Category: Learning

Rethinking the Value of a Business Major

Melissa Korn reporting in the Wall Street Journal:

“The biggest complaint,” writes Korn is that “undergraduate degrees focus too much on the nuts and bolts of finance and accounting and don’t develop enough critical thinking and problem-solving skills through long essays, in-class debates and other hallmarks of liberal-arts courses. Companies say they need flexible thinkers with innovative ideas and a broad knowledge base derived from exposure to multiple disciplines.”

That gap in my own knowledge was one of the reasons I started Farnam Street.

Robert Hagstrom, author of Investing: The Last Liberal Art, adds: comments

At first, you might think the “art of achieving worldly wisdom” is an elective you can do without. After all, there is simply not enough time to read all that is required before the next day’s opening bell, and besides, what passes for reading today is more about adding information and less about gaining knowledge. But don’t despair. In the words of Charlie Munger, “we don’t have to raise everyone’s skill in celestial mechanics to that of Laplace and also ask everyone to achieve a similar level in all other knowledge.” Remember, as he explains, “it turns out that the truly big ideas in each discipline, learned only in essence, carry most of the freight.” Furthermore, attaining broad multidisciplinary skills does not require us to lengthen the already-expensive commitment to college education. We all know individuals who achieved a massive multidisciplinary synthesis of knowledge without having to sign up for another four-year college degree.

According to Munger, the key to true learning and lasting success is learning to think based on a “latticework” of mental models. Building the latticework can be difficult, but once done, it can be applied to a wide range of problems. “Worldly wisdom is mostly very, very simple,” Munger told the Harvard audience. “There are a relatively small number of disciplines and a relatively small number of truly big ideas. And it’s a lot of fun to figure out. Even better, the fun never stops. Furthermore, there’s a lot of money in it, as I can testify from my own personal experience.”

If you want to learn more check out A Lesson in Worldly Wisdom.

Arguments Are For Learning, Not Winning

Despite his best efforts and long hours, Nobel-Prize winning physicist and professor Carl Wieman grew frustrated by his inability to teach and his students’ failure to learn.

When I first taught physics as a young assistant professor, I used the approach that is all too common when someone is called upon to teach something. First I thought very hard about the topic and got it clear in my own mind. Then I explained it to my students so that they would understand it with the same clarity I had.

At least that was the theory. But I am a devout believer in the experimental method, so I always measure results. And whenever I made any serious attempt to determine what my students were learning, it was clear that this approach just didn’t work. An occasional student here and there might have understood my beautifully clear and clever explanations, but the vast majority of students weren’t getting them at all.

In a traditional classroom, the teacher stands at the front of the class explaining what is clear in their mind to a group of passive students.

Yet this pedagogical strategy doesn’t positively impact retention of information from lecture, improve understanding of basic concepts, or affect beliefs (that is, does new information change your belief about how something works).

Alison Gopnik, says “I don’t think there’s any scientist who thinks the way we typically do university courses has anything to do with the best methods for getting people to learn. ”

Given that lectures were devised as a means of transferring knowledge from one to many, it seems obvious that we would ensure that people retain the information they are consuming.

Wieman mentions three studies, the last of which perfectly emphasizes the disturbing point that passive lectures do not seem to work.

In a final example, a number of times Kathy Perkins and I have presented some non-obvious fact in a lecture along with an illustration, and then quizzed the students 15 minutes later on the fact. About 10 percent usually remember it by then. To see whether we simply had mentally deficient students, I once repeated this experiment when I was giving a departmental colloquium at one of the leading physics departments in the United States. The audience was made up of physics faculty members and graduate students, but the result was about the same—around 10 percent.

Wieman argues these results are likely generic and make a lot of sense if you consider the extremely limited capacity of short-term memory.

The research tells us that the human brain can hold a maximum of about seven different items in its short-term working memory and can process no more than about four ideas at once. Exactly what an “item” means when translated from the cognitive science lab into the classroom is a bit fuzzy. But the number of new items that students are expected to remember and process in the typical hour-long science lecture is vastly greater.

The results were similarly disturbing when students were tested to determine understanding of basic concepts. More instruction wasn’t helping students advance from novice to expert. In fact, the data indicated the opposite: students had more novice-like beliefs after they completed a course than they had when they started.

We’re left with a puzzle about teaching. The teachers, unquestionably experts in their subjects, are not improving the learning outcomes: students are not learning the concepts. How can this be?

Research on learning provides some answers.

Cognitive scientists have spent a lot of time studying what constitutes expert competence in any discipline, and they have found a few basic components. The first is that experts have lots of factual knowledge about their subject, which is hardly a surprise. But in addition, experts have a mental organizational structure that facilitates the retrieval and effective application of their knowledge. Third, experts have an ability to monitor their own thinking (“metacognition”), at least in their discipline of expertise. They are able to ask themselves, “Do I understand this? How can I check my understanding?”

