Publications

2025

Students' study activities before and after exam deadlines as predictors of performance in STEM courses: A multi-source data analysis
Students' study activities before and after exam deadlines as predictors of performance in STEM courses: A multi-source data analysis
Luise von Keyserlingk, Fani Lauermann, Qiujie Li, Renzhe Yu, Charlott Rubach, Richard Arum, Jutta Heckhausen
Learning and Individual Differences  ·  01 Jan 2025  ·  doi:10.1016/j.lindif.2024.102598

2024

Course-Skill Atlas: A national longitudinal dataset of skills taught in U.S. higher education curricula
Course-Skill Atlas: A national longitudinal dataset of skills taught in U.S. higher education curricula
Alireza Javadian Sabet, Sarah H. Bana, Renzhe Yu, Morgan R. Frank
Scientific Data  ·  04 Oct 2024  ·  doi:10.1038/s41597-024-03931-8
The life cycle of large language models in education: A framework for understanding sources of bias
The life cycle of large language models in education: A framework for understanding sources of bias
Jinsook Lee, Yann Hicke, Renzhe Yu, Christopher Brooks, René F. Kizilcec
British Journal of Educational Technology  ·  12 Jul 2024  ·  doi:10.1111/bjet.13505
Technology-Based Instructional Strategies Show Promise in Improving Self-Regulated Learning Skills at Broad-Access Postsecondary Institutions
Technology-Based Instructional Strategies Show Promise in Improving Self-Regulated Learning Skills at Broad-Access Postsecondary Institutions
Renzhe Yu, Hui Yang, Xiaoying Lin, Chengyuan Yao, Paul Burkander, Krystal Thomas, Jessica Mislevy
Proceedings of the Eleventh ACM Conference on Learning @ Scale  ·  09 Jul 2024  ·  doi:10.1145/3657604.3664675
Fairness Hub Technical Briefs: Mitigation Strategies of Distribution Shift
Fairness Hub Technical Briefs: Mitigation Strategies of Distribution Shift
Nicolas Acevedo, Carmen Cortez, Christopher Brooks, René F. Kizilcec, Renzhe Yu
Learning Engineering Virtual Institute  ·  01 Jun 2024  ·  doi:10.35542/osf.io/pvbmt
Fairness Hub Technical Briefs: Definition and Detection of Distribution Shift
Fairness Hub Technical Briefs: Definition and Detection of Distribution Shift
Nicolas Acevedo, Carmen Cortez, Chris Brooks, Rene Kizilcec, Renzhe Yu
Learning Engineering Virtual Institute  ·  24 May 2024  ·  arxiv:2405.14186
Temporal and Between-Group Variability in College Dropout Prediction
Temporal and Between-Group Variability in College Dropout Prediction
Dominik Glandorf, Hye Rin Lee, Gabe Avakian Orona, Marina Pumptow, Renzhe Yu, Christian Fischer
Proceedings of the 14th Learning Analytics and Knowledge Conference  ·  18 Mar 2024  ·  doi:10.1145/3636555.3636906
Contexts Matter but How? Course-Level Correlates of Performance and Fairness Shift in Predictive Model Transfer
Contexts Matter but How? Course-Level Correlates of Performance and Fairness Shift in Predictive Model Transfer
Zhen Xu, Joseph Olson, Nicole Pochinki, Zhijian Zheng, Renzhe Yu
Proceedings of the 14th Learning Analytics and Knowledge Conference  ·  18 Mar 2024  ·  doi:10.1145/3636555.3636936

