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RENE F. KIZILCEC

208 Gates Hall

107 Hoy Rd, Ithaca, NY 14853

+1 (607) 255-8327

kizilcec@cornell.edu

http://rene.kizilcec.com/

http://learning.cis.cornell.edu/

EMPLOYMENT

2024 – present        Associate Professor, Department of Information Science, Cornell University
                Graduate field member, Communication (since 2021)
                Graduate field member, Physics (since 2021)
                Minor graduate field member, Data Science (since 2020)

2018 – 2024        Assistant Professor, Department of Information Science, Cornell University

2017 – 2018        Assistant Research Professor, School of Computing, Informatics, and Decision Systems
                Engineering, Arizona State University

EDUCATION

Ph.D., Communication, Stanford University, 2017

M.S., Statistics, Stanford University, 2015

B.A. (1st class honors), Philosophy and Economics, University College London, 2011

SELECTED AWARDS

2025        LEAP Fellow, MIT Solve

2024        Alfred P. Sloan Research Fellow (Computer Science)

2024        Ann S. Bowers Research Excellence Award, Bowers College, Cornell University

2023        Best Paper Award (83 submissions, 23 accepted, 2 awards), ACM Learning at Scale

2023        Community-Engaged Practice and Innovation Award, Einhorn Center, Cornell University

2023        Best Short Paper Honorable Mention, Conference on Learning Analytics & Knowledge

2023        LEAP Fellow, MIT Solve

2022        Best UG Paper Award (72 submissions, 22 accepted, 1 award), ACM Learning at Scale

2021        Jacobs Foundation Research Fellow

2021        Best Paper Honorable Mention (63 subm., 19 accepted, 3 nominated), ACM Learning at Scale

2021        Best UG Paper Award (24 submissions, 10 accepted, 1 award), ACM Learning at Scale

2021        Outstanding Reviewer 2020, American Education Research Association (AERA)

2019        Best Paper Award (70 submissions, 24 accepted, 2 awards), ACM Learning at Scale

2018        Best Paper Award (58 submissions, 24 accepted, 1 award), ACM Learning at Scale

2017        Best Paper Award (105 submissions, 14 accepted, 1 award), ACM Learning at Scale

2017        Nathan Maccoby Outstanding Dissertation Award, Stanford University

2015        Computational Social Science Fellowship, Stanford University ($10,000 research funding)

2014        Stanford Interdisciplinary Graduate Fellowship (Ph.D. funding for 3 years)

SELECTED GRANTS

Chan Zuckerberg Initiative, “National Tutoring Observatory” (2 years; $1,000,000; PI Rene Kizilcec, Co-PIs Justin Reich, Ken Koedinger, Rachel Slama), 2025

Gates Foundations, “National Tutoring Observatory” (2 years; $3,921,000; PI Rene Kizilcec, Co-PIs Justin Reich, Ken Koedinger, Rachel Slama), 2024

Alfred P. Sloan Research Fellowship Program 2024-26 (2 years; $75,000), 2024

NSF, “CAREER: Improving educators trust in and effective uses of predictive learning analytics to support students” (5 years; $807,582; PI Rene Kizilcec), 2023

Schmidt Futures Foundation, “Fairness Analysis & Transfer Learning Hub” (2 years; $475,000; PI Kizilcec; Co-PIs Chris Brooks, Renzhe Yu), 2022

CIFAR and Jacobs Foundation, “Developing a Universal Framework for Teachers’ Adoption of Best Practices” (2 years; Canadian $50,000; PI Rene Kizilcec, Co-PIs Allyson Mckey, Lisa Bardach, Jamie Jirout, Dana McCoy, Luca Maria Pesando, David Yeager), 2022

Cornell-UCL Global Strategic Collaboration Award, “The Role of Transparency Frames in Human-AI Interaction and Trust” (1 year; $5,000 + £4,000; Co-PIs Rene Kizilcec, Mutlu Cukurova), 2022

USyd-Cornell Partnership Collaboration Award, “Testing a Framework for designing and evaluating scalable online assessment in a global higher education context”, (1 year; $7,500 + AUD 10,000; Co-PIs Rene Kizilcec, Elaine Huber), 2022

Jacobs Foundation Research Fellowship Program 2022-24 (3 years; CHF 165,000), 2021

Schmidt Futures Foundation, “Instrumenting the Realizeit Platform” (2 years; $500,000; PI Rene Kizilcec; Co-PI Ryan Baker), 2021

Google Award for Inclusion Research Program, “Investigating How to Mitigate Bias in Predictive Models of Student Success Across Diverse Institutions” (1 year, $60,000; Co-PIs Chris Brooks, Rene Kizilcec), 2021

Cornell Center for Social Science Small Grant, “How University Status Impacts the Stigma Attached to Online Degrees” (1 year; $10,000; Co-PIs Heeyon Kim, Rene Kizilcec), 2021

Cornell Center for Social Science Conference Grant, “Learning at Scale Conference at Cornell Tech” (1 year; $3,000), 2021

NSF, “Medium: Deterring objectionable behavior and fostering emergent norms in social media conversations” (4 years; $1,197,740; PI Drew Margolin; Co-PIs Rene Kizilcec, Natalie Bazarova, Vanessa Bohns, Dominic DiFranzo), 2021

Northeastern Center for Inclusive Computing Data Grant (2 years; $60,000; PI Hakim Weatherspoon; Co-PI Kizilcec), 2021

Cornell Center for Social Science Small Grant, “Content & Impact of Diversity Statements in Course Syllabi” (1 year; $12,000; PI Rene Kizilcec), 2020

Cornell Engaged Development Grant, “Plant-rich Diet” (2 year; $60,000; PI Marianne Krasny; Co-PI Rene Kizilcec), 2020

Mindset Scholars Network/Gates, “Learning Environments and the Mindsets and Performance of Students Within Them” (1.5 years; $75,000; PI Neil Lewis Jr.; Co-PI Rene Kizilcec), 2019