A traditional science instructor concentrates on teaching factual knowledge, with the implicit assumption that expert-like ways of thinking about the subject come along for free or are already present. But that is not what cognitive science tells us. It tells us instead that students need to develop these different ways of thinking by means of extended, focused mental effort. Also, new ways of thinking are always built on the prior thinking of the individual, so if the educational process is to be successful, it is essential to take that prior thinking into account.

This is basic biology. Everything that constitutes “understanding” science and “thinking scientifically” resides in the long-term memory, which is developed via the construction and assembly of component proteins. So a person who does not go through this extended mental construction process simply cannot achieve mastery of a subject.

This reminds me a lot of what Charlie Munger said on mental models:

What is elementary, worldly wisdom? Well, the first rule is that you can’t really know anything if you just remember isolated facts and try and bang ‘em back. If the facts don’t hang together on a latticework of theory, you don’t have them in a usable form.

You’ve got to have models in your head. And you’ve got to array your experience both vicarious and direct on this latticework of models. You may have noticed students who just try to remember and pound back what is remembered. Well, they fail in school and in life. You’ve got to hang experience on a latticework of models in your head.

What are the models? Well, the first rule is that you’ve got to have multiple models because if you just have one or two that you’re using, the nature of human psychology is such that you’ll torture reality so that it fits your models, or at least you’ll think it does…

It’s like the old saying, ”To the man with only a hammer, every problem looks like a nail.”

Students are not learning the basic concepts that experts rely on to organize and apply information. And they are not being aided in developing the mental framework – the latticework – they need to improve retrieval and application of knowledge. “So it makes perfect sense,” Wieman writes “that they are not learning to think like experts, even though they are passing science courses by memorizing facts and problem-solving recipes.”

Improved teaching and learning

A lot of educational and cognitive research can be reduced to this basic principle: People learn by creating their own understanding. But that does not mean they must or even can do it without assistance. Effective teaching facilitates that creation by getting students engaged in thinking deeply about the subject at an appropriate level and then monitoring that thinking and guiding it to be more expert-like.

So what are a few examples of these strategies, and how do they reflect our increasing understanding of cognition?

Reducing Cognitive Load

The first way in which one can use research on learning to create better classroom practices addresses the limited capacity of the short-term working memory. Anything one can do to reduce cognitive load improves learning. The effective teacher recognizes that giving the students material to master is the mental equivalent of giving them packages to carry. With only one package, they can make a lot of progress in a hurry. If they are loaded down with many, they stagger around, have a lot more trouble, and can’t get as far. And when they experience the mental equivalent of many packages dumped on them at once, they are squashed flat and can’t learn anything.

So anything the teacher can do to reduce that cognitive load while presenting the material will help. Some ways to do so are obvious, such as slowing down. Others include having a clear, logical, explicit organization to the class (including making connections between different ideas presented and connections to things the students already know), using figures where appropriate rather than relying only on verbal descriptions and minimizing the use of technical jargon. All these things reduce unnecessary cognitive demands and result in more learning.

Addressing Beliefs

A second way teachers can improve instruction is by recognizing the importance of student beliefs about science. This is an area my own group studies. We see that the novice/expert-like beliefs are important in a variety of ways—for example they correlate with content learning and choice of major. However, our particular interest is how teaching practices affect student beliefs. Although this is a new area of research, we find that with rather minimal interventions, a teacher can avoid the regression mentioned above.

The particular intervention we have tried addresses student beliefs by explicitly discussing, for each topic covered, why this topic is worth learning, how it operates in the real world, why it makes sense, and how it connects to things the student already knows. Doing little more than this eliminates the usual significant decline and sometimes results in small improvements, as measured by our surveys. This intervention also improves student interest, because the beliefs measured are closely linked to that interest.

Stimulating and Guiding Thinking

My third example of how teaching and learning can be improved is by implementing the principle that effective teaching consists of engaging students, monitoring their thinking, and providing feedback. Given the reality that student-faculty interaction at most colleges and universities is going to be dominated by time together in the classroom, this means the teacher must make this happen first and foremost in the classroom.

To do this effectively, teachers must first know where the students are starting from in their thinking, so they can build on that foundation. Then they must find activities that ensure that the students actively think about and process the important ideas of the discipline. Finally, instructors must have mechanisms by which they can probe and then guide that thinking on an ongoing basis. This takes much more than just mastery of the topic—it requires, in the memorable words of Lee Shulman, “pedagogical content knowledge.”

Arguments Are For Learning, Not Winning

Is arguing the path towards learning?

