Learning is personal. For me, learning is on demand, relevant and about making connections. This school year, one of my major goals was to design opportunities for my students to authentically learn more about what they are passionate about. The result is one of my proudest accomplishments as a teacher.
My students in AP Economics have the opportunity- and obligation- to submit assignments of their choosing on a topic of individual interest. This component of our course is labeled Challenge by Choice.
This work gives students the flexibility to choose a focus and application of course concepts. They can choose the format of the work they do (read a newspaper article, write a paper, conduct an interview, film a TV segment, conduct a debate, etc.) and each piece earns points relative to the size of the assignment (points are based on a combination of time, effort, insight, etc.). Students must earn 200 points each semester.
The results have been astonishing and I will be sharing some of their work as we design a sort of online journal and digital poster session. A few highlights include an analysis of the elasticity of school spirit shirts, an investigation into gender inequality within the economics profession, a thorough analysis of the Philadelphia 76ers tanking and “The Process” strategy, interviews with family members who utilize economics, quantifying the profit lost by Ray Consella in “Field of Dreams,”and relevant topics in the headlines such as BitCoin and Net Neutrality.
More importantly, student work sparked in class conversations and dialogue. One student had read the book “Thinking Fast and Slow,” which is one of my favorite books and I was thrilled to talk with a student who was not always the first to speak up in class; this helped him find his voice. Students asked questions about Amazon’s potential move and the relevance of our work on the long term supply of competitive firms. Beyond the work students put in outside of class, the ability to connect core curricular content to their interests and current events deepened their understanding- the ultimate learning outcome.
A few nuts and bolts: This has not been an easy ride. Our Learning Management system Canvas has enabled me to receive submissions, but because these are not traditional assignments (i.e. the point values vary) the grading has been complicated. Some students procrastinated and were on the verge of failing this component of the course. Most of the submissions were written work, which took time to grade and students did not always know how many points they had earned in real-time. I updated students every two or three weeks, but at the end of the semester students wanted to know each day where they stood. I don’t have answers yet as to how to streamline the submission and motivate students’ willingness to move beyond written work, but I hope someone who reads this might offer perspective.
Implementing strategies: If I want students to take this seriously, I knew that I needed to properly incentivize this work. I showed students the image posted above and told them they would be assessed for 40% of their final grade on their challenges (50% is AP style tests and 10% are small assignments). I also gave students two or three days per month to work on their challenges and provided nudges to students in the form of a podcast to listen to or article to read, so students did not feel stuck and had some directive if they needed it.
I am lucky. I teach AP Economics and am able to teach both the AP Microeconomics and Macroeconomics curriculum. I am lucky because there is overlap between these two typically one-semester courses and instead of complaining that I don’t have enough time to prepare my students for their AP Exams, I find myself with a bit of extra time to allow students to deepen their understanding. Ultimately, I hope my students build a foundation of economic understanding that they can apply to their lives. Challenge By Choice is the means to reach that end.
Over 20 million freshmen matriculate into college each year and the most common question we ask them is: Do you know what you’re going to major in? Colleges traditionally require students to declare their major during the second year and some colleges are requiring high school applicants to select a major, thus 18-20 year-olds make a decision that defines their college degree. But does this decision define a career?
To what extent do college graduates work in fields unrelated to their college degree? Luckily the National Survey of College Graduates asks respondents this question directly. Of college graduates, 54% report that their highest degree field of study is closely related to their job. Meanwhile, 25% report that their degree field is somewhat related to their job and 20% report that their field of study is not related to their current job. Demographically, more women than men report that their field of study is closely related to their job (56.3% and 52.5%, respectively).
This data is from the 2013 version of the survey, and the answer to the question “To what extent was your work on your principal job… related to your highest degree?” has remained relatively constant (see figure 1).
While this data only consists of responses from those who are employed (otherwise there is nothing to match), there may be individuals unemployed because of their college major choice.
Ultimately, many choose careers that do not match our formal education and learn on-the-job. Nothing says that salary or happiness is based solely on this match, so the 20% of individuals who report that their field of study is not related to their current job may be doing just fine!
(note: this is the first of three posts relating college majors and careers.)
These are the resources that will be presented on Saturday at 11:00 (room 108 in BCEC).
Handout: Economic Applications NCTM
Slides: NCTM economic applications
I am teaching a hybrid AP Microeconomics course this spring. This is the first of three posts describing my experience teaching this course. The first is the basics about the course. Attached is a FAQ that I sent to students before the class began.
About the Course: AP Microeconomics
- This is a one-semester course.
- It is a hybrid course where students meet once every six school days and complete online readings, activities, and assessments.
- The goal was to add the opportunity for students to fit the course into their schedule and to add the flexibility to students’ workload.
- Students are expected to complete about an hour’s worth of work each day (equivalent of 40 minute class plus 20 minute homework).
- Students use the Learning Management System Canvas.
- Students read from Mankiw’s Principles of Economics textbook.
- Students complete workbook activities from Stone’s AP Microeconomics Resource Manual.
- Students meet in small groups in occasionally non-traditional locations (ie. library or breakout room)
- The schedule was challenging to coordinate everyone’s availability, given that we did not have a dedicated meeting time.
