The Study On Grade Categorization Model Of Question Based On On-Line Test Data

To tackle with the blindness of random questions choosing for exercise and test of the on-line learning system, this paper clusters questions exploiting various feature subsets and parameters via K-means. For the test data of ACM Online Judge system, the features of temporal fluctuations mean of time consumption and repeat submission rate are used to make the question categorization and automatic recommendation come true. The experimental results suggest that the proposed method is simple but effective, and by which an on-line test platform can realize functions such as individuation teaching, intelligently questions choosing, teaching instruction, automatically paper constructing and paper difficult prediction.