2023

Fairness Hub Technical Briefs: AUC Gap
Fairness Hub Technical Briefs: AUC Gap
Jinsook Lee, Chris Brooks, Renzhe Yu, Rene Kizilcec
Learning Engineering Virtual Institute  ·  27 Sep 2023  ·  arxiv:2309.12371
Fairness Hub Technical Briefs: Overview of Bias Mitigation Strategies
Fairness Hub Technical Briefs: Overview of Bias Mitigation Strategies
Jinsook Lee, Christopher Brooks, Renzhe Yu, René F. Kizilcec
Learning Engineering Virtual Institute  ·  23 Sep 2023  ·  doi:10.35542/osf.io/jtb5n
Semantic Topic Chains for Modeling Temporality of Themes in Online Student Discussion Forums
Semantic Topic Chains for Modeling Temporality of Themes in Online Student Discussion Forums
Harshita Chopra, Yiwen Lin, Mohammad Amin Samadi, Jacqueline G. Cavazos, Renzhe Yu, Spencer Jaquay, Nia Nixon
Proceedings of the 16th International Conference on Educational Data Mining  ·  05 Jul 2023  ·  doi:10.5281/zenodo.8115691
What can digital trace data tell us about postsecondary students' academic success? An overview of the literature and an illustrative example
What can digital trace data tell us about postsecondary students' academic success? An overview of the literature and an illustrative example
Luise von Keyserlingk, Fani Lauermann, Renzhe Yu, Charlott Rubach, Richard Arum
Jahrbuch der Schulentwicklung (Band 23)  ·  21 Jun 2023  ·  isbn:978-3-7799-7718-6
Cross-Institutional Transfer Learning for Educational Models: Implications for Model Performance, Fairness, and Equity
Cross-Institutional Transfer Learning for Educational Models: Implications for Model Performance, Fairness, and Equity
Joshua Gardner, Renzhe Yu, Quan Nguyen, Christopher Brooks, Rene Kizilcec
2023 ACM Conference on Fairness, Accountability, and Transparency  ·  12 Jun 2023  ·  doi:10.1145/3593013.3594107

2022

Salient syllabi: Examining design characteristics of science online courses in higher education
Salient syllabi: Examining design characteristics of science online courses in higher education
Christian Fischer, Peter McPartlan, Gabe Avakian Orona, Renzhe Yu, Di Xu, Mark Warschauer
PLOS ONE  ·  03 Nov 2022  ·  doi:10.1371/journal.pone.0276839
Large-Scale Student Data Reveal Sociodemographic Gaps in Procrastination Behavior
Large-Scale Student Data Reveal Sociodemographic Gaps in Procrastination Behavior
Sunil Sabnis, Renzhe Yu, René F. Kizilcec
Proceedings of the Ninth ACM Conference on Learning @ Scale  ·  01 Jun 2022  ·  doi:10.1145/3491140.3528285
Risk and Protective Factors of College Students’ Psychological Well-Being During the COVID-19 Pandemic: Emotional Stability, Mental Health, and Household Resources
Risk and Protective Factors of College Students’ Psychological Well-Being During the COVID-19 Pandemic: Emotional Stability, Mental Health, and Household Resources
Julia Moeller, Luise von Keyserlingk, Marion Spengler, Hanna Gaspard, Hye Rin Lee, Katsumi Yamaguchi-Pedroza, Renzhe Yu, Christian Fischer, Richard Arum
AERA Open  ·  11 Mar 2022  ·  doi:10.1177/23328584211065725

2021

A Research Framework for Understanding Education-Occupation Alignment with NLP Techniques
A Research Framework for Understanding Education-Occupation Alignment with NLP Techniques
Renzhe Yu, Subhro Das, Sairam Gurajada, Kush Varshney, Hari Raghavan, Carlos Lastra-Anadon
Proceedings of the 1st Workshop on NLP for Positive Impact  ·  05 Aug 2021  ·  doi:10.18653/V1/2021.NLP4POSIMPACT-1.11
Should College Dropout Prediction Models Include Protected Attributes?
Should College Dropout Prediction Models Include Protected Attributes?
Renzhe Yu, Hansol Lee, René F. Kizilcec
Proceedings of the Eighth ACM Conference on Learning @ Scale  ·  08 Jun 2021  ·  doi:10.1145/3430895.3460139
Construction of Weighted Course Co-Enrollment Network
Construction of Weighted Course Co-Enrollment Network
Xunfei Li, Renzhe Yu
Proceedings of the Workshop on Using Network Science in Learning Analytics: Building Bridges towards a Common Agenda  ·  12 Apr 2021  ·  [no id info]
How Universities Can Mind the Skills Gap (Higher Education and the Future of Work)
How Universities Can Mind the Skills Gap (Higher Education and the Future of Work)
Carlos X. Lastra-Anadon, Subhro Das, Kush R. Varshney, Hari Raghavan, Renzhe Yu
Center for the Governance of Change, IE University  ·  01 Apr 2021  ·  [no id info]

