Deeper Learning in Macroeconomics

Sarah Fine and Jal Mehta have a new book In Search of Deeper Learning. Their focus is on deeper learning in high schools. I want to explore the possibility of deeper learning in college macroeconomics.

What is Deep Learning?

In an interview with Liz Mineo for the Harvard Gazette, Jal Mehta defined “deeper learning” this way:

Deeper learning is the understanding of not just the surface features of a subject or discipline, but the underlying structures or ideas. If we were talking about a biological cell, shallow learning would be able to name the parts of the cell; deeper learning would be able to understand the functions of the cell and how they interrelate. 

When you listen to the show “Car Talk,” you are listening in on a conversation between someone who has a shallow understanding of their car and someone who has a deeper understanding. A person will call in and say, “My car tends to slow down when it rains.” And then one of the guys will say, “Well, does it happen more in hot weather or cold weather?” The caller can only see the symptoms; the person at the other end of the phone can see the system and has some underlying theory or diagnosis of what might be happening.

In the same interview, Jal also explains where and when deeper learning is most likely to happen:

… deeper learning tends to emerge at the intersection of mastery, identity, and creativity. Mastery is developing significant knowledge and skill; identity is seeing yourself as connected to doing the work; and creativity is not just taking in knowledge but doing something in the field. When those three elements come together, it often yields deep learning. …

When we visited schools, we asked students, teachers, and administrators to point us to the most powerful learning spaces in their schools. They frequently pointed to elective classes and extracurricular spaces.  

… we did a deep dive on theater and debate, and those were really different domains, but they shared a number of elements. It started with purpose — students knew why they were there, what they were trying to produce, and why it mattered. There was also a much stronger sense of community in extracurriculars; students described these places as like “family.” And there was lots of opportunity for student leadership as opposed to passively receiving knowledge. There was lots of intrinsic motivation and passion — that’s the identity and creativity parts of deep learning. But there was also a lot of careful feedback, practice, and refinement — that’s the mastery part. 

… the best core classes shared the same characteristics as the extracurriculars; there was a purpose created either by a project, an essential question, or by an authentic thing that was trying to be produced. There was a real attention to trying to build the right kind of community; there was a lot of peer learning by watching how other students were doing work or making comments.

Engaging with the Big Questions in Macroeconomics (or in Economics More Broadly)

At the University of Colorado Boulder,  I teach a class of about 100 students in Intermediate Macroeconomics. That stage of learning about macroeconomics and the sheer size of the class makes it difficult to assign a large term project that would force students to dig deeply into an issue in macroeconomics, but I give students the opportunity to dig deeply if they are willing to seize it. I assign weekly blog posts (on an internal class blog) that can be used to examine different angles of a given topic or to explore different topics. And even when a student explores ostensibly different topics in each blog post, I am a big believer that there is almost always a theme that answers the questions “Why am I interested in this set of things? What is the connection between them?”

In my view, the degree of personal initiative needed to seize the opportunity to make the writing assignments a deep learning experience is an appropriate level of personal responsibility for college as contrasted with high school. Those students who take that initiative will find the class much more rewarding.

Macroeconomics, in particular, offers many deep questions to wrestle with. Every day I see people wrestling with big questions in Economics Twitter. Here are just some of the big questions:

  1. What caused the take-off into modern economic growth?

  2. What policies and what political equilibria can get countries that are still poor onto the track toward getting richer as Japan, Southeast Asian countries, China and India have?

  3. Should fiscal policy or monetary policy take the lead in taming business cycles?

  4. How should monetary policy adjust to the increasingly frequent situations in which the short-term interest rate needed in order to provide enough stimulus is lower than the traditional zero interest rate on paper currency?

  5. What will it take to avoid another financial crisis like the Financial Crisis of 2008?

  6. What should we do about rising inequality? What are the side-effects of different ways of trying to address inequality?

  7. What is the best way of aligning the interests of corporations with the common good? Was Milton Friedman right in saying that telling them to maximize shareholder value will yield the best outcomes for the economy?

  8. What causes trade deficits? How could we reduce the trade deficit? Should we?

  9. Is immigration good for the economy or bad for the economy? If it is good for some people and bad for others, who is it good for and who is it bad for? How is the answer different when immigration policy is designed to shift the balance of immigrants to high-skill immigrants?

  10. How do labor market policies affect the economy as a whole?

  11. Have colleges lost their way? How effective are colleges at helping their students build human capital?

  12. How should we be evaluating the performance of governments? For example, should GDP be supplemented or supplanted by a National Well-Being Index? If so, on what principles should it be designed?

  13. In helping get people what they want, what is the right balance between the four main domains of the economy: the government, non-profits, for-profit activity, household production that is not exchanged in the market?

