S
Sean Raleigh
Researcher at Westminster College (Utah)
Publications - 4
Citations - 256
Sean Raleigh is an academic researcher from Westminster College (Utah). The author has contributed to research in topics: Computer science & Curriculum. The author has an hindex of 2, co-authored 2 publications receiving 191 citations.
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Journal ArticleDOI
Curriculum Guidelines for Undergraduate Programs in Data Science
Richard D. De Veaux,Mahesh Agarwal,Maia Averett,Benjamin S. Baumer,Andrew Bray,Thomas Bressoud,Lance Bryant,Lei Zhang Cheng,Amanda Francis,Robert G. Gould,Albert Y. Kim,Matt Kretchmar,Qin Lu,Ann Moskol,Deborah Nolan,Roberto Pelayo,Sean Raleigh,Ricky J. Sethi,Mutiara Sondjaja,Neelesh Tiruviluamala,Paul X. Uhlig,Talitha M. Washington,Curtis L. Wesley,David White,Ping Ye +24 more
TL;DR: These guidelines are meant to provide some structure for institutions planning for or revising a major in Data Science.
Journal ArticleDOI
Curriculum Guidelines for Undergraduate Programs in Data Science
Richard D. De Veaux,Mahesh Agarwal,Maia Averett,Benjamin S. Baumer,Andrew Bray,Thomas Bressoud,Lance Bryant,Lei Zhang Cheng,Amanda Francis,Robert G. Gould,Albert Y. Kim,Matt Kretchmar,Qin Lu,Ann Moskol,Deborah Nolan,Roberto Pelayo,Sean Raleigh,Ricky J. Sethi,Mutiara Sondjaja,Neelesh Tiruviluamala,Paul X. Uhlig,Talitha M. Washington,Curtis L. Wesley,David White,Ping Ye +24 more
TL;DR: The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program met for the purpose of composing guidelines for undergraduate programs in Data Science as discussed by the authors, and the group consisted of 25 undergraduate faculty from a variety of institutions in the U.S., primarily from the disciplines of mathematics, statistics and computer science.
Proceedings ArticleDOI
Analysis of Student Grades After Switching to POGIL
TL;DR: In this article , the authors present a Bayesian analysis of student grades using a hierarchical ordinal logistic regression model, which includes the number of A, B, C, D, F, and W grades, disaggregated by gender and ethnicity.
Proceedings ArticleDOI
Analysis of Student Grades Before and After Adopting POGIL
TL;DR: In this paper , a Bayesian analysis of student grades using a hierarchical ordinal logistic regression model is presented, showing that most faculty observed an improvement in student pass rates in the second and third term after they began teaching with POGIL.