ANALYZING CORRELATIONS: CLIMATE CHANGE IMPACTS AND RENEWABLE SOLUTIONS LAURA ROBERTS RET PARTICIPANT SUMMER 2015 8 TH GRADE MATH-ADAPTABLE TO ALGEBRA AND.

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ANALYZING CORRELATIONS: CLIMATE CHANGE IMPACTS AND RENEWABLE SOLUTIONS LAURA ROBERTS RET PARTICIPANT SUMMER TH GRADE MATH-ADAPTABLE TO ALGEBRA AND ALGEBRA 2

OBJECTIVES Students will be able to identify current trends in carbon emissions and their global implications. Students will analyze trends in data related to climate change/engineering trends. Students will be able to explain the importance of lowering emissions/investing in engineering. Students will collect data to build scatter plots modeling solar power. Students will analyze impacts of climate change on specific populations.

MATH STANDARDS ADDRESSED (8 TH GRADE) F.4: Construct a function to model a linear relationship between two quantities. Determine the rate of change and initial value of the function from a description of a relationship or from two (x, y) values, including reading these from a table or from a graph. Interpret the rate of change and initial value of a linear function in terms of the situation it models, and in terms of its graph or a table of values. SP.1: Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association. SP.2: Know that straight lines are widely used to model relationships between two quantitative variables. For scatter plots that suggest a linear association, informally fit a straight line, and informally assess the model fit by judging the closeness of the data points to the line. SP.3: Use the equation of a linear model to solve problems in the context of bivariate measurement data, interpreting the slope and intercept. For example, in a linear model for a biology experiment, interpret a slope of 1.5 cm/hr as meaning that an additional hour of sunlight each day is associated with an additional 1.5 cm in mature plant height. SP.4: Understand that patterns of association can also be seen in bivariate categorical data by displaying frequencies and relative frequencies in a two-way table. Construct and interpret a two-way table summarizing data on two categorical variables collected from the same subjects. Use relative frequencies calculated for rows or columns to describe possible association between the two variables. For example, collect data from students in your class on whether or not they have a curfew on school nights and whether or not they have assigned chores at home. Is there evidence that those who have a curfew also tend to have chores?

LESSON 1: ‘DO THE MATH’ Essential Questions: What do positive and negative correlations look like? What makes a correlation stronger or weaker? How do correlations help us understand data? Introduction (Check for prior knowledge) 9 of the top ten global concerns Water, Food, Environment, Poverty, Terrorism & War, Disease, Education, Democracy, and Population Informal Discussion: How does energy help us solve these problems? Hook: What is the top global concern? ENERGY!! Why is energy a global concern? Why are 2, 565, 2785 important numbers? Show clips from “Do the Math”. First, 2°C and 565 (565 billion gigatons of carbon is the max we have agreed to let into the atmosphere.).

LESSON 1 CONTINUED Re-visit objective (scatter plot/correlation) How much carbon have we already released into the atmosphere? Do you think we are close to 565? Data for carbon ppm in atmosphere ftp://aftp.cmdl.noaa.gov/products/trends/co2/co2_annm ean_mlo.txt ftp://aftp.cmdl.noaa.gov/products/trends/co2/co2_annm ean_mlo.txt Create scatterplot Why don’t the points make a straight line? Which direction are they going? Direct Instruction regarding correlation Show clip (finishing 565/ final number 2785)

LESSON 1: CONCLUSION Informal discussion of final number. (2795 billion tons of carbon is what is currently in reserves). Homework: Create scatter plots/determine correlation for major effects of climate change (temperature, arctic ice, and rising sea levels) Source:

GLOBAL TEMPERATURE

ARCTIC ICE EXTENT

SEA LEVEL CHANGE

LESSON 2: TREND LINES Objectives: Students will create trend lines to interpret data Introduction: Discussion of Trends: Which had positive/which had negative? What do the graphs look like? Teacher picks one graph…e.g. rising sea levels: what do you think the change will be in 2019? How did you get your answer? Why do we want to predict future numbers? Quickly introduce objective/draw trend line What does this line show? How does it help us? What do you think could be some implications of rising sea levels? Hook: Video

LESSON 2: CONTINUED More detailed direct instruction regarding trend lines Create trend line for Maldives sea level rises Students complete trend lines for scatter plots they did for homework Homework: Students analyze data sets for different populations/see different effects of climate change. Include news headlines related to each. Tanzania Temps/Coffee Production Southern Africa Temps/Maize Production (soil moisture) New York (Northeast Temp Increase/Precipitation Increase) Respond to quote- What are some possible solutions to the climate change problem? Creativity is not just for artists…it's for engineers trying to solve a problem; it's for parents who want their children to see the world in more than one way - Twyla Tharp UA.99 UA.99 Mӧrner, Nils-Axel. “The Maldives: A Measure of Sea Leval Changes and Sea Level Ethics”. Paleogeophysics and Geodynamics, Rӧsundavӓgen 17, 13336, Saltsjobaden, Sweden. C8QFjAC&url=http%3A%2F%2Fmyweb.wwu.edu%2Fdbunny%2Fpdfs%2FCh7Elsev ier.pdf&ei=5QWIVYjiK8WoyATGyLzACQ&usg=AFQjCNF69gdW4uqnTlv3QOvXaNd WCmiXOA&sig2=CbwIuZiWVUahTJoMeiyXbw C8QFjAC&url=http%3A%2F%2Fmyweb.wwu.edu%2Fdbunny%2Fpdfs%2FCh7Elsev ier.pdf&ei=5QWIVYjiK8WoyATGyLzACQ&usg=AFQjCNF69gdW4uqnTlv3QOvXaNd WCmiXOA&sig2=CbwIuZiWVUahTJoMeiyXbw