- There are five major resources that we use:
- Videos (short bursts of information)
- Textbook (longer and more theoretical)
- Workbook & Handouts (focusing on mechanics)
- Class (connecting dots and filling in the blanks)
- Discussion Board (with threaded answers to questions, both conceptual and vocabulary)
- Students take online quizzes to test for basic comprehension and completion
- Students take in-person quizzes and tests by scheduling a convenient time.
An economic bubble can be defined as an overvaluation of a product or asset. In the case of Facebook and its looming IPO (initial public offering) this week, I want to describe three potential bubbles relating to facebook.
First is in the literal sense. By most estimations, Facebook will have the largest IPO in history: $100 Billion. Simply, Facebook stock may simply be overvalued. With an inflated price, a classic bubble burst may be on Facebook’s horizon. The rationale for the inflated value may be because of two social networking bubbles.
Facebook uses each user’s personal information to sell ads. That’s how Facebook makes its money. Their ads are targeted based on users’ likes and clicks; they can sell their ads for a higher price because of the targeted audience. The bubble occurs as more people become fed up by the exploitation of their personal information. Once this practice becomes more common knowledge, I believe there will be an exodus from social networking sites that are simply shills for data gathering.
The third potential Facebook bubble is a mass departure by the people who were Facebook’s initial constituents. Now approaching their thirty-somethings, the college students that Facebook originally targeted may be bored by a decade of the social networking site. Many adults (mainly forty-plus) are only on Facebook because of their children. Maybe the hype will catch up with users who are departing their roaring twenties where sharing everything was a way to connect. Those users are now entering into their adult lives and may no longer feel the need to constantly share or to delve into their friends’ every matter.
Whether Facebook repels users by sharing their information or users finally lose interest in social networking, the company faces many unknowns while it emerges as a public company. While twenty years from now Facebook may be the largest company in the world, if I had to put money on it, I would bet that we all look back and see Facebook as an another instance of a dot-com bubble.
In my first (found here) of a three part series on statistical analysis, I discussed how data can inform decisions within countless industries. My research in human capital, and specifically education, provides for various usages of data in decision making. Specifically, available data can be used for predictions of when, where, and which students may have trouble, determinants of parental satisfaction, admission decisions (at both secondary and collegiate levels), and student achievement both academically, on standardized tests, and in future wages.
This post is intended to shed light on the science of data analysis, specifically conditional expectations. The mathematical approach to conditional expectation is based on heavy statistical concepts, some of which are not appropriate for this venue. That being said, my intention is to provide an accessible explanation of the techniques used in statistical analysis. For a mathematical approach, I recommend the seminal text Econometric Analysis, by William Greene, 2002; or Econometric Analysis of Cross Section and Panel Data, by Jeffrey Wooldridge.
Econometrics, and essentially any data analysis, is based on determining a prediction. In statistical terms, this is called an expectation. A conditional expectation is a prediction based on available information.
For instance, consider guessing the height of a random human being. The average human height is 5 foot 6 inches, so, this would be a logical starting point for our prediction. But if we know more information about this random person, we can improve our expectation. Specifically, if we knew the person was male, we would want to change our expectation conditional on that fact. The average height of an adult man is 5 foot 9.5 inches, so that would be our new prediction given some information.
If we also knew that the person weighed 240 pounds, we may want to increase our expected height. Note here that there is no causal assumption, just a change in our expectation, given some piece of information. This is correlation: the taller a person is the more, on average, we expect that person to weigh. We may predict 6 foot 1 inch for our random male weighing 240 pounds. Data analysis can help us with our predictions, given some imperfect information.
Next, consider that we also knew this random person’s SAT score was 1200. We probably would not consider changing our expectation of height. If we had data on a sample of people with the variables height, sex, weight, and SAT score, some variables may be good predictors of height and be statistically significant while others, SAT score in this example, would not be statistically significant and would not persuade us to change our expectation.
Multiple Regression Analysis essentially considers a sample of data and determines the predictive success of each variable. Using the information from a statistical data program (even excel can do this reasonably well), we can arrive at a predictive equation for the most logical expectation conditional on the information we have at our disposal.
The data will find the coefficients- the “B’s”- and also determine the likelihood that each “B” is a significant predictor. In this case, I suspect B3 would not be statistically significant.
In part three, I will discuss an example of student achievement data from a nation-wide sample and how conditional expectations can be used to inform decisions in many fields.
In the past few days, I have come across this question multiple times: “What would happen if there was a negative interest rate?”
First, let me define a positive, then a negative, interest rate. Banks want us to give them our money so that they can lend it to others. The bank pays us to give it our money then charges a premium to others to borrow that same money. A negative interest rate would result in us paying the bank while we give it our money. This is not entirely unfeasible; in fact, with the recent rise in bank fees, this may be the case for some smaller accounts.
In a piece in Slate Online Magazine by Matthew Yglesias, which I commented on in my last post, Yglesias describes a negative interest rate as “in effect a tax on holding cash in the bank”. He continues with the logic that if this were the case, we would all store money in shoeboxes. That is, unless there was no physical money only “electronic” currency that we were forced to pay this “tax” on. Then, he argues we could stimulate demand by “raising this tax” or equivalently making the interest rate more negative.
But even in the simple model economy I described in my last post (The Economic Overlapping Generations Model), a negative interest rate results in saving. Specifically, by the need to store the value of current production. The Value of Money is based on our need to store value not in the interest rate that we receive from the bank.