What the Best College Students Do

Chapter 7 gives examples of students who resisted the urge to specialize too soon and later enjoyed successful and productive careers because of their ability to explore wide fields of knowledge. Chapter 8 accepts that tests are important and must be passed, and it presents techniques for doing just that.

Mount Sinai Medical School’s experiment in training liberal arts majors as doctors was a success. These graduates tended to go into primary care fields, filling much-needed positions in neighborhood healthcare. Their strong performance points to the importance of “high touch” skills like communication, compassion, and thoughtful awareness of another person’s beliefs and needs. (It’s also possible that liberal arts majors are simply less experienced with the math and engineering training required for many of the highly specialized, and more lucrative, medical fields.) The general point is that a variety of viewpoints and perspectives can be useful in science, especially in a field as densely complex as medicine.

One way to transcend surface learning and engage deeply with college studies is to have a grand purpose, and a common one is social justice and helping the needy and the exploited. As the book progresses, it becomes clear that the author’s view of a good education includes guiding students toward compassion for the downtrodden and, often, career-making decisions to right the wrongs of society. Many or most of the examples of successful students presented in the text are people who have gone into fields involving social justice: Will Allen and decent food for the inner city; Mary Ann Hopkins and Doctors Without Borders; David Protess and the Innocence Project; Meixi Ng and disadvantaged youth.

Within students’ descriptions of college life, deep study, and late-night conversations, “We heard […] a pervasive concern for justice” (211). The author quotes philosopher Andrew Chrucky: “‘Liberal education should,’ he wrote, ‘empower individuals to try to reach agreements…on what is economically and politically advantageous to everyone’” (209-10).

Learning that includes a variety of perspectives ought, naturally, to lead toward a better understanding of, and sympathy for, the concerns of people outside our normal experience. One implication is that students who learn to focus on deep learning instead of grades have already abandoned the acquisitive mindset; their life purpose is more likely to revolve around improving society than earning a lot of money.

The benefits of this type of education are not limited to college students. A bachelor’s degree is a feather in one’s cap, and many jobs are closed to people without them. There’s also an argument that college life—laboratories, athletic fields, art studios, personal contact with professors, and the give-and-take of college classes and dorm living—provides a unique experience. However, much of the knowledge available at colleges and universities is also available, virtually for free, in libraries or on the Internet. Sports, the arts, and good conversations aren’t limited to college campuses. Those benefits can, with a bit of ingenuity, be cobbled together from daily life in the modern world. Many of the students profiled in the book also developed their spirits of curiosity and enthusiasm for learning well before college. The concentration of high-quality encounters, discoveries, and ideas available at a college or university is hard to find anywhere else, but the author’s point is that students should avail themselves of such resources as part of deep learning.

Either way, exams happen, and one of the study aids mentioned in Chapter 8 is to learn the material as if you were going to teach it. In a version of this approach called the Feynman Technique (named after the late Nobel physicist Richard Feynman, a widely admired science teacher), the student learns a subject and then teaches it to a child. If the explainer can’t put the concepts into simple, direct language, it’s a sign they don’t yet fully grasp the material.

The author suggests ways to memorize facts, including repetition and association. Repetition works, but it takes a lot of time. Association—embedding a fact into information you already know—is one of the most commonly recommended techniques described in books on memorization. The idea is to associate a fact with vivid imagery that’s easy to remember. A series of connected facts, for example, can be recalled by embedding them in a silly story. A grocery list containing bread, soup, fish, and celery might be strung together as, “The bread dives into a pond of soup, and fish, trying to escape, leap out of the pond but end up snagged in a tree made of celery.” Another technique is a “memory palace,” in which a familiar interior, like the inside of a house, contains hooks on which facts are hung. The author also mentions spaced-repetition memorization apps Anki and SuperMemo for general-purpose learning and the Pimsleur programs for languages; many others are available online.

For those who want the benefits of deep learning and the reward of good grades, one method is to pursue inspired studies for most of the session, then brush up on detailed knowledge in the days just before an exam. Another approach is to take a weekly inventory of class requirements and do catch-up reading in areas relevant to the test. Term papers can be approached similarly, with deep learning and drafts of important ideas piling up, followed by a final assembly and tight edit just before the due date.

If, at the end of four years of higher education, the student has learned how to think deeply and has discovered a life purpose, that student will be better able to find inspiring work. Those jobs also tend to pay more. Thus, the deep-learning approach can solve for both sides of the university equation—a grand purpose and the ability to enter a higher paying, more satisfying career.

In the Epilogue, the author mentions professors who still believe many students are suited only for “routine expertise”; he notes that such surface knowledge “may quickly become outdated and stale” (260). This is already coming true as middle-class job security is eroded by computers and robots. A growing population of frustrated workers, trained at colleges that didn’t care if students acquired wide learning, now search for jobs while lacking a robust ability to strategize and re-train. This is a strength they might have acquired if higher education had stressed it. The best thing college students can learn isn’t a particular set of skills that may soon become obsolete, but a wide perspective that brings with it an increased ability to adapt, adjust, and innovate. They will then find their way to the problems and needs that cry out for help in a rapidly changing world.

For the student who must work a side job while at school, cramming for tests may seem all they have time for. The extra effort they make to understand the material, however, generates memory connections that help at test time. This process embeds those facts more firmly in memory, which will prove useful later on the job.

Cynical students may respond, “Employers only care about the degree! Besides, college doesn’t teach you how to work for a particular employer. That company will train you in its system. Deep learning is a waste of time.” This attitude is short-sighted. Deep learning makes students smarter at anything they attempt, and their performance at a new job will likely exceed that of the students who studied merely for the exam. Moreover, it helps them acquire the knowledge, perspective, and—perhaps—wisdom that can benefit them in all areas of life.

Some readers might argue that the author selects successful people and then cherry-picks their biographies to make their good outcomes comport with his theories about the value of deep education. The point of the examples isn’t so much to prove a theory as it is to present cases of people whose unorthodox approach to learning served them well in college and later years. It’s true that their experiences vary a lot, yet this variety supports the thesis that there’s no specific, programmed way to approach deep learning other than with curiosity and the urge to know more: “for the people we interviewed, the particular ingredients of their worldviews varied, as did the wellspring that gave it life, in each case rooted in individual circumstances” (54).

The author never explicitly defines deep learning—the central concept of the book—yet by the end of the final chapter the reader should have a strong sense of what deep learning is all about. Perhaps this is because it takes an entire book to make clear a term that contains universes of thought and an open-ended list of skills to master. The author also discusses deep learning in his previous book, What the Best College Teachers Do.

The students profiled in the book credit much of their success to their wide interests and passionate pursuit of knowledge during and after their formal studies. Many of them were that way as children, but all of them were that way in college. The core principle of the book is to follow curiosity where it leads, but each student’s experience will be unique. Pursued diligently, the results will be tailored to an individual's preferences, adjusted to account for that person’s strengths and weaknesses. The end result isn’t just another new cog in the corporate machine but a vibrant young mind with a uniquely evolving perspective and a rapidly growing skill set that will bring value to the world no matter where that person ends up.