Cornell Active Learning Initiative, “Promoting Active Learning in Large Information Science Courses” (3 years; $950,000; PI Steven Jackson; Co-PI Rene Kizilcec), 2019

Cornell China Center Innovation Grant, “Environment and Education SDGs: Building capacity for local environmental practice through online learning in China” (2 years; $60,000; PIs Marianne Krasny and Rene Kizilcec), 2019

Cornell Engaged Planning Grant, “Teaching Programming through Semantic Gamification” (1 year; $30,000; PI Francois Guimbretiere; Co-PIs Rene Kizilcec and Andrew Myers), 2019

Cornell Institute for the Social Sciences Collaborative Project, “Prosocial Behavior in the Digital Age” (3 years; PIs Natalie Bazarova, Drew Margolin; Co-PIs Vanessa Bohns, Rene Kizilcec, Janis Whitlock), 2018

PUBLICATIONS

Google Scholar (2/5/2025): 9597 citations; 37 h-index; 66 i10-index

Peer-Reviewed Articles:  General Science Journals

Tao, Y., Viberg, O., Baker, R. S., & Kizilcec, R. F. (2024). Cultural bias and cultural alignment of large language models. PNAS nexus, 3(9), p. 346.

Kizilcec, R. F., Baker, R. B., Bruch, E., Cortes, K. E., Hamilton, L. T., Lang, D. N., Pardos, Z. A., Thompson, M. E., & Stevens, M. L. (2023). From pipelines to pathways in the study of academic progress. Science, 380(6643).

Hohenstein, J., Kizilcec, R. F., DiFranzo, D., Aghajari, Z., Mieczkowski, H., Levy, K., Naaman, M., Hancock, J., & Jung, M. F. (2023). Artificial intelligence in communication impacts language and social relationships. Scientific Reports, 13(1), 5487.

Kizilcec, R. F., Makridis, C. A., & Sadowski, K. C. (2021). Pandemic Response Policies' Democratizing Effects on Online Learning. Proceedings of the National Academy of Sciences (PNAS), 118(11).

Kizilcec, R. F. & Kambhampaty, A. (2020). Identifying course characteristics associated with sociodemographic variation in enrollments across 159 online courses from 20 institutions. PloS One 15(10), e0239766.

Kizilcec, R. F., Reich, J., Yeomans, M., Dann, C., Brunskill, E., Lopez, D., Turkay, S., Williams, J., & Tingley, D. (2020). Scaling Up Behavioral Science Interventions in Online Education. Proceedings of the National Academy of Sciences (PNAS), 117(26), 14900-14905.

Chirikov, I., Semenova, T. Maloshonok, N., Bettinger, E., Kizilcec, R. F. (2020). Online Education Platforms Scale College STEM Instruction with Equivalent Learning Outcomes at Lower Cost. Science Advances, 6(15).

Kizilcec, R. F., Saltarelli, A., Reich, J., & Cohen, G. L. (2017). Closing global achievement gaps in MOOCs. Science, 355(6322), 249.

Kizilcec, R. F. & Cohen, G. L. (2017). Eight-minute self-regulation intervention raises educational attainment at scale in individualist but not collectivist cultures. Proceedings of the National Academy of Sciences (PNAS), 114(17), 4348–4353.

Eckles, D., Kizilcec, R. F., & Bakshy, E. (2016). Estimating peer effects in networks with peer encouragement designs. Proceedings of the National Academy of Sciences (PNAS), 113(27), 7316-7322.

Peer-Reviewed Articles:  Disciplinary Journals

Kizilcec, R. F., Huber, E., Papanastasiou, E. C., Cram, A., Makridis, C. A., Smolansky, A., Zeivots, S., & Raduescu, C. (2024). Perceived impact of generative AI on assessments: Comparing educator and student perspectives in Australia, Cyprus, and the United States. Computers and Education: Artificial Intelligence, 7, 100269.

Zhao, P., Bazarova, N. N., DiFranzo, D., Hui, W., Kizilcec, R. F., & Margolin, D. (2024). Standing up to problematic content on social media: which objection strategies draw the audience’s approval?. Journal of Computer-Mediated Communication, 29(1).

Chen, Y., & Kizilcec, R. F. (2024). Showing authentic examples of academic and career trajectories to influence college students’ career exploration. Journal of Vocational Behavior, 153, 104026.

Viberg, O., Kizilcec, R. F., Wise, A. F., Jivet, I., & Nixon, N. (2024). Advancing equity and inclusion in educational practices with AI‐powered educational decision support systems (AI‐EDSS). British Journal of Educational Technology, 55(5), 1974-1981.

Viberg, O., Cukurova, M., Feldman-Maggor, Y., Alexandron, G., Shirai, S., Kanemune, S., Wasson, B., Tømte, C., Spikol, D., Milrad, M. Coelho, R., Kizilcec, R. F. (2024). What Explains Teachers’ Trust of AI in Education across Six Countries? International Journal of Artificial Intelligence in Education.

Lee, J., Hicke, Y., Yu, R., Brooks, C., & Kizilcec, R. F. (2024). The life cycle of large language models in education: A framework for understanding sources of bias. British Journal of Educational Technology, 55(5), 1982-2002.

Viberg, O., Kizilcec, R. F., Jivet, I., Monés, A. M., Oh, A., Mutimukwe, C., Hrastinski, S., & Scheffel, M. (2024). Cultural differences in students’ privacy concerns in learning analytics across Germany, South Korea, Spain, Sweden, and the United States. Computers in Human Behavior Reports, 14, 100416.

Alvero, AJ., Lee, J., Regla-Vargas, A., Kizilec, R., Joachims, T., & Antonio, A. L. (2024) Large language models, social demography, and hegemony: comparing authorship in human and synthetic text. Journal of Big Data 11, 138.

