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  1. 1. STEMinars Robert D. Cormia Foothill College
  2. 2. STEMinars <ul><li>Pedagogy for informal learning </li></ul><ul><li>Four component model </li></ul><ul><ul><li>S cience </li></ul></ul><ul><ul><li>T echnology </li></ul></ul><ul><ul><li>E ngineering </li></ul></ul><ul><ul><li>M athematics </li></ul></ul><ul><li>Formal SLOs </li></ul><ul><ul><li>(Seminar Learning Outcomes) or STEMinar Learning Objects </li></ul></ul>
  3. 3. Seminars Pros and Cons <ul><li>Current material - recency </li></ul><ul><li>Topical focus – applied context </li></ul><ul><li>Keeps us ‘up to date’ </li></ul><ul><li>Lacks formal Learning Outcomes (SLOs) </li></ul><ul><li>Usually not foundational </li></ul><ul><ul><li>Prior knowledge required to participate </li></ul></ul><ul><li>Lacks mathematics rigor </li></ul><ul><ul><li>Rarely do you see people work the numbers </li></ul></ul>
  4. 4. Seminar Examples <ul><li>PARC forum – technology and society </li></ul><ul><li>Stanford Energy Seminar – climate / energy / technology </li></ul><ul><li>California Academy of Science – technology and society </li></ul><ul><li>Webinars – virtually any current topic </li></ul><ul><li>Documentaries - virtually any current topic </li></ul>The Internet and World Wide Web are radically changing how education is delivered
  5. 5. Seminars as Open Educational Resources <ul><li>PARC Forum – Streaming AV </li></ul><ul><li>Energy Seminar - iTunesU </li></ul><ul><li>Webinars – WebEx </li></ul><ul><li>Conferences – AV and/or mp3 / mpeg </li></ul>
  6. 6. The STEM in STEMinar <ul><li>S cience – as foundational framework </li></ul><ul><li>T echnology – the emphasis (interest) </li></ul><ul><li>E ngineering – practical how-too context </li></ul><ul><li>M athematics – rarely practiced in public </li></ul>All too often we are merely shown the current context, nothing foundational, nor the toil that went into solving the problem, and instead just the end result (like Julia Childs). We need to see the mathematics and/or engineering equations that form the basis of engineering know-how, and or data (visualization) that drives home the main point. Solving problems in public is important!
  7. 7. Better STEMinar Practices <ul><li>S cientific foundation (discovery) </li></ul><ul><li>E ngineering know-how (nuts and bolts) </li></ul><ul><li>T echnology – how is it used, and why? </li></ul><ul><li>M athematics – supporting equations </li></ul>It’s your four basic food groups – applied to ‘everyday innovation’. If you blend a bit of each into your technical discussions, you get a much deeper learning outcome, one that has ‘current context’, relevance, and SLO rigor.
  8. 8. STEMinar Examples <ul><li>The Science of Climate Change </li></ul><ul><li>Electric vehicles, fuel cells, and EMF </li></ul><ul><li>How does wind energy save the day ? </li></ul><ul><li>Acidification of the ocean by GHGs </li></ul><ul><li>A glimpse at Peak Oil Production </li></ul><ul><li>Using math in public ( supportively ) </li></ul>
  9. 9. Learning Goals Up Front <ul><li>Tell your audience what they will learn </li></ul><ul><li>Share the field of science involved </li></ul><ul><li>Share the engineering challenges </li></ul><ul><li>What new technology will they learn? </li></ul><ul><li>Have handouts for one or two equations </li></ul>SLOs help us craft the roadmap of a presentation – informal quizzes at the end ensure we accomplished those goals – and create reflective learning opportunities.
  10. 10. Wrap Up Quiz at the End <ul><li>You need answers to five questions </li></ul><ul><ul><li>What was the (S) cience / knowledge? </li></ul></ul><ul><ul><li>What (E) ngineering problems were solved? </li></ul></ul><ul><ul><li>What (T) echnologies are practiced, and how? </li></ul></ul><ul><ul><li>What was the (M) numeracy and computation? </li></ul></ul><ul><ul><li>How will *you* use or share this information? </li></ul></ul>Turn it into a contest – with groups of students competing for points. You can also have follow up questions that require research, synthesis and computation
  11. 11. Solar Energy - earth’s Heat
  12. 12. 250 years of Carbon Emissions It took 125 years to burn the first trillion barrels of oil – we’ll burn the next trillion in less than 30 years – why should you care?
