Intelligent Problem Solvers in Education: Design Method and Applications

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In this chapter we present the method for designing intelligent problem solvers (IPS), especially those in education. An IPS, which is an intelligent system, can consist of AIcomponents such as theorem provers, inference engines, search engines, learning programs, classification tools, statistical tools, question-answering systems, machinetranslation systems, knowledge acquisition tools, etc (Sowa, John F. 2002). An IPS in education (IPSE) considered here must have suitable knowledge base used by the inference engine to solve problems in certain knowledge domain, and the system not only give human readable solutions but also present solutions as the way teachers and students usually write them. Knowledge representation methods used to design the knowledge base should be convenient for studying of users and for using by inference engine. Besides, problems need to be modeled so that we can design algorithms for solving problems automatically and propose a simple language for specifying them. The system can solve problems in general forms. Users only declare hypothesis and goal of problems base on a simple language but strong enough for specifying problems. The hypothesis can consist of objects, relations between objects or between attributes. It can also contain formulas, determination properties of some attributes or their values. The goal can be to compute an attribute, to determine an object, a relation or a formula. After specifying a problem, users can request the program to solve it automatically or to give instructions that help them to solve it themselves. The second function of the system is Search for Knowledge. This function helps users to find out necessary knowledge quickly. They can search for concepts, definitions, properties, related theorems or formulas, and problem patterns. By the cross-reference systems of menus, users can easily get knowledge they need.