"""<p>The advantage of massive input is that you don't need to force yourself to stop to ask all these questions (ie forcing yourself to slow down) or to slow down to write notes. In my own experience learning biology, the reason why this worked for me is that when starting in a new field, there are a lot of things that are unclear to the novice if they are important, even things in textbook. Maybe nothing else you'll ever see again will leverage that concept. That's highly likely in bio. When you know that most of what you are reading may not be important, forcing yourself to take notes and make SRS prompts makes the learning process slower and not rewarding at all. The massive input approach gives you permission to skim, jump ahead, and go on tangents.<p>But in contrast, I would never do this with any formal subject (math, physics, learning a new programming language, computer science in general). There I think Andy's approach is the right one and the one I've tried to follow in the past.<p>The why seems clear: Formal domains tend to rely a lot on deep towers of abstraction, mastering one level makes a lot of sense to get to the next one because the next one is the previous one, wrapped in new symbols. The number of concepts encountered is small, but they way they can interact is very rich, and one has to be able to work through these interactions as part of producing output in the domain in question. Whereas other domains like biology have less abstraction. The underlying nature of the domain is extremely complex, the nature of the interactions of the components in biological systems are not well defined by the sort of formal rules one can neatly encapsulate in abstractions, it all leaks to some extent; so in practice in biology one is not so much proving things but gesturing in various directions and then pinning down the gesturing with concrete experiments.<p>"""