TANZANIA Arabica Production Trends Mean Temperature

NEW YORK Mean TemperatureMean Precipitation New York City Panel on Climate Change, 2013: “Climate Risk Information 2013: Observations, Climate Change Projections, and Maps.” C.Rosenzweig and W. Solecki (Editors), NPCC2. Prepared for use by the City of New York Special Initiative on Rebuilding and Resiliancy, New York, New York.

SOUTH AFRICA Jury, Mark R. “An Inter-comparison of Model-simulated East-west Climate Gradients over South Africa”. “Water SA”,vol.38 n.4 Pretoria Jan University of Zululand, KwaDlangezwa, 3886, South Africa Physics Department, University of Puerto Rico Mayaguez, PR, USA Hudson, D.A., and R.G. Jones Regional climate model simulations of present day and future climates of Southern Africa. Technical note 39. Bracknell, UK: Hadley Centre.

LESSON 2 HOMEWORK POTENTIAL HIGHER ORDER THINKING QUESTIONS How does this data affect the populations of the respective countries? How do you think they are responding to the data? Who should be the most concerned out of all the populations? Least concerned? Why? Do you think we are affected by the trends in different cities/countries? Explain your reasoning. Provide quotes showing how data can be debated. E.g. “While politicians and environmental advocates routinely attribute natural disasters with human- caused climate change, the uncomfortable reality is that such attribution remains speculative. There is not yet a scientific basis for making such a connection. That is not an argument against taking action, but it is an argument for accurately representing the science. ” –Roger Pielke Jr.

LESSON 3: HANDS ON SOLAR Objectives: Students will collect and analyze data modeling solar power throughout a simulated day Students will attempt to maximize power output of solar panel and document their data/determine their effectiveness Hook: Informal Discussion regarding quote, then video Materials Needed Lamp Solar Panel Multi-Meter Chair (or something that provides a moveable fixed height) Alligator Clips Tape Tape Measurer

LESSON 3 CONTINUED Potential group assignments Team Leader Recorder Multi-meter Manager Chair Coordinator Students will measure and mark tape according to certain hours of the day (8, 9, 10, 11, 12, 1, 2, 3, 4) Alligator clips connect solar panel to multi-meter: Solar panel stays in fixed place (12:00) Chair is moved along designated times, stopping at each marked spot on tape to record data Data should model quadratic function

LESSON 3 CONCLUSION Once students determine their correlation is not linear, they must work as a team on the following task You cannot lift the solar panel completely off the ground or move it outside it’s designated box. How can we maximize the solar energy? Experiment! Sample Data Sets: 1 st is leaving solar panel flat, second is adjusting angle “Time” Voltage “Time” Voltage Follow-up Questions Which hours would you expect to see the most difference in voltage? Why? Of your data, which hours saw the most difference in voltage? Could this data ever represent a perfect line? Why or why not? Do you think solar panels’ angles change throughout the day? What would the advantage be? Disadvantage? Exit Slip: Will the total amount of voltage collected throughout the day have a correlation? If so will it be weak or strong? Is it possible for this to be a perfect line? Provide explanations for all your answers. Homework: Graph scatterplot comparing time and total voltage. Analyze trend and correlation.

FORMATIVE ASSESSMENT Keeping it relevant: Students will analyze trends in engineering by plotting data, assessing correlation and drawing trend lines. Introduce with quote: “I hope climate science becomes the big thing. And then what I want is electrical engineers to solve the world's energy problems, energy distribution problems. I want mechanical engineers to make better transportation systems. I want chemical engineers to develop better solar panels, and so on”-Bill Nye Analyze the following trends Trends in engineering degrees (electrical, mechanical, chemical) Women in as a percentage of workers in science and engineering careers (specifically engineers) Graduate enrollment in engineering, by citizenship/race and ethnicity

TRENDS IN BACHELORS DEGREES

WOMEN IN ENGINEERING

GRADUATE ENROLLMENT BY CITIZENSHIP, RACE/ETHNICITY

POTENTIAL PROJECT BASED LEARNING OR CO-CURRICULAR APPLICATIONS Debate importance of renewable energy (address the fact that climate change is in fact a debate: a current weakness of these lesson plans) Analyze more biodiversity data to coincide closer with science standards Students choose diminishing species (plant or animal) and create a research project Have students come up with ideas to conserve energy/reduce waste. They can collect the data and determine their success (e.g. negative correlation for time/weight of trash-steeper slope is better) Connect to political events (ex. Oil pipeline) Write a persuasive letter or create a video taking a side and providing evidence to back up your argument Convince high school students to enter engineering Either with persuasive letter or real-world audience As students or taking the role of populations introduced with trend lines