This paper proposes a method for reinforcing noun countability prediction, which plays a crucial role in demarcating correct determiners in machine translation and error detection. The proposed method reinforces countability prediction by introducing a novel heuristics called one countability per discourse. It claims that when a noun appears more than once in a discourse, all instances will share identical countability. The basic idea of the proposed method is that mispredictions can be corrected by efficiently using one countability per discourse heuristics. Experiments show that the proposed method successfully reinforces countability prediction and outperforms other methods used for comparison. In addition to its performance, it has two advantages over earlier methods: (i) it is applicable to any countability prediction method, and (ii) it requires no human intervention to reinforce countability prediction.

This paper is concerned with an ITS designed for augmenting a student's capability in problem solving. Discussions are concentrated on helping students acquire strategic knowledge and assisting them to build it in their heads. In this paper, many kinds of strategies are treated from a unified point of view. Based on this consideration, a teaching paradigm of strategic knowledge is presented. The paradigm is realized in an ITS as a training environment for strategic knowledge. Assisting students to learn strategic knowledge, the system sets up an appropriate environment and gives them some appropriate advice in each environment. It is realized as a function of giving them appropriate problems and hints about it. In general, strategic knowledge is a kind of heuristics so that it is not easy to describe their application conditions deterministically and explicitly. For this reason, an ITS for strategic knowledge is required to be designed so as to cover not only the case where expertise is represented explicitly as an executable model but also the case where it is represented only implicitly. To realize this teaching paradigm, situation-dependent knowledge called reminding pattern is prepared in the system. It is represented by a triple of a strategy, a situation, and a key symbol in the situation. It denotes that the key usually reminds students of the strategy in the situation. The system gives students problems including positive/negative examples of applications of each strategy in its problem solving process and hints which remind them of an appropriate strategy and makes them resume the problem solving when they fall into an impasse. In this paper, the structure of the system realizing this teaching paradigm is explained in the domain of proving propositional formulas.