Muñoz-Najar Galvez, S., Lee, J., Alvero, AJ., Stewart, S., Kizilcec, R. F., & Desiderio, A. (2024). Artificial Communication and Media Realism in College Admissions. The Digitized Campus: Artificial Intelligence and Big Data in Higher Education.

Allen, S. E. & Kizilcec, R. F. (2024). A systemic model of academic (mis)conduct to curb cheating in higher education. Higher Education, 1-21.

Kizilcec, R. F. & Mitchell, J. C.. (2024). Remote Learning and Work. IEEE Internet Computing, 28(1).

Zhao, P., Bazarova, N. N., DiFranzo, D., Hui, W., Kizilcec, R. F. & Margolin, D. (2024). Standing up to problematic content on social media: which objection strategies draw the audience’s approval? Journal of Computer-Mediated Communication, 29(1).

Rizvi, S., Rienties, B., Rogaten, J., & Kizilcec, R. F. (2023). Are MOOC learning designs culturally inclusive (enough)? Journal of Computer-Assisted Learning.

Alon, L., Sung, S., Cho, J., & Kizilcec, R. F. (2023). From emergency to sustainable online learning: Changes and disparities in undergraduate course grades and experiences in the context of COVID-19. Computers & Education, 203, 104870.

Misevic, D., Atal, I., Bedard, D., Cherel, E., Escamilla, J., Evans, L., Hannon, V., Huron, C., Irrmann, O., Kizilcec, R. and Lazega, E. (2023). Harnessing collective intelligence for the future of learning – a co-constructed research and development agenda. Human Computation, 10(1), 1-30.

Claure, H., Kim, S., Kizilcec, R., & Jung, M. (2023). The social consequences of machine allocation behavior: Fairness, interpersonal perceptions and performance. Computers in Human Behavior, 146, 107628.

McCarthy, K. S., Crossley, S. A., Meyers, K., Boser, U., Allen, L. K., Chaudhri, V. K., Collins-Thompson, K., D’Mello, S., De Choudhury, M., Garg, K., Goel, A., Gosha, K., Heffernan, N., Hooper, M. A., Hyman, E., Jarratt, D. C., Khalil, D., Kizilcec, R. F., Litman, D., Malatinszky, A., Marks, K., McNamara, D. S., Menko, R., Palermo, C., Porcaro, D., Roscoe, R., Shapiro, S., Khanh-Phoung, T., Trumbore, A. M., White, C., Wong, W., Yang, D., & Zampieri, M. (2022). Toward more effective and equitable learning: Identifying barriers and solutions for the future of online education. Technology, Mind, & Behavior.

Rizvi, S., Rienties, B., Rogaten, J., & Kizilcec, R. F. (2022). Beyond one-size-fits-all in MOOCs: Variation in learning design and persistence of learners in different cultural and socioeconomic contexts. Computers in Human Behavior, 126, 106973.

Williams-Ceci, S., Grose, G. E., Pinch, A. C., Kizilcec, R. F., & Lewis Jr, N. A. (2021). Combating sharenting: Interventions to alter parents’ attitudes toward posting about their children online. Computers in Human Behavior, 125, 106939.

Kizilcec, R. F., Chen, M., Jasinska, K., Madaio, M., & Ogan, A. (2021). Mobile Learning During School Disruptions in Sub-Saharan Africa. AERA Open, 7.

Varanasi, R. A., Vashistha, A., Kizilcec, R. F., & Dell, N. (2021) Investigating Technostress Among Teachers in Low-IncomeIndian Schools. In Proceedings of the ACM on Human Computer Interaction.

Cho, J., Li, Y., Krasny, M. E., Russ, A., & Kizilcec, R. F. (2021). Online Learning and Social Norms: Evidence from a Cross-Cultural Field Experiment in a Course for a Cause. Computer-based Learning in Context, 3(1), 18-36.

Chaturapruek, S., Dalberg, T., Thompson, M. E., Giebel, S., Harrison, M., Johari, R., Stevens, M. L., & Kizilcec, R. F. (2021). Studying Undergraduate Course Consideration at Scale. AERA Open, 7.

Rizvi, S., Rienties, B., Rogaten, J., Kizilcec, R. F. (2019). Investigating Variation in Learning Processes in a FutureLearn MOOC. Journal of Computing in Higher Education, 32, 162-181.

Davis, D., Kizilcec, R. F., Hauff, C., & Houben, G.-J. (2018). Scaling Effective Learning Strategies: Retrieval Practice and Long-Term Knowledge Retention in MOOCs. Journal of Learning Analytics, 5(3), 21-41.

Maldonado-Mahauad, J., Pérez-Sanagustín, M., Kizilcec, R. F., Morales, N., & Munoz-Gama, J. (2018). Mining theory-based patterns from Big data: Identifying self-regulated learning strategies in Massive Open Online Courses. Computers in Human Behavior, 80, 179-196.

Kizilcec, R. F., Perez-Sanagustin, M., & Maldonado, J. J. (2017). Self-Regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses. Computers & Education, 104, 18-33.

Li, J., Kizilcec, R. F., Bailenson, J. N., & Ju, W. (2016). Social Robots and Virtual Agents as Lecturers for Video Instruction. Computers in Human Behavior, 55(B), 1222-1230.

Kizilcec, R. F. & Schneider, E. (2015). Motivation as a Lens to Understand Online Learners. ACM Transactions on Computer-Human Interaction (TOCHI), 22(2).

Kizilcec, R. F., Bailenson, J. N., & Gomez, C. J. (2015). The Instructor’s Face in Video Instruction: Evidence from Two Large-Scale Field Studies. Journal of Educational Psychology, 107(3), 724-739.

Kizilcec, R. F., Schneider, E., Cohen, G. L., & McFarland, D. A. (2014). Encouraging Forum Participation in Online Courses with Collectivist, Individualist, and Neutral Motivational Framings. eLearning Papers, 37, 13-22.

