NSDL/NSTA Web Seminar: Learning By Doing—Computational Science LIVE INTERACTIVE LEARNING @ YOUR DESKTOP NSDL/NSTA Web Seminar: Learning By Doing—Computational Science http://nsdl.org http://institute.nsta.org/web_seminars.asp

Robert introduces Patricia and Bethany

http://nsdl.org Access to large collections of simulations and interactives Resources for 21st century learning skills Still intro, mention of Pathways and NSDL CSERD: NSDL Computational Science Pathway

What is Computational Science?

Computational Science… uses models to demonstrate and visualize concepts New Moon? Full Moon?

Computational Science… uses real-life situations to teach inquiry-based math and science concepts Estimator: The number of stars is greater or less than 340 Revised Slide 16 Greater than 340? Less than 340?

Computational Science… helps students learn how to use technology to solve problems Topples Stands

Computational Science… uses interactive tools to observe and analyze data

Interactive Activities Computational Science Education Reference Desk (CSERD) http://cserd.nsdl.org Interactive Activities Discussions Lesson Plans Suggestions & Help

Skill level with use of technology in classroom? Intermediate Advanced Novice Skill level with use of technology in classroom? Combine math and science together in your curriculum? Rarely to Never Occasionally On a regular basis

Modern science and mathematics are more concerned with pattern recognition and characterization than with mere symbol manipulation.

Recognition The pahomnnehil pweor of the hmuan mnid. Aoccdrnig to a rehcaseerr at Cmabirdge Uinervtisy, it deosn’t mttaer in waht oredr the ltteers in a wrod are, the olny imprmoetnt tihng is taht the frist and lsat ltteer be at the rghit pclae. The rset can be a total mses and you can sitll raed it wouthit porbelm. Tihs is bcuseae the huamn mnid deos not raed ervey lteter by istlef, but the wrod as a whlohe. Anizamg huh?

Rabbits and Wolves: Population Dynamics Characterization Rabbits and Wolves: Population Dynamics

Add after Slide 24

Symbol Manipulation

http://www.shodor.org/interactivate 100+ interactive math based activities Lesson plans Discussions Worksheets Open-ended explorations Dictionary Standards alignments

Predict: How much of the forest will burn? Given: If 1 tree is on fire there is a 100% probability that the tree next to it will catch. Predict: How much of the forest will burn? Exactly 0% 0%-50% 50%-100% Exactly 100%

Predict: How much of the forest will burn? Given: If 1 tree is on fire there is a 0% probability that the tree next to it will catch. Predict: How much of the forest will burn? Exactly 0% 0%-50% 50%-100% Exactly 100%

As a scatter plot our data looks like: Data Points 0, 0 1, 100 Interactivate’s Scatter Plot Activity

Poll Question: Given: If 1 tree is on fire there is a 50% probability that the tree next to it will catch. Predict: How much of the forest will burn?

You try it! Try using the Fire! Interactive a few times on your own We will now take you to this link: http://www.shodor.org/interactivate/activities/Fire Try using the Fire! Interactive a few times on your own We will bring you back in 3 minutes… ask for help by pushing *6 if you need it!

Data from 10 Burns at 50% Probability of Burn Trial # % Burned 1 1% 2 27% 3 54% 4 65% 5 41% Trial # % Burned 6 44% 7 69% 8 43% 9 60% 10 45% MEAN from 10 trials: ~45%

As a scatter plot our data looks like: Red Data Points (0, 0) (1, 100) Blue Data Points (0.5, 45) Hmm… How could we find the overall pattern? Interactivate’s Scatter Plot Activity

Recognizing the Pattern Resulting graph in green from averaging 10 burns at each of the following probabilities: 0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1

Would you have predicted that pattern? Computers help us to model and simulate real world phenomena so we can better understand the world around us. The model is only as good as the design. How does the Fire!! model relate to the real world and how does it not?

Possible Content Addressed: Mathematics Fractions / Percents Scatter Plots, Graphing Coordinate Pairs Reading / Interpreting Graphs Mean / Average Probability Randomness Science Experimental Design Experimental Control Independent and Dependent Variables Conjecture and Hypothesis Chaos

More Robust Models Interactivate’s Directable Fire!! (not pictured) Interactivate’s A Better Fire!! (pictured below)

Go to http://nsdl.org and click on the K-12 audience page Download this seminar’s annotated module for resources from this seminar and more!

THANK YOU! Patricia Jacobs Bethany Hudnutt Robert Payo http://nsdl.org http://cserd.nsdl.org Patricia Jacobs pjacobs@shodor.org THANK YOU! Bethany Hudnutt bhudnutt@shodor.org Robert Payo rpayo@nsdl.ucar.org

National Science Teachers Association Gerry Wheeler, Executive Director Frank Owens, Associate Executive Director Conferences and Programs Al Byers, Assistant Executive Director e-Learning NSTA Web Seminars Flavio Mendez, Program Manager Jeff Layman, Technical Coordinator Judith Lopes, Administrative Assistant Susan Hurstcalderone, Volunteer Chat Moderator LIVE INTERACTIVE LEARNING @ YOUR DESKTOP