  13. 13. Rising CO 2 over 50 Years see-saw swings in CO 2 result from seasonal ‘biological production’
  14. 14. Temperatures over 1000 Years
  15. 15. Ice Cores – Story of Vostok
  16. 16. Vostok Ice Core Data <ul><li>A perfect correlation between CO 2 , temperature, and sea level </li></ul><ul><li>For every one ppm CO 2 , sea level rises 1 meter, temp rises .05 C (global) </li></ul><ul><li>Process takes 100 years to add 1 ppm CO 2 , and reach thermal equilibrium </li></ul>This is not just a correlation, this is a complex and dynamic process , with multiple inputs. Touching one input affects all other inputs , and increases in temperature becomes a further feedback and multiplier of these inputs.
  17. 17. GHGs and Vostok Data James Kirchner Department of Earth and Planetary Science, University of California, Berkeley
  18. 18. Dials on the Thermostat GHGs force energy into the planet, surface warming leads to feedbacks Thermal inertia Climate feedbacks GHGs CO 2 CH 4 Ice / albedo Water vapor Clouds Temperature
  19. 19. Missing feedbacks, asymmetric uncertainties, and the underestimation of future warming Margaret S. Torn and John Harte AGU GEOPHYSICAL RESEARCH LETTERS, VOL. 33, L10703 Effect of Climate Feedbacks
  20. 20. Ocean Acidification and CO 2 <ul><li>250 years of fossil fuel combustion </li></ul><ul><li>300,000 G tons C, 1 trillion tons of CO 2 </li></ul><ul><li>pH of ocean is buffered by bicarbonate ion </li></ul><ul><li>Phytoplankton shells are made of carbonate and can’t easily form and persist below a pH of 8 </li></ul><ul><li>At ~450 ppm CO 2 , the ocean has become too acidic (pH) </li></ul>
  21. 21. Understanding CO 2 and pH CO 2 + CaCO 3 + H 2 O => 2(HCO 3 ) -  + 2Ca 2+   Dissolving CO 2 into seawater produces bicarbonate and hydrogen ions – decreasing pH
  22. 22. Ocean Acidification
  23. 23. Peak Oil Production <ul><li>M. King Hubbert’s famous 1956 prediction! </li></ul><ul><ul><li>Peak oil production around 2004 - 2010 </li></ul></ul><ul><ul><li>After that, more expensive to find / refine </li></ul></ul><ul><li>Economies built on oil / gas will struggle </li></ul><ul><li>Not the end of oil, the end of easy oil! </li></ul><ul><ul><li>More expensive to find </li></ul></ul><ul><ul><li>Technically challenging </li></ul></ul><ul><ul><li>Environmentally damaging </li></ul></ul><ul><li> </li></ul>
  24. 24. Peak Oil – ‘After the Crash’
  25. 25. World Oil Production History
  26. 26. Oil Production – Reserves From ‘The Inevitable Peaking of World Oil Production’, Hirsch, 2005
  27. 27. Logistic Analysis of Oil Production <ul><li>Logistic analysis is how ultimate production estimates are made. </li></ul><ul><li>Plot production growth (percent) on Y-axis, and cumulative production on X axis. </li></ul><ul><li>1/t ‘modulation’ is the trend line for the bell shaped ‘peak oil curve’ </li></ul><ul><li>These are US oil data => </li></ul>
  28. 28.
