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Northwestern University Computational Thinking in STEM Building interest and proficiency in computational thinking in STEM http://ct- stem.northwestern.edu

Northwestern University Computational Thinking in STEM

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Northwestern University Computational Thinking in STEM. http :// ct- stem.northwestern.edu. Building interest and proficiency in computational thinking in STEM. Meet the Team. Principal Investigators. - PowerPoint PPT Presentation

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Page 1: Northwestern University Computational Thinking in STEM

Northwestern UniversityComputational Thinking in STEM

Building interest and proficiency in computational thinking in STEM

http://ct-stem.northwestern.edu

Page 2: Northwestern University Computational Thinking in STEM

Meet the Team

High School Lead Teachers & PD Providers:

Kemi Jona Michael Horn Vicky Kalogera Laura Trouille Uri Wilensky Kai Orton

Principal Investigators

Graduate Students

David Weintrop Elham Behesti

This work is supported in part by the National Science Foundation under NSF grants CNS-1138461 and is covered by IRB study STU00058570. However, any opinions, findings, conclusions, and/or recommendations are those of the investigators and do not necessarily reflect the views of the Foundation.

Mark Vondracek Ami Lefevre Meagan Morscher

Pilot Teachers: 11 in 2012-201316 in 2013-201415 in 2014-2015

Page 3: Northwestern University Computational Thinking in STEM

CT-STEM: Goals

Goals:• Build teacher knowledge, interest, and confidence:

• developing your students’ CT-STEM skills• using CT tools to improve your students’ learning of STEM concepts

• Connect CT-STEM to what you already do & to Illinois standards

• Train in discipline-specific CT-STEM lesson plans

Pilot Teachers: • Summer Workshop• 5 Saturday continuing education workshops• Teaching and assessing 5 CT-STEM lessons in your classroom

Page 4: Northwestern University Computational Thinking in STEM

4

“Big Data” is Everywhere

~40 109 Web pages at ~300 kilobytes each = 10 PetabytesYoutube 48 hours video uploaded per minute;

in 2 months in 2010, uploaded more than total NBC ABC CBS~2.5 petabytes per year uploaded?

LSST 30 TB/nightLHC 15 petabytes per yearRadiology 69 petabytes per yearSquare Kilometer Array Telescope will be 100 terabits/secondEarth Observation becoming ~4 petabytes per yearEarthquake Science – few terabytes total todayPolarGrid – 100’s terabytes/yearExascale simulation data dumps – terabytes/second

Page 5: Northwestern University Computational Thinking in STEM

5

McKinsey Institute on Big Data Jobs

• There will be a shortage of talent necessary for organizations to take advantage of big data. By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.

Page 6: Northwestern University Computational Thinking in STEM
Page 7: Northwestern University Computational Thinking in STEM

CT-STEM: Key Concepts

• Algorithmic Thinking: – create a series of ordered steps to solve a problem– allows for automation of a procedure

• Examples:

• Efficiency at a buffet table• Long Division• Experimental Procedure

Page 8: Northwestern University Computational Thinking in STEM

CT-STEM: Key Concepts

• Abstraction: – Pulling out the important details– Identifying principles that apply to other situations

• Examples:• Holiday dinners• Construct a model of an atom• Use the term ‘titration’ in an experimental design

Page 9: Northwestern University Computational Thinking in STEM

CT-STEM: Key Concepts

• Computational Modeling:– Use a computational tool to develop a representation of a

system (i.e., visualize an abstraction of a system)– Use a computational tool to analyze, visualize, and gain

understanding of a STEM concept

• Examples:• CAD (in engineering)• Netlogo and other computational environments

Page 10: Northwestern University Computational Thinking in STEM

CT-STEM: Key Concepts

• Decomposition:– Reformulating a seemingly difficult problem into

one we know how to solve

• Examples:

• Road networks in a major city -> Muddy City

Page 11: Northwestern University Computational Thinking in STEM

CT-STEM: Key Concepts

• Generalization:– How is this problem is similar to others?– Can we transfer the problem solving process from a

solved problem to this new one?

• Examples:• Can I apply the same strategies that I learned playing soccer to playing basketball? • Gravity and flux

Page 12: Northwestern University Computational Thinking in STEM

CT-STEM: Key Concepts

• Big Data:– Big Data refers to a collection of data sets so large and complex,

it’s impossible to process them with the usual databases and tools.

– Because of its size and associated numbers, Big Data is hard to capture, store, search, share, analyze and visualize.

• Examples:• Sequencing the human genome• The Galaxy Zoo Project of over 1 million galaxies

Page 13: Northwestern University Computational Thinking in STEM

The Human Genome…By the Numbers

46…Chromosomes in each cell~23,000…Genes in the human genome2.4 million…Base pairs in the largest human gene3.1 billion…Base pairs in each cell75-100 trillion…Cells in the human body

Page 14: Northwestern University Computational Thinking in STEM

CT in Biology

• Shotgun algorithm expedites sequencing of human genome - DNA sequences are strings in a language - Protein structures can be modeled as knots - Protein kinetics can be modeled as computational processes - Cells as a self-regulatory system are like electronic circuits

Page 15: Northwestern University Computational Thinking in STEM

CT in Astronomy

• Mass Determination of our Milky Way’s Black Hole– Comparing observed data to simulations

Page 16: Northwestern University Computational Thinking in STEM

CT in Chemistry

• Atomistic calculations explore chemical phenomena• Optimization and searching algorithms identify best chemicals for improving

reaction conditions to improve yields

Page 17: Northwestern University Computational Thinking in STEM

CT in Engineering

• Boeing 777 never tested in a wind tunnel, only in computer simulations

• Ability to calculate higher order terms implies more precision, which implies reducing weight, waste, costs in fabrication, etc.

Page 18: Northwestern University Computational Thinking in STEM

CT in Geology

• Modeling the earth inner layers, using seismic waves• Modeling the earth and our atmosphere to track and predict

climate changes

Page 19: Northwestern University Computational Thinking in STEM

CT in Math

• Discovering E8 Lie Group – took 18 mathematicians, 4 years and 77 hours of supercomputer time

(200 billion numbers). – Profound implications for physics (string theory)

Page 20: Northwestern University Computational Thinking in STEM

CT in Medicine

• Robotic surgery• Electronic health records require privacy technologies• Scientific visualization enables virtual colonoscopy

Page 21: Northwestern University Computational Thinking in STEM

CT in Social Sciences

• Social networks explain phenomena like MySpace, YouTube• Statistical machine learning is used for recommendation and

reputation services, e.g., Netflix, affinity card

Page 22: Northwestern University Computational Thinking in STEM

CT in the Humanities

• What do you do with a million books?– Nat’l Endowment for the Humanities Institute of Museum

and Library Services• Arts, drama, music, photography

Credit: Christian Mueller

Page 23: Northwestern University Computational Thinking in STEM

CT in Entertainment

• Games• Music MP3 sorting/searches• Movies

- Dreamworks uses HP data center to renderShrek and Madagascar - Lucas Films uses 2000-node data center to make Pirates of the Caribbean.