest students pursuing graduate studies in Alberta.

Chinese Government Award for Outstanding Graduate Students Abroad

The scholarship is considered the highest award given by Chinese government to graduate students studying outside China.

Professor Mian Muhammad Afzal International Graduate Scholarship in Education

The scholarship recognizes a graduate student with superior academic achievement annually in the Faculty of Education

University of Alberta Doctoral Recruitment Scholarship

The scholarship recognizes superior students at the doctoral level who have the potential to contribute to the University of Alberta’s community and research.

China National Scholarship

The scholarship recognizes the top 3% of master’s students at Beijing Normal University (BNU) annually. It is the most prestigious scholarship operated by the central government of China.

Liyun Rank 1 Graduate Scholarship

The scholarship recognizes five outstanding graduate students at BNU every two years.

Huawei Graduate Scholarship

The scholarship recognizes six outstanding graduate students at BNU annually.

Referred Journal Articles

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(2020). LogCF: Deep collaborative filtering with process data for enhanced learning outcome modeling. Journal of Educational Data Mining.

(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.

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(2020). Scale up predictive models for early detection of at-risk students: A feasibility study. Information and Learning Sciences.

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(2019). An item response theory analysis of DSM-5 heroin use disorder in a clinical sample of Chinese adolescents. Frontiers in Psychology.

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(2019). Predictive analytic models of student success in higher education: A review of methodology. Information and Learning Sciences.

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(2017). Applying the rule space model to develop a learning progression for thermochemistry. Research in Science Education.

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(2017). Applying psychometric models in learning progressions studies: Theory, method and breakthrough. Advances in Psychological Science.

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(2016). Model-data fit test methods and statistics for cognitive diagnostic models. Advances in Psychological Science.

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(2014). Interviewer’s rating and influencing factors in structural interviews. Advances in Psychological Science.

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Conference Presentations

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Automating test administration decisions in computerized formative assessment

Paper to be presented at the 2020 Annual Meeting of the National Council on Measurement in Education

Examining relation of information and communication technology to collaborative problem solving by hierarchical linear modeling

Paper to be presented at the 2020 Annual Meeting of the National Council on Measurement in Education

Predictive analytics of temporal behavior to automate formative feedback on course performance

Paper to be presented at the 2020 Annual Meeting of the National Council on Measurement in Education

Analyzing student process data with Bayesian knowledge tracing and dynamic Bayesian network

Annual Meeting of the National Council on Measurement in Education (Symposium Canceled due to COVID-19)

Detection of aberrant response patterns using discrete variational autoencoder

Annual Meeting of the National Council on Measurement in Education (Symposium Canceled due to COVID-19)

Utilizing game analytics to inform digital game-based assessment design

Annual Meeting of the National Council on Measurement in Education (Symposium Canceled due to COVID-19)

Validity of process-based competency outcome claims using think-a-loud data and evidence-trace files

Annual Meeting of the National Council on Measurement in Education (Symposium Canceled due to COVID-19)

Identifying influential contextual factors of online reading literacy through a machine learning approach

Paper to be presented at the 2020 annual meeting of American Educational Research Association, San Francisco, CA http://tinyurl.com/qq724ky (Conference canceled due to COVID-19)

Influential factors contributing to students’ mathematics achievement (PISA 2012): A comparison between Alberta and Quebec

Poster presented at the 2019 Alberta Research Network Meeting, Edmonton, AB

Enhancing student success through predictive learning analytics

Paper presented at the 2019 Festival of Teaching and Learning at University of Alberta, Edmonton, AB

Prenatal alcohol exposure and its relation to intelligence, executive functions, and antisocial and prosocial outcomes

Paper presented at the European Conference on Fetal Alcohol Spectrum Disorders 2018, Berlin, German

Applying M2 statistic to evaluate the fit of hierarchical diagnostic classification models

Paper presented at the 2017 Annual Meeting of the National Council on Measurement in Education, San Antonio, TX

Applying the rule space model to develop a learning progression of thermochemistry

Paper presented at the 80th Annual Meeting of the Psychometric Society, Beijing, China

The effects of interviewees’ nonverbal clues on interviewers’ ratings

Paper presented at the 16th National Academic Congress of Psychology, Nanjing, China

Selected Projects

Deep Learning-Based Collaborative Filtering for Enhanced Learning Outcome Modeling

Given the importance of accurate prediction of learners’ learning outcomes (e.g., correctly solving a problem or not) for successful personalized learning, this project aims to develop novel cognitive modeling methods to predict learners’ learning outcomes on future problems by exploiting their problem-solving process and sequential problem-solving results based on a machine learning approach named collaborative filtering (CF).

Informing and Validating Digital Game-Based Assessment: Game Analytics of Process Data

Investigate and demonstrate how to apply machine learning approaches to analyze student process data for validating and informing digital game-based assessments with an evidence-centered game design.

Predictive Modeling of Course Performance based on Student Temporal Behaviors in Learning Management Systems

Develop generic and simple modeling frameworks based on recurrent neural networks for early detection of at-risk students using their daily behaviors in the learning management system.

Influential Contextual Factors of Academic Success: Evidence from International Large-Scale Assessments

Investigate what contributes to student success in science, mathemetics, and reading through advanced statistical or machine learning analyses of PISA, PIRLS, and TIMSS data.

Contact

  • 6-110 Education Centre North, University of Alberta, 11210 87 Ave NW, Edmonton, AB T6G 2G5