The pedagogical objective of this
project is to introduce elementary statistics students to essential topics of
statistics such as correlation and regression analysis, curve fitting and
polynomial models using an environmental (global warming) theme as a framework.
This project gives students a chance to explore in detail some issues related
to global warming such as CO2 (carbon dioxide) emissions and rising global
average temperature. The objective of this specific project is to enhance
students’ skills in mathematical and statistical modeling, particularly
modeling using polynomials of first through third degree and the quality of curve
fit. Using CO2 gas emission visualization data obtained from the
Data Visualization link (http://www.eia.gov; United
States US Energy Information Administration) students construct a model for polynomials
of first (linear), second and third degrees to predict CO2 emissions.
As a starting point, this project
provided students the world map of
CO2 emissions data in table-1
(http://www.eia.gov/cfapps/ipdbproject/iedindex3.cfm?tid=90&pid=45&aid=8&cid=regions&syid=1980&eyid=2010&unit=MMTCD).https://docs.google.com/spreadsheet/ccc?key=0AonYZs4MzlZbdGNQcEtMeF9VSzZvU3FOQ0F4V3pDbFE#gid=0.)
and carbon web (http://www.theguardian.com/news/datablog/2011/jan/31/world-carbon-dioxide-emissions-country-data-co2
) under the category of the environment from Data Visualization links using Google Earth as a DH data visualization
tools.
This was an introductory step so
students can get trained in handling given data using Google Earth and what can
be done with it. In addition the project introduced SPSS/Excel as a DH
simulation tool to show how a concept, mainly a statistical concept, can be
achieved via modeling, graphing and reflecting on the findings. The goal is to
have the students explore, investigate and research widely available databases
once they are comfortable with the idea of using the data to learn the
statistical concept. Specifically, in the first part of this project,
students were asked to use the above link to construct a table for CO2
emissions for USA and the World over time. They were also asked to construct
another table showing population in at least 10 countries, and carbon emissions
per person. Using the collected data, students used polynomial modeling to predict
the level of CO2 emissions after 10, 20 and 30 years. In addition,
students were also able to examine the relationship between population and carbon
emissions per capita. For example, students constructed a linear regression
model and curve fitting using SPSS/Excel and used a linear regression equation to
predict the level of CO2 emissions after 10, 20 and 30 years ( see
the attached student sample).
In this project, the students were introduced a
video of New York carbon emission related to global warming and how carbon
emissions affect globally to increase the temperature (http://www.theguardian.com/news/datablog/2012/oct/25/carbon-emissions-new-york).
This project also introduced how much global warming has raised local
temperatures in your area or elsewhere on the globe using Google Earth. The Google Earth interface shows in the
following figures how the globe has been
split into latitude and longitude grid boxes. Clicking on a grid box reveals
the area's annual temperatures, as well as links to more detailed downloadable
station data.
Curious about how much global warming has caused temperatures around New
York City to rise? Just click on the grid in Google Earth and a graph pops up
showing flat temperatures from 1900 to 1990 followed by a nearly 1°C rise over
the past 25 years.
Wondering how much the area
around Kyoto, Japan has warmed in recent decades? The answer again is just a
click away, and shows a rate of warming.
Students used SPSS/Excel to manipulate the given data and to model the
curve that best fits the values of the data enabling them to accurately
describe the relationship between atmospheric variables. The students were
exposed to the science of the atmosphere studies and global climate change to
learn modeling using linear equations. Based on the students’ feedback,
it appeared that they loved the term-project and they got more engaged during
the process. This is due to the fact that they looked and searched for the data
using visualization link such as Google Earth, Google Earth @ NOAA and
throughout this process they learned a lot more about the theme and the
specific topic of the project. This was expected and this is one of the reasons
that I designed the course with one project with given data and a long-term
project that can be done on multiple phases or parts. For the next semester, I will re-design the project
to be a semester-long project such that it can be divided into multiple phases.
At the same time, and as an effort to test the DH technique and the
readiness of the developed materials and the ease of re-use, I will attempt to
incorporate some visualization database applications in other courses. For
example, since not all the concepts that are used in MAT 120/MAT 121 can be
used in every other course, I will use some of the concepts that are introduced
in multiple parts or phases of the projects and I will incorporate them in MAT
115 and my engineering courses MAE 103 (i.e., Computer-Aided Analysis Tools for
Engineers using MATLAB) and MAE 106 (Introduction
to Earth System & Engineering/Science) in Fall 2014 using Excel.
I have already designed and
developed three DH projects in a Spring I, 2014, MAE 213-Electrical Circuits
Course under the category of simulations and visualizations. The objective of
these projects is to use Multisim software simulation and Matlab software tools
as DH tools (visualization /simulation) to solve electric circuits problems
that require computer simulations and visualization will increase student’s
understanding of electrical circuit theories and concepts. The advantage of
this is that Multisim will help students visualize and simulate their
electrical circuits problem schematically whereas Matlab helps students solve
problems by simulating the working of the circuit itself. I had a plan to
implement these projects in this semester. Due to cancelation of my class in
this semester, I am unable to implement of this activity in my current MAE 213
class. Hopefully I will do so next semester.
Student Sample:
