A defense presents evidence for a thesis. What kind of evidence is appropriate depends on what kind of thesis is being defended. There are very different defenses for each of the kinds of claims given above. In AI, the more common defense is based on empirical results from running a program. A good defense here means more than one example, and answers to questions such as the following.
Analogous questions arise in the design of learning environments.
You should be able to argue that your environment can support learning in more than one specific arena, and what would be involved in implementing it elsewhere. You should be clear and specific about when it would not be a good approach. The same kind of defense applies here as in the previous case, but now serious comparisons with previous systems are required. X This is usually defended by a logical argument. It is usually very tough to do, even if the argument doesn't have to be formalized.