Thille, C., Schneider, D. E., Kizilcec, R. F., Piech, C., Halawa, S. A., & Greene, D. K. (2014). The Future of Data–Enriched Assessment. Research & Practice in Assessment, 9(2), 5-16.

Aymerich-Franch, L., Kizilcec, R. F., & Bailenson, J. N. (2014). The Relationship between Virtual Self Similarity and Social Anxiety. Frontiers in Human Neuroscience, 8(944).

Peer-Reviewed and Published Conference Papers

Harvey, E. H., Koenecke, A., & Kizilcec, R. F. (2025). "Don't Forget the Teachers": Towards an Educator-Centered Understanding of Harms from Large Language Models in Education. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems. ACM.

Williamson, K. H., Kizilcec, R. F., Fath, S., & Heffernan, N. (2025). Algorithm Appreciation in Education: Educators Prefer Complex over Simple Algorithms. In Proceedings of the ACM Conference on Learning Analytics and Knowledge (LAK).

Lee, J., Harvey, E., Zhou, J., Garg, N., Joachims, T., & Kizilcec, R. F. 2024. Ending Affirmative Action Harms Diversity Without Improving Academic Merit. In Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO ’24), ACM.

Harvey, E., Koenecke, A., & Kizilcec, R. (2024) Towards an Educator-Centered Method for Measuring Bias in Large Language Models. AAAI 2024 Workshop on AI for Education. Spotlight Presentation.

Rajashekar, N.C., Shin, Y.E., Pu, Y., Chung, S., You, K., Giuffre, M., Chan, C.E., Saarinen, T., Hsiao, A., Sekhon, J., Wong, A.H., Evans, L.V., Kizilcec, R.F. Laine, L., Mccall, T., & Shung, D. (2024) Human-Algorithmic Interaction Using a Large Language Model-Augmented Artificial Intelligence Clinical Decision Support System. In Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems. ACM.

Cho, J., Tao, Y., Yeomans, M., Tingley, D., Kizilcec, R. F. (2024). Which Planning Tactics Predict Online Course Completion? In Proceedings of the ACM Conference on Learning Analytics and Knowledge (LAK).

Lee, H., Kizilcec, R. F., & Joachims, T. (2023). Evaluating a Learned Admission-Prediction Model as a Replacement for Standardized Tests in College Admissions. In Proceedings of the ACM Conference on Learning at Scale (L@S). Best Paper Award

Lee, J. Thymes, B., Zhou, J., Joachims, T., & Kizilcec, R. F. (2023). Augmenting Holistic Review in University Admission using Natural Language Processing for Essays and Recommendation Letters. In Workshop Proceedings of Intl. Conference on Artificial Intelligence in Education (AIED).

Cram, A., Raduescu, C., Zeivots, S., Smolansky, A., Kizilcec, R. F., & Huber, E. (2023). Developing a Prototype to Scale up Digital Support for Online Assessment Design. In Proceedings of the ACM Conference on Learning at Scale (L@S).

Smolansky, A., Cram, A., Raduescu, C., Zeivots, S., Huber, E., & Kizilcec, R. F. (2023). Educator and Student Perspectives on the Impact of Generative AI on Assessments in Higher Education. In Proceedings of the ACM Conference on Learning@ Scale (L@S).

Kizilcec, R.F., Viberg, O., Jivet, I., Martínez-Monés, A., Oh, A., Hrastinski, S., Mutimukwe, C., & Scheffel, M. (2023). The Role of Gender in Students’ Privacy Concerns about Learning Analytics: Evidence from five countries. In Proceedings of the ACM Conference on Learning Analytics and Knowledge (LAK). Best Short Paper Honorable Mention

Gardner, J., Yu, R., Nguyen, Q., Brooks, C., & Kizilcec, R. F. (2023). Cross-Institutional Transfer Learning for Educational Models: Implications for Model Performance, Fairness, and Equity. In Proceedings of the ACM Conference on Fairness, Accountability, and Transparency (FAccT).

Williamson, K. H., & Kizilcec, R. F. (2023). Structures in Online Discussion Forums: Promoting Inclusion or Exclusion? In Proceedings of the Intl. Conference on Artificial Intelligence in Education (AIED), 115-120

Alon, L., Sung, S. Y., & Kizilcec, R. F. (2023). “It’s Nice to Mix Up the Rhythm”: Undergraduates’ Experiences in a Large Blended Learning Course in Information Science in the Context of COVID-19. In Proceedings of the Intl. Conference on Information, 445-460.

Sung, S., Alon, L., Cho, J., & Kizilcec, R. F. (2022). How to Assess Student Learning in Information Science: Exploratory Evidence from Large College Courses. In Proceedings of the 85th Annual Meeting of the Association for Information Science & Technology (ASIS&T).

Chen, Y., Fu, A., Lee, J., Wilkie Tomaski, I., & Kizilcec, R. F. (2022). Pathways: Exploring Academic Interests with Historical Course Enrollment Records. In Proceedings of the ACM Conference on Learning at Scale (L@S).

Sabnis, S., Yu, R., & Kizilcec, R. F. (2022). Large-Scale Student Data Reveal Sociodemographic Gaps in Procrastination Behavior. In Proceedings of the ACM Conference on Learning at Scale (L@S). Best UG Paper Award

Williamson, K. & Kizilcec, R. F. (2022). Using Social Network Analysis to Explore Discussion Board Networks in Higher Education Classrooms. In Proceedings of the ACM Conference on Learning at Scale (L@S).

Cho, J., Li, Y., Krasny, M. E., & Kizilcec, R. F. (2022). Measuring Cultural Dimensions of Learning in Online Courses. In Proceedings of the ACM Conference on Learning at Scale (L@S).

Kizilcec, R. F., Mimno, J. A., & Karhan, A. J. (2022). Effects of Framing Professional Development as a Career Growth Opportunity on Course Completion. In Proceedings of the ACM Conference on Learning at Scale (L@S).

