Mine Çetinkaya-Rundel | Advancing Open Access Data Science Education

<p>Mine Çetinkaya-Rundel | Advancing Open Access Data Science Education #datascience #statistics #education</p> <p>Mine Çetinkaya-Rundel (Duke University) describes the current and future states of statistics and data science education. Then she discusses the process of building open access learning material.</p> <p> </p> <p>0:00 - Introduction 1:40 - Prioritizing topics in curricula 9:07 - Teaching with intent to test 11:22 - Statistics without computing 17:52 - What should be taught? How do we teach it? 19:07 - Computational thinking is valuable (to 31:45) 23:47 - Self reinforcing academics / positive feedback (to 31:45) 31:08 - Data science vs statistics (the computing angle) 37:55 - Statistical collaboration / technical collaboration 39:45 - Common language / imputation under ignorance 41:12 - Are some topics better for hands on or computational learning? 45:32 - Learning computation through visualization 52:40 - Video cut option before she gives an example 52:42 - Let them eat cake first. 56:08 - What is open source education? Open source vs open access. 59:36 - Advancing open source text books 1:03:55 - Economics of open source 1:07:55 - The open education ecosystem 1:12:17 - Modularizing & parallelizing learning topics 1:16:52 - Favorite dataset on OpenIntro.Org? 1:18:14 - What topic should the statistics community debate?</p>