Analysis Of Students' Mark Based On Data Warehouse And Data Mining

DM has been widely applied to commerce, banking, enterprise production and markets, while there has been comparatively less application in education. Schools of higher education have accumulated a wealth of teaching and administrating data which haven't been effectively made use of. In recent years, with the extension of enrollment in universities and colleges, the increasing number of students has brought great trouble in teaching and administrating. Therefore, traditional teaching and administrating methods can't be suitable for the social development. Nowadays quite a lot of university researchers have come to apply DM technology to teaching and administration. The use of data mining in large databases of student achievement data mining, data on student achievement in a large number of data extraction, conversion, analysis and other treatment model to the data found that the potential exists and rules, analysis of student achievement Forecast The development trend of teachers teaching specific aspects of the recommendations and views; on the management of schools to provide more useful knowledge, so that the management of the schools targeted to help schools adjust the strategy or decision-making.This Paper is based on good comprehension on data warehouse and data mining knowledge. Firstly, it introduces the basic theory of them. Secondly, it expounds the basic arithmetic of association rule mining and clustering analysis. Thirdly, it creates the data warehouse for the students'performance, including the structure designing, modeling and the extraction, transformation and loading for the data. Lastly, through deep research on the arithmetic of association rule mining and clustering analysis,the paper improved it and put them into the mining. In conclusion, based on deeply analysis and reasonable conclusion, plenty of valuable information is found. For example,what kind of knowledge point is proper for what type of questions, how knowledge points influence each other and the influence between different courses, and see the teaching effect of different teachers between different courses. All the analysis will have great effects on the performing and improving of teaching. Building Data Warehouse needs a lot of historical data accumulation, the model structure is a step-by-step process of continuous improvement. Faced with such a long-term and arduous work, based on the need for a large number of important preparatory work. Data Warehouse design of the structure of the whole system is of decisive significance to guide the first step is to carry out the standardization of data, data transmission, analytical tools and so on the premise of choice. Data Warehouse design and the traditional structure of the database design is different. This is because the data warehouse is a decision support system, it has a large amount of data, not updated very frequently, such as characteristics of the data warehouse must be carefully carried out to optimize the design, in order to meet the rapid increase in the amount of data and query performance is not falling Demand. In this article the construction of students'mark data warehouse was based by my school Jilin Teachers'Institute of Engineering and Technology. Through the data warehouse design of structure and model , building student mark data warehouse in order to carry out further analysis. The establishment of student mark data warehouse is to use student mark data warehouse for analysis of data for decision-making support for the teaching service.As soon as the student mark data warehouse has finished, it is necessary to analysis the data by the use of data mining. In this paper, the analysis to the data was primarily used of relation regulation and clustering method. In the fifth section of the paper in response to Jilin Teachers'Institute of Engineering and Technology student performance analysis of the application of the two options, in the process of analysis, but also for the different needs of different solutions to a large extent, depend on the content of the data And comprehensive data. Through the introduction of teacher-dimensional information, analysis of different titles in different courses for teachers in the teaching effectiveness of teachers who come in the course which results in better teaching. For example, through the analysis we can know that, No. 004 teachers in the data structure of the teaching process has been better teaching results, so that we can arrange more than 004 teachers, some of the data structure courses to enhance the effectiveness of teaching; the introduction of class, compared with the same subjects at different hours of the arrangement, students have good or bad situation, such as we increase class test in this database in the course of the proportion of students have some knowledge point better, so we have to develop after hours Arrangements, is focused on: the introduction of teachers and title-dimensional type of test could be in different professions, different test requirements for the types of titles assigned to the teachers to teach. For example, in a number of non-computer professionals to learn basic computer courses, teachers are not adequate resources, there is no need to allocate a professor teaching in this computer-based classes can be arranged lecturers to teach, this will help the rational use of resources, teachers, Is also conducive to the training of teachers and growth; Similarly, we on this basis, the introduction of time reflects the years at different times for each individual with the teachers to improve teaching standards and raise the title, the effect of strengthening the medium of instruction ; The introduction of teacher's age, which may reflect the age of the teachers have better teaching results, this time in our data mining process, concluded that between 35-45 in the classroom is more good results, which is also in line with The fact that logic, since the age of teachers has extensive teaching experience, as well as energy, should become the backbone of the teaching in schools through such an analysis, we have more teachers more rational arrangement of courses for teachers has reached resources Culture and rational utilization. To sum up, we have the data mining process includes the Chinese-dimensional information of students, teachers, Victoria, Victoria questions peacekeeping courses, knowledge-dimensional point, professional-dimensional peace-keeping type of test, we passed on a different dimension for extraction, mining and information integration And analyze a large amount of the benefit of the teaching guide association rules in order to illustrate how we have a reasonable distribution and use of these teaching resources, we improve the combat effectiveness of teaching and adaptability in order to optimize the ultimate goal of teaching and learning performance.Data Mining is a newly-established frontier subject. During the past decade or so, many new concepts and techniques on Data Mining have been presented and some of them have been discussed in higher levels for the recent years. Like the other new techniques, however, Data Mining must develop gradually from concept creation, accepted importance, wide discussion, and few usage attempts to large applications. Judging from the current situation, most scholars believe that the study of data mining is still in the stage of extensive research and exploration, it needs to be practiced in the basic theory and the application model. The research of Data Mining has reached significant achievement and has been applied successfully in many areas.The conclusion is a practical suggestion for the computer teaching administration. Some unexpected DM knowledge may enhance the quality of education and guide the teaching methods scientifically. With the further development of DM, more and more DM knowledge will be applied to teaching and it surely will bring us an unprecedented pleasant surprise.