Mine Çetinkaya-Rundel | Advancing Open Access Data Science Education
#datascience #statistics #education
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.
 
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?