Investigation of scaffolding learning by the development of a server-client-based intelligent learning system.

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We developed an intelligent tutoring system that teaches undergraduate students Natural Deduction. The system gives students, as scaffolding, recommended inference rules for the next inference step, and inferred results drawn by the applications of the rules. Through experimental investigation, we confirmed that as the levels of support increased, the problem solving performance was raised; but the learning gains reached the maximum at a certain support level, and then decreased with the further extreme learning supports.