2020

Opening the black box: user-log analyses of children’s e-Book reading and associations with word knowledge
Opening the black box: user-log analyses of children’s e-Book reading and associations with word knowledge
Osman Umarji, Stephanie Day, Ying Xu, Elham Zargar, Renzhe Yu, Carol Connor
Reading and Writing  ·  18 Aug 2020  ·  doi:10.1007/s11145-020-10081-x
Interpretable Models Do Not Compromise Accuracy or Fairness in Predicting College Success
Interpretable Models Do Not Compromise Accuracy or Fairness in Predicting College Success
Catherine Kung, Renzhe Yu
Proceedings of the Seventh ACM Conference on Learning @ Scale  ·  12 Aug 2020  ·  doi:10.1145/3386527.3406755
Towards Accurate and Fair Prediction of College Success: Evaluating Different Sources of Student Data
Towards Accurate and Fair Prediction of College Success: Evaluating Different Sources of Student Data
Renzhe Yu, Qiujie Li, Christian Fischer, Shayan Doroudi, Di Xu
Proceedings of the 13th International Conference on Educational Data Mining  ·  10 Jul 2020  ·  [no id info]
LIWCs the Same, Not the Same: Gendered Linguistic Signals of Performance and Experience in Online STEM Courses
LIWCs the Same, Not the Same: Gendered Linguistic Signals of Performance and Experience in Online STEM Courses
Yiwen Lin, Renzhe Yu, Nia Dowell
Proceedings of the 21st International Conference on Artificial Intelligence in Education  ·  30 Jun 2020  ·  doi:10.1007/978-3-030-52237-7_27
The benefits and caveats of using clickstream data to understand student self-regulatory behaviors: opening the black box of learning processes
The benefits and caveats of using clickstream data to understand student self-regulatory behaviors: opening the black box of learning processes
Rachel Baker, Di Xu, Jihyun Park, Renzhe Yu, Qiujie Li, Bianca Cung, Christian Fischer, Fernando Rodriguez, Mark Warschauer, Padhraic Smyth
International Journal of Educational Technology in Higher Education  ·  14 Apr 2020  ·  doi:10.1186/s41239-020-00187-1
Mining Big Data in Education: Affordances and Challenges
Mining Big Data in Education: Affordances and Challenges
Christian Fischer, Zachary A. Pardos, Ryan Shaun Baker, Joseph Jay Williams, Padhraic Smyth, Renzhe Yu, Stefan Slater, Rachel Baker, Mark Warschauer
Review of Research in Education  ·  01 Mar 2020  ·  doi:10.3102/0091732X20903304

2019

Quasi-Experimental Evidence of a School Equalization Reform on Housing Prices in Beijing
Quasi-Experimental Evidence of a School Equalization Reform on Housing Prices in Beijing
Wei Ha, Renzhe Yu
Chinese Education & Society  ·  04 Jul 2019  ·  doi:10.1080/10611932.2019.1667681
Student Behavioral Embeddings and Their Relationship to Outcomes in A Collaborative Online Course
Student Behavioral Embeddings and Their Relationship to Outcomes in A Collaborative Online Course
Renzhe Yu, Zachary Pardos, John Scott
Proceedings of the Workshop on Learning Analytics: Building Bridges Between the Education and the Computing Communities  ·  02 Jul 2019  ·  [no id info]
Construction of Weighted Course Co-Enrollment Network
Construction of Weighted Course Co-Enrollment Network
Renzhe Yu
Proceedings of the Workshop on Connectivism: Using Learning Analytics to Operationalize A Research Agenda  ·  04 Mar 2019  ·  [no id info]
Utilizing Learning Analytics to Map Students' Self-Reported Study Strategies to Click Behaviors in STEM Courses
Utilizing Learning Analytics to Map Students' Self-Reported Study Strategies to Click Behaviors in STEM Courses
Fernando Rodriguez, Renzhe Yu, Jihyun Park, Mariela Janet Rivas, Mark Warschauer, Brian K. Sato
Proceedings of the 9th International Conference on Learning Analytics & Knowledge  ·  04 Mar 2019  ·  doi:10.1145/3303772.3303841

2018

Understanding Student Procrastination via Mixture Models
Understanding Student Procrastination via Mixture Models
Jihyun Park, Renzhe Yu, Fernando Rodriguez, Rachel Baker, Padhraic Smyth, Mark Warschauer
Proceedings of the 11th International Conference on Educational Data Mining  ·  16 Jul 2018  ·  [no id info]
Representing and predicting student navigational pathways in online college courses
Representing and predicting student navigational pathways in online college courses
Renzhe Yu, Daokun Jiang, Mark Warschauer
Proceedings of the Fifth Annual ACM Conference on Learning at Scale  ·  26 Jun 2018  ·  doi:10.1145/3231644.3231702