Research And Development Of Undergraduate Teaching Evaluation Information System In College And Universities

The higher school teaching assessment work plays an important role in improvingschool teaching conditions, accelerating the teaching infrastructure and promoting fasterdevelopment of school. It will greatly improve the efficiency of the assessment bybuilding an efficient platform for online teaching evaluation and integrating the teachingassessment resourcesThis paper is based on the serious and careful research of Qingdao TechnologicalUniversity teaching assessment work. According to the requirements of teachingevaluation system and the theory of information engineering, this paper focus on thesystem data model, safety mechanism and overall framework, then design theUndergraduate Teaching Evaluation Information System. The system adopts B/S as themain system structure which applies ASP programming at application and part of thefunctions use COM components, and background database adopts SQL Server2000as adata server. The distributed style Web site is used for collecting the basis data ofteaching evaluation, and the database is used for storing raw data. The system can dealwith the data collection and processing, information processing, storage andtransmission, which can ensure evaluators use the campus network to access theschool’s teaching evaluation resources, and then deal with different data completely. Wehave considered fully the system development in the future, so the system has goodmaintainability and expansibility. In this paper, we pay attention to the following twoaspects:1. The thesis have improved model RBAC. According to the users’ needs, expandtwo main object model of the original RBAC, and make it more suitable for structuralfeatures of the system users. It also improves the management efficiency of the systemadministrator.2. The data mining function is introduced into teaching evaluation decisionsubsystem. Data mining is applied widely in the areas of bank, telecommunication andtransportation because of its strong discovery ability. This paper use classical association rules--Apriori algorithm to optimize its efficiency. And the paper appliesalgorithm to the decision support subsystem, which achieve the mining functions of thepart of the raw data.