  14. Which economic regulations are bad and which are good? What are the essential economic regulations needed to effectively establish property rights?

  15. How can we slow global warming in a way that has the lowest cost to other economic objectives that we have? How can we build a political coalition to do that?   

Math and Deep Learning

In his examples of deep learning, Jal Mehta tends to give examples that are about thinking with words or honing words. And he talks about algorithms as if they were the antithesis of deep learning:  

The bad news was that in these schools, which had been recommended as places that did 21st-century learning or particularly rigorous forms of traditional learning, students still experienced a lot of unchallenging instruction; they were doing a lot of worksheets and tasks that were pretty low level, where they were expected to memorize content and apply algorithms rather than analyze, synthesize, and create.

For me, designing an algorithm is one of the true challenges for deep learning. Using an algorithm may or may not be an occasion for deep learning. The deep learning in relation to using algorithms is often about learning which algorithm to use in different situations, how to identify the inputs into the algorithm and how to interpret the numbers an algorithm produces. The algorithm itself may seem simple, without much depth, but once all of these challenges in using an algorithm appropriately are thought of as part of learning the algorithm, an algorithm can be an occasion for deep learning.

I teach many algorithms in my “Intermediate Macro” class because I think the questions of “What happens?” and “How much?” are essential for macroeconomics. As just one example of where the question “How much?” matters, there are many, many people on Twitter and in politics think they can get enough resources to do vast government programs from printing money. Seignorage, the effective government revenue from printing money, just isn’t that big. People can get very excited about something like seignorage because it is an unusual type of thing, but then overestimate just how big a deal it is, if they don’t do the arithmetic. Sometimes deep learning can be figuring out the difference between an effect existing and an effect being substantial in size.

Less is More

There is a tradeoff between deep learning and “covering” a lot of material. “Covering” a lot of material often amounts to a lot of time spent in giving the instructor the delusion that the students have a large set of ideas firmly in hand. True engagement by students requires taking longer for each key idea. Jal Mehta says this in his interview by Liz Mineo:

We define them as compelling teachers when they give their students a challenging, higher-order thinking task, and where at least three-quarters of the students were highly engaged with that task. … These teachers created spaces where they brought together rigor and joy and which were intellectually demanding, but also open, playful, and warm. … They emphasized coverage less and seeing things from different angles more.

Students as Scientists

Any deep learning requires students exercising their own minds in many ways. Jal says this to Mineo: 

Our most compelling teachers viewed their students as essentially inquirers in the subjects they were pursuing; the students were the historians or the scientists. They were trying to help students to own the standards of their fields or disciplines and also inspire them to get interested in their subjects in the long run.

… It takes time to develop knowledge, skill, and mastery over a domain, and these teachers were trying to get students excited about this trajectory.

In economics, the answers to many questions are still disputed, so taking the role of a scientist is not only a good way to learn, it is necessary in order to make a decision for yourself among competing ideas. Even when I only lay out only one view in my lectures, that view often differs enough from the view in the textbook or the view in an earlier class that there are plenty of different views for students to wrestle with if they are willing. A key here is to realize that a state of being confused is a gateway to deep learning.

What is wrestling with different views? It is asking the question of how someone could believe each view and then asking yourself what you believe after you have the backup for each view kicking around in your head. Euclid, who formalized the geometry you learned in high school thousands of years ago, is reputed to have said “There is no royal road to geometry.” I am saying “There is no road to deep learning that does not pass through a period of feeling confused.” Feeling confused along the way is not a problem. Thinking that feeling confused means you should give up is a big problem. I can tell you that cutting-edge research almost always involves going through a period of feeling confused. There is great honor in feeling confused because you are trying to understand something deeply.

Motivating Students and Making Things Fun

To me, economics is fascinating. I tend to teach as if everyone found it as intrinsically fascinating as I do. But I realize that, in fact, students come into my class with a wide variety of different motivations, almost none of which I understand. I would love to have more students tell me what it is they hope to get out of their Intermediate Macro class. If I understood better what interests my students come into the class with, I could thicken the connection of what we are doing in class those interests. Sometimes the connection might be that those interests stem from what I see as a faulty view of macroeconomics, but there should always be some way to connect things.

I would also love to have more students tell me what kinds of spice they like to have added to lectures. My primary goal will always be learning that lasts. But if, within my abilities, I can see how to make lectures more fun without sacrificing learning that lasts, I’ll try to do it.

Finally, I’d love to get feedback from other professors about what they think motivates students and what keeps things fun for students in macroeconomics. They might be interested in turn in what I have to say about my approach in “On Teaching and Learning Macroeconomics.” One possible motivation for wanting to learn macroeconomics is to be able to understand the newspaper as it talks about the big important events of the day. That is the objective for learning macroeconomics that, so far, I have been most focused on in my teaching.