Study on Model of Auto-generating Test Paper Based on Spatial-temporal Clustering

doi:10.3969/j.issn.1006-2475.2017.05.017

Abstract

Abstract: To improve the quality of auto-generating test paper, a novel method is investigated on testing data from ACM Online Judge system, in which auto-clustering is done on questions by the features of temporal fluctuations and mean of time consumption firstly, then the difficulty coefficient is calculated through the submitting times and solved times of all types of questions, and eventually the model of auto-generating test paper is constructed by Gaussian stochastic process. Compared to the traditional model, the proposed model can scientifically evaluate testers’ knowledge level in the light of the difficulty and discrimination of questions. The experimental results suggest that the model is simple but effective and has strong adaptability.

Key words: spatial-temporal feature, clustering algorithm, difficult coefficient, auto-generating test paper

FAN Yu-ling, DONG Li-kai, WANG Qin, CAO Ai-zeng. Study on Model of Auto-generating Test Paper Based on Spatial-temporal Clustering[J]. Computer and Modernization, 2017, 0(5): 88-91.

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