René F. Kizilcec
Ph.D. candidate, Dept. of Communication, Stanford University
Stanford Interdisciplinary Graduate Fellow
Co-founder, Stanford Lytics Lab
René Kizilcec is a Stanford Interdisciplinary Graduate Fellow and co-founding member of the interdisciplinary Lytics Lab. He recently defended his Ph.D. dissertation in the Department of Communication at Stanford University.
His research focuses on social and cultural psychological factors in interactive technologies, for example, how psychological barriers hinder the academic achievement of online learners, how effective self-regulation strategies vary across cultures, and how peer influence spreads in social networks. He is particularly interested in the psychological challenges to realizing the potential of digital environments for diverse and global audiences. His research has been published in leading journals such as Science, Proceedings of the National Academy of Sciences (PNAS), Journal of Educational Psychology, Computers in Human Behavior, Computers & Education, and in the proceedings of leading human-computer interaction and education conferences such as ACM SIGCHI, Learning at Scale, and Learning Analytics & Knowledge. This research was awarded a Computational Social Science Fellowship, a Stanford Interdisciplinary Graduate Fellowship, and a Faculty Seed Grant for Innovation in Research at Stanford. René has worked closely with Facebook to conduct research on social influence in communication behavior on social media. He worked as a web developer before graduate school.
René’s research has examined the consequences of social identity threat, self-regulation, trust, and cultural differences using longitudinal field experiments. Recently, he has investigated how to (1) close the online global achievement gap between members of more and less developed countries in online courses, (2) support goal pursuit across cultural contexts with self-regulation strategies, and (3) enhance the online learning experience by strategically placing social cues in videos. He leverages techniques from data mining, machine learning, and natural language processing to examine behavior and motivation, reveal heterogeneous treatment effects, and inform user-centered design.
René holds an M.Sc. in Statistics from Stanford University and a B.A. in Philosophy and Economics from University College London.
You can follow him on Twitter @whynotyet.
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