A great book. Totally needs to be read by all students, lifelong learners, professionals etc., especially of the older cohorts who want to learn, but maybe never learned how to learn purposefully. It’s often the case in the United States especially, that people have a belief that everyone can learn, but the “rate” of learning some item is fixed by the individual. Although few in the country would state it that way, it will often come out in casual conversation as “Oh I’m not a math person”, or “I’m just not good at that.” The history of this mind-meme/belief is long, and in the case of the United States, I suspect it’s tied to the country’s dark history with eugenics in the late 19th and early 20th century, and one will still see “respectable” academics today tout notions like IQ, as a human-invariant.
Luckily, however, this seems to not really be the case. Or perhaps more conservatively, if there is truly a fixed-rate of learning, up to an individual, it is the case that the range by which your “fixed” rate of learning can roam, is quite large, and thus, for most people’s purposes the fixture will be functionally inconsequential in their lives. How does one explore that range? That’s what this book is about. To be clear, this book has a large intersection-set with many other books in the genre, including very good ones, written by Cal Newport and Scott Young’s “Ultralearning,” and others not so good (which you can see from my past reviews which are). What I like about this book is not so much unique content (although to be sure there are distinct content from the other two in here), but the tightness of the organization of the content into something cohesive, a theory of the case.
The author’s thesis is simple, to effectively learn one must be able to personalize the information in some way, once this is achieved, it helps motivate the material. While engaging the material, there must be some kind of stress, a struggling that occurs with respect to grasping (and ultimately mastery in the beyond), but this struggle should be augmented with feedback through mentorship (which the author believes is the best mode of information delivery), and ultimately, there must be the revision of this understanding, introspection. I’ve come to a similar system as the authors through the hard way (something akin to random depth first search unfortunately), and thus only relatively recently started to implement a similar system for myself.
That being said, both as a student and mentor, I have found this system to be extremely effective, especially for highly technical material. First, contextualization is key. There is however, another word for this process, the “thought experiment” (or gedankenexperiment as made famous by Albert Einstein). By almost “anthropomorphising” the phenomena you are studying, whether that be a light wave or a search algorithm, you can better leverage the sophisticated bit of neural net kit in your head, your mind, to make connections and learn better (and faster). Unfortunately, too often in higher education for the past 30 - 40 years, “concretizing” abstraction has been viewed as a “lower” kind of thinking. However, the truth is, when reading the primary documentation of many pioneers in science/technology/engineering/mathematics, one will find the ability to analogize, one of the primary tools to achieve contextualization/personalization is absolutely critical deep understanding. The author’s points here are absolutely spot on.
The author adds many little tips and hints on how he has achieved functional abilities within each process, and I very much appreciated these as many books in this genre are often vehicles for second-hand delivery of research in neuroscience or psychology (many of these research papers are often underpowered statistically, which explains why there’s a never-ending stream of papers that often contradict each other every few years and hence, a never ending stream of layman books to report on them to the mass public). This book does not do that (much), the tips it provides are fairly useful and can be put to practice. For instance, the bit on improving memory towards the last 1/5th of the book were good, which introduced them via a recounting the study regiment of a former Jeopardy champion, and applying that regiment (intelligent timed-review of facts dependent on successful recall over a long time-interval) is something I will implement for my own purposes. I would have liked more of these tactical tools, but that’s really not the purpose of this book.
Overall, I am happy with this book, for the more functionally-minded, I think it delivers a good balance of stories, pop-neuroscience, and practical advice, and packages it all within a great meta-thesis (appropriate since the author’s meta-cognition is very strong throughout). Highly recommended for people just starting (or even intermediate) in their purposeful learning journey. I suspect this is not an advanced book, but it’s definitely at the level of a Cal Newport style book on learning-tricks (perhaps slightly less in terms of the tricks).