Williamson, K. & Kizilcec, R. F. (2022). A Review of Learning Analytics Dashboard Research in Higher Education: Implications for Justice, Equity, Diversity, and Inclusion. In Proceedings of the Intl. Conference on Learning Analytics and Knowledge (LAK).

Allen, S. E., Phillips, A. M., & Kizilcec, R. F. (2021). Student perceptions of pre-assessments: “It’s basically just guessing anyways.” In Proceedings of the Physics Education Research Conference.

Alon, L., Sung, S. & Kizilcec, R.F. (2021). How Does Active Learning Change Undergraduate Learning Experiences? A Case of a Large Technology Design Course. In T. Bastiaens (Ed.), In Proceedings of Innovate Learning Summit, 201-208.

Yu, R., Lee, H., & Kizilcec, R. F. (2021). Should College Dropout Prediction Models Include Protected Attributes? In Proceedings of the ACM Conference on Learning at Scale (L@S). Best Paper Honorable Mention

Williamson, K. & Kizilcec, R. F. (2021). Effects of Algorithmic Transparency in Bayesian Knowledge Tracing on Trust and Perceived Accuracy.  In Proceedings of the Conference on Educational Data Mining (EDM).

Williamson, K. & Kizilcec, R. F. (2021). Learning Analytics Dashboard Research Has Neglected Diversity, Equity, and Inclusion. In Proceedings of the ACM Conference on Learning at Scale (L@S).

Cho, J. & Kizilcec, R. F. (2021). Applying the Behavior Change Taxonomy from Public Health Interventions to Education Research.  In Proceedings of the ACM Conference on Learning at Scale (L@S).

Cho, J., Li, Y., Krasny, M. E., Armstrong, A., Russ, A., & Kizilcec, R. F. (2021). Using Social Norms to Promote Actions Beyond the Course. In Proceedings of the ACM Conference on Learning at Scale (L@S).

Cho, J., Tomasik, I., Yang, H., & Kizilcec, R. F. (2021). Student Perceptions of Social Support in the Transition to Emergency Remote Instruction. In Proceedings of the ACM Conference on Learning at Scale (L@S). Best UG Paper Award

Cho, J. & Kizilcec, R. F. (2021). Delivery Ghost: Effects of Language Immersion and Interactivity in a Language Learning Game. In Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI).

Kizilcec, R. F. & Chen, M. (2020). Student Engagement in Mobile Learning via Text Message. In Proceedings of the ACM Conference on Learning at Scale (L@S).

Chen, Y. & Kizilcec, R. F. (2020). Examining Sources of Variation in Student Confusion in College Classes. In Proceedings of the ACM Conference on Learning at Scale (L@S).

Kizilcec, R. F., Saltarelli, A. J., Bonfert-Taylor, P., Goudzwaard, M., Hamonic, E., & Sharrock, R. (2020). Welcome to the Course: Early Social Cues Influence Women’s Persistence in Computer Science. In Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI).

Varanasi, R. A., Kizilcec, R. F., & Dell, N. (2019). How Teachers in India Reconfigure their Work Practices around a Teacher-Oriented Technology Intervention. In Proceedings of the ACM Conference on Computer-Supported Cooperative Work (CSCW).

Kizilcec, R. F. & Saltarelli, A. (2019). Can a diversity statement increase diversity in MOOCs? In Proceedings of the ACM Conference on Learning at Scale (L@S). Best Paper Award

Kizilcec, R. F. & Goldfarb, D. (2019). Growth Mindset Predicts Student Achievement and Behavior in Mobile Learning. In Proceedings of the ACM Conference on Learning at Scale (L@S).

Kizilcec, R. F. & Saltarelli, A. (2019). Psychologically Inclusive Design. In Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI).

Kizilcec, R. F., Bakshy, E., Eckles, D., & Burke, M. (2018). Social Influence and Reciprocity in Online Gift Giving. In Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI).

Chaturapruek, S., Dee, T. S., Johari, R., Kizilcec, R. F., & Stevens, M. L. (2018). How a data-driven course planning tool affects college students' GPA: Evidence from two field experiments. In Proceedings of the Fifth ACM Conference on Learning at Scale (L@S). Best Paper Award

Davis, D., Kizilcec, R. F., Hauff, C., & Houben, G.-J. (2018). The Half-Life of MOOC Knowledge: A Randomized Trial Evaluating the Testing Effect in MOOCs. In Proceedings of the Intl. Conference on Learning Analytics and Knowledge (LAK).

Kizilcec, R. F., Davis, G. M., & Cohen, G. L. (2017). Towards equal opportunities in MOOCs: Affirmation reduces gender & social-class achievement gaps in China. In Proceedings of the ACM Conference on Learning at Scale (L@S). Best Paper Award

Davis, D., Jivet, I., Kizilcec, R. F., Chen, G., Hauff, C., & Houben, G.-J. (2017). Follow the Successful Crowd: Facilitating Social Comparison Raises MOOC Completion Rates. In Proceedings of the International Conference on Learning Analytics and Knowledge (LAK).

Kizilcec, R. F. (2016). How Much Information? Effects of Transparency on Trust in an Algorithmic Interface. In Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI).

Kizilcec, R. F., Perez-Sanagustin, M., & Maldonado, J. J. (2016). Recommending Self-Regulated Learning Strategies Does Not Improve Performance in a MOOC. In Proceedings of the ACM Conference on Learning at Scale (L@S).

Kizilcec, R. F., & Halawa, S. A. (2015). Attrition and Achievement Gaps in Online Learning. In Proceedings of the ACM Conference on Learning at Scale (L@S).

Krause, M., & Kizilcec, R. F. (2015). To Play or not to Play: Response Quality and Task Complexity in Games and Paid Crowdsourcing. In Proceedings of the AAAI Conference on Human Computation & Crowdsourcing (HCOMP).

