Research is described on a system for web-assisted education and how it is used to deliver on-line drill questions, automatically suited to individual students. The system can store and display all of the various pieces of information used in a class-room (slides, examples, handouts, drill items) and give individualized drills to participating students. The system is built on the basic theme that it is for learning rather than evaluation. Experimental results shown here imply that both the item database and the item allocation methods are important and examples are given on how these need to be tuned for each course. Different item allocation methods are discussed and a method is proposed for comparing several such schemes. It is shown that students improve their knowledge while using the system. Classical statistical models which do not include learning, but are designed for mere evaluation, are therefore not applicable. A corollary of the openness and emphasis on learning is that the student is permitted to continue requesting drill items until the system reports a grade which is satisfactory to the student. An obvious resulting challenge is how such a grade should be computed so as to reflect actual knowledge at the time of computation, entice the student to continue and simultaneously be a clear indication for the student. To name a few methods, a grade can in principle be computed based on all available answers on a topic, on the last few answers or on answers up to a given number of attempts, but all of these have obvious problems.