Study on Effect and Value of Result Analysis with Decision Tree Algorithm IN Colleges

Abstract

in efficient management teaching, students' results are important basis to evaluate teaching quality and teaching effect. Factors influencing students' results are complex and diversified. It is necessary to reasonably utilize data mining technology and adopt decision tree to analyze and predict students' results, correct bad behaviors influencing students' results in time in allusion to predication results and change teaching strategies. This paper studies application and value of decision tree algorithm in analyzing students' results in colleges. Teaching objective of higher education is to cultivate high-quality elites and inter-disciplinary talents and improve teaching quality. However, in teaching, students' results are an important indicator to evaluate students' knowledge mastery and also important basis to evaluate teaching quality. Reasonable analysis and prediction of students' results can provide important basis for enhancing teaching management, improving teaching environment, boosting teaching quality and deepening teaching reform. Data mining technology is the foundation and precondition of further deep-level data analysis in decision-making process. So, it is very significant to apply data mining technology in result analysis. It can comprehensively analyze the relationship between exam results and factors influencing results. When data mining technology is used to analyze students' results, relevant results can be gained in time and students, and bad be haviors can be corrected in time, too. I. Importance of analyzing students' results in colleges In current education, students' results are a basic standard to measure students' knowledge mastery and important basis of evaluating teaching quality. In actual teaching process, teachers will generally accumulate a large quantity of data, utilize relevant technology to rationally analyze and mine data, transform classification rules, and carry out quantitative analysis of data from many aspects so as to make sure the relationship between various factors and exam results can be displayed clearly. Analysis of students' results with certain technology, application of data mining technology in analysis of students' results and rational expression of the problems contribute to formulating corresponding strategies and measures by teachers and relevant departments and improving teaching quality and teaching effects. Main significance of data mining lies in rational analysis of huge data knowledge among massive data and mining unknown data with potential value and influence on decisions as powerful basis for relevant decisions. Decision tree algorithm is a relatively important algorithm in data mining. The tree-shaped structure is used to express results so as to better understand the data. Besides, in actual data mining process, data are regarded as the main research object. Through comparing traditional analysis methods and combining traditional technology, fuzzy mathematics and visualization technology, new mining technologies and methods form. The new mining technologies mainly include association rules algorithm, genetic algorithm, artificial neural network, decision tree algorithm, visualization technology and rough set theory etc. In teaching management process of colleges, students' results are important data which not just reflect teachers' teaching level to some extent, but also can evaluate students' learning situations. In teaching management, decision tree method can be used to analyze and comprehensively mine results of students from different majors. To specify relations among courses can greatly help teachers improve their teaching level. In actual teaching, more rational method should be chosen to better boost students' results and teaching level and provide guarantee for improving teaching quality.