Vivek Haldar writes: "One of the most deeply held beliefs in the culture of unix is that the steep learning curve pays off. Yes, the tools seem cryptic and “hard-to-use” ...  [but] if you stick with it and keep learning you will be rewarded. When you grok the power of economical command lines, composability and extensibility, you’re glad you didn’t run back to the arms of the GUI on the first day.   There is another belief that goes deeper: the learning curve has value, it is essential for learning, and it needs to be preserved, not whittled away in the name of 'ease-of-use.' "  Haldar goes on to reference research which supports exactly this point of view.

What are the common mistakes people make in trying to read mathematics?  How can these mistakes be corrected?

Jason Gorman presents how developers can learn TDD to the point of transforming the knowledge acquired into habits by exercising a number of practices over a period of 4-6 months followed by evaluation done by fellow co-workers.

"All teachers of programming find that their results display a 'double hump'. It is as if there are two populations: those who can, and those who cannot, each with its own independent bell curve. [...] We have a test which picks out the population that can program, before the course begins."

"Everyone should know how to use a computer, but not everyone needs to be a programmer. But it's still a little disturbing that the act of programming seems literally unteachable to a sizable subset of incoming computer science students." Jeff Atwood discusses a research paper which identifies some very simple tests which identify those who are likely to be able to learn to program effectively.

Dave Thomas (of the Productive Programmers) talks about the stages between novice and expert, and points out that a person at one stage has needs very different forms of guidance and management than someone at a different stage.

A guided set of puzzles most of which need some python programming to solve.

"Project Euler is a series of challenging mathematical/computer programming problems that will require more than just mathematical insights to solve. Although mathematics will help you arrive at elegant and efficient methods, the use of a computer and programming skills will be required to solve most problems. The motivation for starting Project Euler, and its continuation, is to provide a platform for the inquiring mind to delve into unfamiliar areas and learn new concepts in a fun and recreational context. The intended audience include students for whom the basic curriculum is not feeding their hunger to learn, adults whose background was not primarily mathematics but had an interest in things mathematical, and professionals who want to keep their problem solving and mathematics on the edge."

This web site gives an excellent overview of the origin of life from the earliest pre-RNA world through the construction of the first proto-cells.

A collection of several small Python programs aimed at intermediate programmers.

The home page for MIT's OpenCourseWare, which provides open access to all course materials used at MIT including lecture nodes, videos, labs, etc.

"Technology is beginning to assail the underlying concepts of our educational system. ... [P]aying dues and embracing proxies for quality may give way having the ability to know what kids really know."

Twelve guidelines for giving a good academic lectures. Most of them, I think, are applicable to any form of technical speaking.