Data Science Education

Statistics Practicum: Placing 'Practice' at the Center of Data Science Education

by Eric D. Kolaczyk, Haviland Wright, and Masanao Yajima

Connections

Commentaries (8):

Jessica Utts

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Kit T. Rodolfa & 1 other

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Usama Fayyad & 1 other

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David R. Hardoon

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Nicholas J. Horton & 3 others

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Philip L. H. Yu & 1 other

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Antonietta Mira & 1 other

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David Uminsky

Rejoinders (1):

Eric D. Kolaczyk & 2 others

High School Data Science Review: Why Data Science Education Should Be Reformed

by Angelina Chen

Introducing GAISE II: A Guideline for Precollege Statistics and Data Science Education

by Christine Franklin and Anna Bargagliotti

The Opportunities of Two-Year College Data Science

by Brian Kotz

The Coronavirus Exponential: A Preliminary Investigation into the Public's Understanding

by Alexander Podkul, Liberty Vittert, Scott Tranter, and Alex Alduncin

Data Science for Everyone Starts in Kindergarten: Strategies and Initiatives from the American Statistical Association

by Wendy L. Martinez and Donna LaLonde

Data, Data, Everywhere…

by Nicole Lazar

Beyond Unicorns: Educating, Classifying, and Certifying Business Data Scientists

by Thomas Davenport

On the Convergence of Epidemiology, Biostatistics, and Data Science

by Neal D. Goldstein, Michael LeVasseur, and Leslie A. McClure

Toward Foundations for Data Science and Analytics: A Knowledge Framework for Professional Standards

by Usama Fayyad and Hamit Hamutcu

The Role of Academia in Data Science Education

by Rafael A. Irizarry

Change Through Data: A Data Analytics Training Program for Government Employees

by Frauke Kreuter, Rayid Ghani, and Julia Lane

Data Science as a Foundation for Inclusive Learning

by Robert A. Lue

Highlights of the National Academies Report on "Undergraduate Data Science: Opportunities and Options”

by Laura Haas, Alfred Hero, and Robert A. Lue

Data Science: What the Educated Citizen Needs to Know

by Alan M. Garber

The Promise of Portfolios: Training Modern Data Scientists

by Deborah Nolan and Sara Stoudt

Interleaving Computational and Inferential Thinking: Data Science for Undergraduates at Berkeley

by Ani Adhikari, John DeNero, and Michael I. Jordan

Connections

Commentaries (10):

Allen B. Downey

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Alan David Fekete

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Michael J. Franklin & 1 other

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Alison L. Gibbs & 1 other

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Yolanda Gil

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Aleksandrina Goeva & 3 others

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Brian Kim

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Dr. Alfred Z. Spector

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Dustin Tingley

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Chris J. Wild & 2 others

Rejoinders (1):

Ani Adhikari & 2 others

Rejoinder: Practice-Centric Learning—A Driver for Democratization of Data Science

by Eric D. Kolaczyk, Haviland Wright, and Masanao Yajima

Statistical Practice Is Not a Spectator Sport

by Jessica Utts

Project-Based Learning via Competition for Data Science Students

by Philip L. H. Yu and Wai Keung Li

Taking Our Medicine: Standardizing Data Science Education With Practice at the Core

by Kit T. Rodolfa and Rayid Ghani

The Data Science Corps Wrangle-Analyze-Visualize Program: Building Data Acumen for Undergraduate Students

by Nicholas J. Horton, Benjamin S. Baumer, Andrew Zieffler, and Valerie Barr

How Can We Train Data Scientists When We Can’t Agree on Who They Are?

by Usama Fayyad and Hamit Hamutcu

From Outlier to Normalcy: Community Partnering as a Pathway Toward Modularity, Sustainability and Diversity When Centering ‘Practice’ in Data Science Education

by David Uminsky

The Capstone in Everyone’s Delivery Room: Placing ‘Practice’ at the Center of Data Science Education

by Antonietta Mira and Ernst Wit

Is Data Science Education a Jack of all Trades?

by David R. Hardoon

Kaleidoscopic Perspectives on Practicum-Based Data Science Education

by Shuang Frost, Aleksandrina Goeva, Javin Pombra, Will Seaton, Sara Stoudt, Ana Trisovic, Chris Wang, and Catherine Zucker

Can the Coronavirus Prompt a Global Outbreak of “Distributional Thinking” in Organizations?

by Nathan Sanders

Data Science and Computing at UC Berkeley

by Jennifer Chayes

Connections

Commentaries (5):

Patrick J. Wolfe

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Hal S. Stern & 2 others

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S. Joe Qin

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David Madigan

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Munther A. Dahleh

Engaging Young Learners With Data: Highlights From GAISE II, Level A

by Leticia R. Perez, Denise A. Spangler, and Christine Franklin