  29. 29. Electric Vehicles <ul><li>EMF – work without heat </li></ul><ul><li>250 to 333 watt-hours per mile </li></ul><ul><li>How flow cells / fuel cells work </li></ul><ul><li>Electricity from wind energy </li></ul><ul><li>How much wind do we need? </li></ul>EMF – Electro Motive Force – the ‘work’ that an electron does using voltage
  30. 30. Electric Vehicles (EVMT) <ul><li>In the US we use 400 million gallons of gasoline a day (400 x 10 6 gallons/day) </li></ul><ul><li>At 20 mpg that is 8 billion miles a day (8 x 10 9 ) </li></ul><ul><li>Cross check VMT chart ( 3.0 trillion miles/year ) </li></ul><ul><li>An electric car uses 0.25 to 0.33 KwHr per mile </li></ul><ul><li>US would need 2.5 billion KwHrs per day (EV) to replace gasoline (~25% e - charging overhead) </li></ul><ul><li>Where can we get 2.5 x 10 9 KwHrs per day? </li></ul>Building the Electron Economy – Robert D. Cormia 2010
  31. 31. US GDP/VMT VMT data from green car congress =>
  32. 32. Energy Efficiency/Liquidity <ul><li>US buildings use 60% of all electricity </li></ul><ul><li>Could we be 40% more efficient with energy? </li></ul><ul><ul><li>(40% is the typical efficiency goal for LEED) </li></ul></ul><ul><li>40% energy reduction of 60% electricity is 24% </li></ul><ul><li>24% of 10.5 x 10 9 KwHrs a day = 2.5 x 10 9 / day </li></ul><ul><li>~2.5 x 10 9 KwHrs/day is needed for EVMT </li></ul><ul><li>What we could gain *with efficiency alone* could (almost) *completely* replace gasoline </li></ul>Building the Electron Economy – Robert D. Cormia 2010
  33. 33. Wind Power – Real Power
  34. 34. Why Wind is the Answer to EV <ul><li>One motor winds up – another unwinds </li></ul><ul><li>1MW of wind supports 1,000 EV cars </li></ul><ul><li>See the math (calculation below) </li></ul><ul><li>Need to ‘forward store’ wind energy for later EV charging (like email distribution) </li></ul><ul><li>Predictive analytics , grid-scale storage , collaborative EV charging networks are key </li></ul>1 MW of wind => 24 hrs * 365 days * 1/3 utilization = 2.9 * 10^6 KwHrs annually 1,000 EVs * 10,000 miles / EV * 300 watt-hrs / mile = 3.0 * 10^6 KwHrs annually
  35. 35. Vanadium redox flow cells Store excess power for later use!
  36. 37. Batteries and Fuel Cells <ul><li>Batteries </li></ul><ul><ul><li>NiMH </li></ul></ul><ul><ul><li>Lithium </li></ul></ul><ul><li>Fuel cells </li></ul><ul><ul><li>DMFC </li></ul></ul><ul><ul><li>SOFC </li></ul></ul><ul><ul><li>Hydrogen </li></ul></ul>
  37. 38. How Fuel Cells Work A fuel cell is a device that uses hydrogen (or hydrogen-rich fuel) and oxygen to create electricity. Fuel cells are more energy-efficient than combustion engines and the hydrogen used to power them can come from a variety of sources. If pure hydrogen is used as a fuel, fuel cells emit only heat and water, eliminating concerns about air pollutants or greenhouse gases.
  38. 39. Do Math in Public! <ul><li>Numeracy and computation </li></ul><ul><li>Analytical reasoning ability </li></ul><ul><li>Deeper understanding of concepts </li></ul><ul><li>Understanding trend lines is critical </li></ul><ul><li>We need to use numbers in conversation </li></ul>
  39. 40. Do Math in Public! Use numbers in your conversation to tell a story. Numeracy and computation is how we learn and test both statistical and empirical (causal) relationships.
  40. 41. Exploratorium
  41. 42. OER – Open Educational Resources and Derivatives <ul><li>Learning objects </li></ul><ul><li>Open CC license </li></ul><ul><li>Metadata labeled </li></ul><ul><li>Easily shared </li></ul><ul><li>Easily integrated </li></ul>
  42. 43. Creative Commons Licenses
  43. 44. Summary <ul><li>STEMinars is a pedogical approach to informal learning – it is simply a discipline </li></ul><ul><li>STEM are the four basic food groups </li></ul><ul><li>Always have learning goals up front </li></ul><ul><li>Have a quick ‘informal quiz’ at the end </li></ul><ul><li>Create, share, and use Open Educational Resources (OERS) with SLOs attached </li></ul>
  44. 45. References <ul><li>STEMtech – </li></ul><ul><li>iTunesU - </li></ul><ul><li>Exploratorium – </li></ul><ul><li>How Stuff Works - </li></ul><ul><li>Creative Commons – </li></ul><ul><li>PARC – http://www/ </li></ul>