I assign students to groups the first day of class (typically three to four students in adjacent seats) and design each lecture around a series of seven to 10 clicker questions that cover the key learning goals for that day. The groups are told they must come to a consensus answer (entered with their clickers) and be prepared to offer reasons for their choice. It is in these peer discussions that most students do the primary processing of the new ideas and problem-solving approaches. The process of critiquing each other’s ideas in order to arrive at a consensus also enormously improves both their ability to carry on scientific discourse and to test their own understanding.

Kathryn Schulz on why Knowledge Collapses as often as it Accretes

Kathryn Schulz comments on the fantasy that knowledge is static in This Will Make You Smarter: New Scientific Concepts to Improve Your Thinking.

Because so many scientific theories from bygone eras have turned out to be wrong, we must assume that most of today’s theories will eventually prove incorrect as well. And what goes for science goes in general. Politics, economics, technology, law, religion, medicine, child-rearing, education: no matter the domain of life, one generation’s verities so often become the next generation’s falsehoods that we might as well have a Pessimistic Meta-Induction from the History of Everything.

Good scientists understand this. They recognize that they are part of a long process of approximation. They know that they are constructing models rather than revealing reality…

The rest of us, by contrast, often engage in a kind of tacit chronological exceptionalism. Unlike all those suckers who fell for the flat earth or the geocentric universe or cold fusion or the cosmological constant, we ourselves have the great good luck to be alive during the very apex of accurate human thought. The literary critic Harry Levin put this nicely: “The habit of equating one’s age with the apogee of civilization, one’s town with the hub of the universe, one’s horizons with the limits of human awareness, is paradoxically widespread.” At best, we nurture the fantasy that knowledge is always cumulative, and therefore concede that future eras will know more than we do. But we ignore or resist the fact that knowledge collapses as often as it accretes, that our own most cherished beliefs might appear patently false to posterity.

That fact is the essence of the meta-induction — and yet, despite its name, this idea is not pessimistic. Or rather, it is only pessimistic if you hate being wrong. If, by contrast, you think that uncovering your mistakes is one of the best ways to revise and improve your understanding of the world, then this is actually a highly optimistic insight.

The book is a curated collection of answers to the question: What scientific concept would improve everybody’s cognitive toolkit? All of the answers are available online in their entirety.

Still curious? Knowledge, like milk, has an expiry date.

The Seductive Path of Good Enough

The ability to learn new skills is the entry ticket for being a knowledge worker. If you can’t learn and adapt, you fall flat on your face. But not all of us learn at the same pace, and not all of us reach the same level of mastery. Some of us get better with experience, and some of us seem to keep making the same mistakes over and over. Why?

When we learn any new skill, we usually learn just enough to become competent, and then our brains switch to autopilot. They’re lazy that way.

The brain tries to conserve as much energy as it can. And while practice is easy, deliberate practice is not.

So much of success is just showing up day after day and grinding away at the hard parts in a deep and focused way. However simple that sounds, it’s not easy. And that’s why most of us struggle to get better.

Perhaps an example will help illustrate what I’m talking about. Consider driving. Most of us can drive. It’s a skill we learned. At first, we were terrible and nervous. Through deliberate practice and coaching, we got better and better. We reached some level of competence and verified this through a test. I don’t know about you, but despite having spent thousands of hours behind the wheel since then, I’ve probably gotten only marginally better at driving.


There are many reasons. One is that I lack feedback. There is no expert coaching me and telling me where to improve. Another reason is that I don’t even know what I want to improve. What does it mean to become a better driver? Getting better sounds like a lot of work. And that’s the rub.

We’re hard-wired to avoid pain. This tendency includes reflecting on our decisions as well as practicing skills. Once we reach some base level of competence, we practice that part over and over and shy away from the parts that might make us better. In short, I’ve been driving the same way for thousands of hours, practicing skills I already had instead of trying new things.

“By nature, we humans shrink from anything that seems possibly painful or overtly difficult.”

— Robert Greene

However, a base level of competence doesn’t get us ahead of anyone or set us apart. The base-level comprises the most easily acquired aspects of any particular skill and the bare minimum we need to do to claim that skill. And most of the time, we’ve learned the conventional way of doing things — it’s a form of social proof where we just mimic what other people have done. Because we acquire the most easily accessible parts of any skill, we also over-estimate our competence. (I think this is why we all rate ourselves as above average at very basic things like driving.)

Stopping here is a hallmark of amateurs.

The only way to get better at a task is through deliberate practice. The idea is simple: instead of avoiding pain, you dive in. How?

First, use the mental model of Galilean Relativity to switch perspectives and see yourself through the eyes of others. This will allow you to recognize the areas that you need to improve. Recognizing these areas is necessary if you want to improve.

