This research aims to explore whether analyzing learning effectiveness of Chinese writing with grey statistical clustering analysis can offer more detailed information for improvement than with average score disparity analysis. The paper uses grey whitening weight function to classify the students’ original grades into high, middle and low level to calculate these statistical indicators for their corresponding value and sum of given whitening weight function. Next, after calculating the weighting vector of each statistical indicator corresponding to the given grey whitening weight function, the maximum weighting vector were selected to be the statistical grey value of the subjects. The result shows that college of humanities and social sciences is among the highest in the high level category for the increasing degree of students’ scores, and college of management ranks second. As for the decreasing degree in the low level category, college of science and engineering ranks first and follows also by college of management. Besides, the post-teaching scores are obviously higher than the pre-teaching scores in every college, and the grades are also moving from low level toward middle and then to high level. If summating the increasing degree of high and middle level, the one that significantly improved is the college of science and engineering, and the college of management plays second fiddle.