For the first Action Project in Economics, GCE Seniors investigated the following guiding question:
How do you determine the value of your college education?
Here’s the scenario students were challenged with:
You are a high school senior and you are deciding whether to go to college, enroll in community college, or seek an internship next Fall. You are financing the entire cost of your education to pursue the career of your choice. You have heard that college has never been more expensive to attend. Between 2000 and 2010, the average cost of attending a private, 4-year institution has increased over 35%. However, your parents might think it’s worth it. The US Census Bureau data seems to agree, publishing a study that suggests college grads earn 74% more than those with a just a high school diploma. From your Economics class, you learned that over a lifetime that difference can mean more than a million dollar in forgone income.
Your peers, family, teachers, and school administrators are excited to hear what you decide to do next year and why. In a 60 second video, explain your decision for next year and explanation. Your video is an executive summary. It must be accompanied by an in-depth analysis of your decision-making. Acceptable formats are 2-3 page paper or 5-15 slide power-point presentation.
Click on the different career cards to take a closer look at the featured student works.
National Standards: Project Alignment with Common Core Math & NextGen Standards
CED.A.1 Create equations and inequalities in one variable and use them to solve problems. Include equations arising from linear and quadratic functions, and simple rational and exponential functions.
CED.A.2: Create equations in two or more variables to represent relationships between quantities; graph equations on coordinate axes with labels and scales.
REI.C.6: Solve systems of linear equations exactly and approximately (e.g., with graphs), focusing on pairs of linear equations in two variables.
ID.C.7: Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.