Kizilcec, R. F., Papadopoulos, K., & Sritanyaratana, L. (2014). Showing Face in Video Instruction: Effects on Information Retention, Visual Attention, and Affect. In Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI).

Zhang, K. & Kizilcec, R. F. (2014). Anonymity in Social Media: Effects of Content Controversiality and Social Endorsement on Sharing Behavior. In Proceedings of the AAAI Intl. Conference on Weblogs and Social Media (ICWSM).

Kizilcec, R. F., Piech, C., & Schneider, E. (2013). Deconstructing Disengagement: Analyzing Learner Subpopulations in Massive Open Online Courses. In Proceedings of the Intl. Conference on Learning Analytics and Knowledge (LAK).

Kizilcec, R. F. (2013). Collaborative Learning in Geographically Distributed and In-person Groups. In Proceedings of the Conference on Artificial Intelligence in Education (AIED).

Book Chapters

Kizilcec, R. F. (forthcoming). Higher Education. In Tara Behrend (Ed.), Human-Technology Partnerships at Work. Cambridge Press.

Kizilcec, R. F., Shung, D. L., & Sung, J. J. (2024). Human-machine interaction: AI-assisted medicine, instead of AI-driven medicine. In Artificial Intelligence in Medicine (pp. 131-140). Academic Press.

Alvero, A. J., Kizilcec, R. F., Lee, J., & Munoz-Najar Galvez. (forthcoming). Perspectives on NLP in College Admissions. In Frank Fernandez (Ed.), The Digitized Campus: Artificial Intelligence and Big Data in Higher Education. SUNY Press.

Kizilcec, R. F. & Davis, D. (2023). Learning Analytics Education: A case study, review of current programs, and recommendations for instructors. In Olga Viberg and Åke Grönlund (Eds.), Practicable Learning Analytics. Springer Nature.

Kizilcec, R. F. & Lee, H. (2022). Algorithmic Fairness in Education. In W. Holmes & K. Porayska-Pomsta (Eds.), The Ethics of Artificial Intelligence in Education, Routledge.

Rizvi, S., Rienties, B., Rogaten, J., & Kizilcec, R. F. (2022). Culturally-Adaptive Learning Design: A Mixed-method Study of Cross-Cultural Learning Design Preferences in MOOCs. In B. Rienties, R. Hampel, E. Scanlon, D. Whitelock (Eds.), Open World Learning: What Works?, Routledge.

Kizilcec, R. F. & Brooks, C. (2017). Diverse Big Data and Randomized Field Experiments in MOOCs. In C. Lang, G. Siemens, A. Wise, D. Gašević (Eds.), Handbook of Learning Analytics (pp. 211-222). Society for Learning Analytics Research.

Edited Special Issues

Kizilcec, R. F. & Mitchell, J. C. (2024). Remote Learning and Work. IEEE Internet Computing, 24(1).

Viberg, O., Kizilcec, R. F., Wise, A. F., Jivet, I., & Nixon, N. (Sep 2024) “Special Issue: Advancing Equity and Inclusion in Educational Practices with AI-Powered Educational Decision Support Systems (AI-EDSS)” British Journal of Educational Technology. CFP: https://bera-journals.onlinelibrary.wiley.com/hub/journal/14678535/cfp-advancing-equity-and-inclusion

Peer-Reviewed Commentaries and Policy Briefs

Williamson, K. H.,  Guerrero, V., & Kizilcec, R. F. (2024). Improving Social Justice should be an Objective of Learning Analytics Research. Journal of Learning Analytics.

Kizilcec, R. F. (2023). To Advance AI Use in Education, Focus on Understanding Educators. International Journal of Artificial Intelligence in Education, 1-8.

Kizilcec, R. F., Mason, J., McCarthy, K. S., Rodrigo, M. M. T., Rose, C. P. (2023). Using Technology to Foster Equitable Access and Diverse Learning Communities. Digital Promise and the International Society of the Learning Sciences.

INVITED TALKS/PANELS

2025        Responsible AI in Education, Nokia Bell Labs, Responsible AI seminar

2025        Introducing the National Tutoring Observatory, AI-ALOE, webinar

2024        Congress on AI in Higher Education, University of Puerto Rico, keynote

2023        IPN - Leibniz Institute for Science and Mathematics Education, Kiel, Germany, invited talk

2022        Educational Data Mining (EDM) Conference, Durham University, keynote

2022        Center for Biomedical Data Science Digital Health Seminar, Yale University, invited talk

2022        MARS AI Seminar Series, Korea Advanced Institute of Science & Technology, invited talk

2022        Culturally Aware Learning Analytics workshop, LAK, workshop keynote

2022        Motivation, self-regulation, and personality symposium, Tübingen University, invited guest

2022        Learning and Collective Intelligence workshop, Learning Planet Institute, Paris, guest speaker

2021        Summer Institute in Computational Social Science, HSE University, guest lecture

2021        Culturally Aware Human-Centered Learning Analytics Workshop, EC-TEL, keynote

2021        Positive Education Conference, Tsinghua University, keynote

2021        eMadrid Research Days, Online, invited talk on Self-regulated Learning

2021        AAAI Panel on Advancing Learning in the Digital Era, panelist

2020        Aspen Forum for the Future of Higher Education, co-organizing session

2020        AERA Educational Data Science Mini-conference, Stanford University, invited talk

2020        Society for Personality and Social Psychology (SPSP) conference, talk (2% acceptance rate)

2019        Singapore Management University, “Communication, Data, and Design” colloquium talk

2019        National University of Singapore, ALSET seminar, invited talk

2019        China Positive Education Conference, Tsinghua University, keynote

2018        Northeast Big Data in Education Conference, CMU, invited keynote

2018        University of Michigan, Academic Innovation speaker series, talk on inclusive learning

2017        Higher School of Economics, Russia, invited keynote at higher education conference

2017        Udemy, Inc., talk on supporting continued engagement with online learning at scale

2017        Kahn Academy, talk on supporting continued engagement with online learning at scale

2016        Pontifical Catholic U. of Chile, talk on social psychological barriers in higher education

2016        Rosetta Stone, talk on psychological factors in online courses

2016        EdTech Meetup RheinMain, Germany, talk on online education research

2016        Pratham Symposium, Stanford, panel on worldwide challenges in education

2016        MediaX Conference, Stanford, panel on digital augmentation in education

2016        Learning Summit, Stanford, panel discussion on inclusive learning environments

2016        TU Delft, the Netherlands, talk on psychological interventions in online learning

2016        Coursera Partners Conference, Holland, talk on strategies to support active learning in MOOCs

2015        UC Berkeley, Institute of Design, talk on psychological interventions in online learning

2015        MIT, xTalk series, talk on psychological interventions in online learning

2015        University of Michigan, MOOC research summit, talk on psychological causes of achievement gaps in online learning

2015        Coursera, Inc., talk on learner motivation, social cues, and achievement gaps in online learning

2015        Digital October Center, Moscow, Russia, talk on instructional design in MOOCs

2014        MediaX Conference, Stanford, talk on market segmentation of online interactions based on motivation

SELECTED CONFERENCE PRESENTATIONS (NON-ARCHIVAL)

2022        Unizin Summit, “Cross-Institutional Transfer Learning for Educational Models: Implications for
         Model Performance, Fairness, and Equity”

2020        IC2S2, “The Limits of Scalable Interventions: Evidence from 248 Online Courses”

2019        CODE@MIT, “Broadening Participation with Diversity Statements”

2019        CODE@MIT, “The Limits of Scalable Interventions”

2019        AI100 Prediction in Practice, “On the Psychology of AI in Practice”

2018        IC2S2, “Heterogenous Effects of Incentives in Mobile Learning in Africa”

2018        CODE@MIT, “Criteria-based Randomization”

2016        BayLearn Conference, “Psychologically Welcoming Learning Environments”

2016        SPSP, “Closing the Global Achievement Gap in Online Learning”

2015        CODE@MIT, “Peer encouragement designs: Estimating peer effects of social feedback”

2014        eMOOCs, “Encouraging Forum Participation […] with Motivational Framings“

2014        Learning with MOOCs, “The Promise of Social Learning & Annotation”

TEACHING

Learning Analytics (INFO 4100/5101), Cornell

Offered in Fall 2019, Spring 2019, Fall 2020, Fall 2021, Fall 2022, Spring 2024, Spring 2025

Behavioral Science Interventions (COMM/INFO 4800), Cornell

Offered in Spring 2020 (with Neil Lewis Jr.) and Spring 2022

PhD Seminar on Learning and Technology (INFO 6940), Cornell

Offered in Spring 2023

Causal Inference and Design of Experiments (INFO 6750), Cornell

Offered in Fall 2018

Freshman Team Projects Course (INFO 1998), Cornell

Offered in Spring 2022, Fall 2022, Spring 2023, Fall 2023

Invited and ad-hoc teaching

2022, 2024        Guest Lecture, 6.882 Ethical Machine Learning in Human Deployments, MIT

2021        Guest Lecture, CS 4660: Foundations in Educational Technology, Georgia Tech

2021        Guest Lecture, EDUC 131: Educational Technology, UC Irvine

2016        Guest Lecture, Learning Analytics Seminar, Stanford University

2014, 2015        Teaching Assistant, “Online Learning Research Methods”, Stanford University

2014        Guest Lecture, Learning Analytics Seminar, George Mason University

2014        Co-Instructor, Workshop on questionnaire design, Stanford University

2010, 2011        Technology Camp Director, TIC Summer Camp, McLean, VA.
Held teacher-training workshops, designed and supervised programming classes.

ADVISING

Primary Advisor (Postdoc)

Primary Advisor (PhD at Cornell)

Committee Member (PhD at Cornell)

Committee Member (PhD at other institution)

Thesis Committee Member (UG and MS/MPS/MEng)

Informal Research Advisor (UG and MS/MPS/MEng)

Visiting PhD Students

PROFESSIONAL SERVICE

Institutional:  Cornell University

2025                Member,  Generative AI Education Committee

2025                Member,  IT Governance: Education & Pedagogy Domain Committee

2024 SP        Director, Broadening Participation Committee, Department of Information Science

2022-23        Member, Presidential Task Force on Undergraduate Admissions

2022-23        Co-Director, Broadening Participation Committee, Department of Information Science

2022-23        Member, Committee on Learning Outcomes, Bowers CIS College

2022-23        Member, Bowers CIS DEI Council

2021-22        Interim Co-Chair, Vice Provost’s Committee on Course Feedback/Teaching Evaluations

2021-22        Member, Hopper Dean Fellowship Selection Committee, Bowers CIS College

Since 2020        Faculty Advisor Board Member, McCormick Teaching Excellence Institute

2020-21        Member, Vice Provost’s Committee on Course Feedback/Teaching Evaluations

2020-22        Member, Broadening Participation Committee, Department of Information Science

2019-23        Co-Lead, Active Learning Initiative, Department of Information Science

2019-20        Member, Undergraduate Committee, Department of Information Science

2018-19        Member, PhD Admissions Committee, Department of Information Science

2018-20        Member, Vice Provost’s Committee on Learning Analytics

Scientific Community:  Organizational/Leadership

Since 2019        Associate Editor, Computer-Based Learning in Context

2024-25        Steering Committee Chair, Festival of Learning 2026

2023                Steering Committee Chair, ACM Learning at Scale

2023                Subcommittee Co-Chair (SC), Learning, Education, and Families, ACM CHI

2022                General Conference Chair, ACM Learning at Scale

2023                Steering Committee Vice Chair, ACM Learning at Scale

2022                Subcommittee Awards Representative, ACM CHI

2020-21        Steering Committee Member, ACM Learning at Scale

2022                Program Committee Member, ACM Learning at Scale; Learning Analytics &
                Knowledge; Educational Data Mining; Higher Education Advances