Second, set aside time for dedicated focus on the specific area you want to improve. A lot of people don’t understand this, but when you’re really focused on something, you can rapidly get better at it. At any given time, most of us are only half-focused on what we’re doing. (How many browser tabs are open right now? What’s on your grocery list?) You really need to immerse yourself in the task at hand.

You also need feedback. Sometimes the task itself can give you feedback, sometimes you’ll want a coach, and sometimes you can have both. When I was learning to drive, the car was giving me instant feedback, but my learning was accelerated by having a coach tell me what was happening, why, and how I could handle it.

Third, push the limits of what you can do so you understand your boundaries. This also helps you stay calm if things don’t go as planned. Driving in the snow is not easy, and it’s often dangerous. I remember one day when my instructor took me to an empty parking lot covered in snow. He looked at me and said, “I want you to go as fast as you can and lose control of the car.”

I was shocked.

“You’re going to lose control of a car in the snow at some point. Might as well be here where no one is around.”

And that day probably saved my life. I knew what it felt like to lose control of the car. And because I knew what to expect, I wasn’t panicked when it happened. More important, through practicing over and over for hours, I knew the best strategies to regain control of the car.

Finally, rinse and repeat over and over again.

You don’t want to do this level of work with every skill. But if you can identify the ones that give you leverage, doing this work is how you get better.

Charlie Munger: How to Teach Business School

From Charlie Munger at the 2011 Berkshire Hathaway Shareholders Meeting:

Costco of course is a business that became the best in the world in its category. And it did it with an extreme meritocracy, and an extreme ethical duty—self-imposed to take all its cost advantages as fast as it could accumulate them and pass them on to the customers. And of course they’ve created ferocious customer loyalty. It’s been a wonderful business to watch—and of course strange things happen when you do that and when you do that long enough. Costco has one store in Korea that will do over $400 million in sales this year. These are figures that can’t exist in retail, but of course they do. So that’s an example of somebody having the right managerial system, the right personnel solution, the right ethics, the right diligence, etcetera, etcetera. And that is quite rare. If once or twice in your lifetime you’re associated with such a business you’re a very lucky person.

The more normal business is a business like, say, General Motors, which became the most successful business of its kind in the world and wiped out its common shareholders… what, last year? That is a very interesting story—and if I were teaching business school I would have Value-Line-type figures that took me through the entire history of General Motors and I would try to relate the changes in the graph and data to what happened in the business. To some extent, they faced a really difficult problem—heavily unionized business, combined with great success, and very tough competitors that came up from Asia and elsewhere in Europe. That is a real problem which of course… to prevent wealth from killing people—your success turning into a disadvantage—is a big problem in business.

And so there are all these wonderful lessons in those graphs. I don’t know why people don’t do it. The graphs don’t even exist that I would use to teach. I can’t imagine anybody being dumb enough not to have the kind of graphs I yearn for. [Laughter] But so far as I know there’s no business school in the country that’s yearning for these graphs. Partly the reason they don’t want it is if you taught a history of business this way, you’d be trampling on the territories of all the professors and sub-disciplines—you’d be stealing some of their best cases. And in bureaucracies, even academic bureaucracies, people protect their own turf. And of course a lot of that happened at General Motors. [Applause]

I really think the world … that’s the way it should be taught. Harvard Business School once taught it much that way—and they stopped. And I’d like to make a case study as to why they stopped. [Laughter] I think I can successfully guess. It’s that the course of history of business trampled on the territory of barons of other disciplines like the baron of marketing, the baron of finance, the baron of whatever.

IBM is an interesting case. There’s just one after another that are just utterly fascinating. I don’t think they’re properly taught at all because nobody wants to do the full sweep.


Value Process Before Results

More insight from The Art of Learning: An Inner Journey to Optimal Performance:

The issue is fundamental to the pursuit of excellence in all fields. If a young basketball player is taught that winning is the only thing that winners do, then he will crumble when he misses his first big shot. If a gymnast or ballet dancer is taught that her self-worth is entirely wrapped up in a perfectly skinny body that is always ready for performance, then how can she handle injuries or life after an inevitably short career? If a businessperson cultivates a perfectionist self-image, then how can she learn from her mistakes?

And this quote based on research by Dr. Carol Dweck.

Children who are “entity theorists” … are prone to use language like ‘I am smart at this.’ And to attribute their success or failure to an ingrained and unalterable level of ability. They see their overall intelligence or skill level at a certain discipline to be a fixed entity, a thing that cannot evolve. Incremental theorists, who have picked up a different modality of learning, are more prone to describe their results with sentences like ‘I got it because I worked very hard at it’ or ‘I should have tried harder.’ A child with a learning theory of intelligence tends to sense that with hard work, difficult material can be grasped- step-by-step, incrementally, the novice can become the master.