Validity Analysis Based on Multidimensional Pattern Analysis and Machine Learning Theory in Educational Teaching Assessment

Abstract

Prediction and evaluation methods have important and extensive applications in college education and teaching. These methods are usually realized by intelligent learning machine based on training method. In this case, a very important question is worth analyzing: are all these methods effective? Therefore, this paper converts the original score into standard score through normal distribution, explains the application of standard score, provides a practical standard score processing method for examination subjects with a full score of 150, and establishes a basic model for comparing the overall score or the overall average score by using standard score when combining the scores of different subjects (including examination), so as to determine the individual score in a group, or deeply analyze the basic model and weighting model to determine the relative position of individual scores in a group or population, and evaluate the effectiveness of various methods. Finally, make a general assertion on the effectiveness of prediction and evaluation using intelligent learning machine. In fact, there are many factors that affect the effectiveness of education and teaching and human ability. There are differences between the data of education and teaching effectiveness and human ability. The distribution of these data is generally more in the middle, less in too large and too small.