2021                Program Committee Member, ACM CHI, ACM Learning at Scale, ACM FAccT

2020                Program Co-Chair, ACM Learning at Scale

2019                Program Committee Member, ACM CSCW, ACM CHI, ACM Learning at Scale

2018                Program Committee Member, ACM Learning at Scale

2017                Program Committee Member, ACM Learning at Scale, eMOOCs, Coursera Partners
                Conference

2016                Program Committee Member, Learning with MOOCs Conference

2015                Program Committee Member, ACM Learning at Scale

Scientific Community:  Grant Application/Manuscript Reviewing

2023                Grant Reviewer, Marsden Fund, Schmidt Futures Foundation
                (reviewer and finalist judge for LEVI), MIT Solve LEAP Challenge

2023                Journal Reviewer, Management Science, Applied Psychology, Journal of Learning
                Analytics, British Journal of Educational Technology, Journal of Computer Assisted
                Learning, Routledge (book proposal)

2022                Journal Reviewer, Scientific Reports, Journal of Computational Social Science,
                Frontiers in Psychology, British Journal of Educational Technology, Transactions on
                Learning Technologies, Journal of Computer-Assisted Learning, Computers & Education

2022                Ad-hoc Foundation Grant Reviewer, National Science Foundation (NSF), Israel
                Science Foundation (ISF), Schmidt Futures Foundation

2022                Journal Reviewer, Scientific Reports, Journal of Computational Social Science,
                Frontiers in Psychology, British Journal of Educational Technology, Transactions on
                Learning Technologies, Journal of Computer-Assisted Learning, Computers & Education

2021                Journal Reviewer, Computers & Education, Computers in Human Behavior, Journal of
                Computer-Assisted Learning

2021                Journal Reviewer, Educational Psychology, International Journal of Artificial
                Intelligence in Education, Transactions on Computer-Human Interaction (TOCHI),
                Education Research Review,  IEEE Transactions on Learning Technologies, Computers
                & Education, Educational Researcher, Journal of Computer-Assisted Learning

2021                Grant Reviewer, IES Higher Education Panel

2020                Journal Reviewer: Science, AERA Open, Journal of Business Ethics, Computers &
                Education

2020                Grant Reviewer, Spencer Foundation Large Grants

2014-19        Reviewer, Psychological Science, Oxford University Press, Computers in Human
                Behavior, Journal of Learning Analytics, International Journal of Artificial Intelligence in
                Education, International Conference on Learning Analytics & Knowledge, ACM CSCW
                Conference, IEEE Transactions on Signal Processing, Journal of Computer Assisted
                Learning, ACM TOCHI Transactions on Computer-Human Interaction, Computers &
                Education, IEEE Transactions on Learning Technologies, ACM CHI Human Factors in
                Computing Systems Conference

Workshop Organization

2023                Viberg, O., Jivet, I., Kizilcec, R. F., & Scheffel, M. (2023). Fifth Workshop on
                Culturally-Aware Learning Analytics (CARLA). At the
European Conference on
                Technology Enhanced Learning (ECTEL)
.

2023                Ritter, S., Heffernan, N., Williams, J.J., Lomas, D., Bicknell, K., Roschelle, J.,
                Motz, B., McNamara, D., Baraniuk, R., Basu Mallick, D. and Kizilcec, R. (2023).
                Fourth Annual Workshop on A/B Testing and Platform-Enabled Learning
                Research. At the
ACM Conference on Learning@ Scale (L@S).

2023                Smolansky, A., Nguyen, H. A., Kizilcec, R. F., McLaren, B. M. (2023). Equity,
                Diversity, and Inclusion in Educational Technology Research and Development.
                At the
International Conference on Artificial Intelligence in Education (AIED).

2022                Ritter, S., Heffernan, N., Williams, J.J., Lomas, D., Motz, B., Basu Mallick, D.,
                Bicknell, K., McNamara, D., Kizilcec, R.F., Roschelle, J. and Baraniuk, R.,
                (2022). At the Third Annual Workshop on A/B Testing and Platform-Enabled
                Learning Research. At the ACM Conference on Learning@ Scale (L@S).

2014                Williams, J. J., Kizilcec, R. F., Russell, D. M., & Klemmer, S. R. (2014). Learning
                innovation at scale. At the
ACM Conference on Human Factors in Computing
                Systems (CHI)
.

SELECTED MEDIA COVERAGE

Fast Company, Can AI transform adult online education?, June 2023

EdSurge, The Future Belongs to Online Learners–But Only If Programs Can Help Them Succeed, June 2023

EdSource, Colleges can blunt economic impact of pandemic by sharing online courses, September 2020 (oped with Igor Chirikov)

Forbes, The “Depressing” And “Disheartening” News About MOOCs, June 2020

EdSurge, Massive Study of Online Teaching Ends With Surprising - and ‘Deflating’ – result, June 2020

WIRED, People Want to Know About Algorithms—but Not Too Much, March 2019

Harvard Business Review, We Need Transparency in Algorithms, But Too Much Can Backfire, July 2018

Xinhua News, Exercise devised to boost completion rates of some online learning courses, April 2017

The Australian, Online Primer Fails in Collectivist Cultures, April 2017

EdSurge, Study Finds Tactics to Help Close Global MOOC Achievement Gap, February 2017

The Australian, Welcome effort boosts MOOCs, February 2017

PBS Rewire, ‘Taking an Online Course? Writing Out Your Reasons Why Might Help You Finish’, January 2017

Inside Higher Ed, A Sense of Belonging on Inside Higher Ed, January 2017

Education Week, Practical Guidance from MOOC Research: Student Diversity, July 2015

BBC, Moocs data offers promise of perfect teaching, October 2013

ACM Tech News, Learning analytics at Stanford takes huge leap forward with MOOCs, April 2013

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