Open AccessUse of Data Mining Technologies in an English Online Test Results Management System
Author(s) -
Pan Chen,
Lei Yu
Publication year - 2021
Publication title -
international journal of emerging technologies in learning/international journal: emerging technologies in learning
Language(s) - English
Resource type - Journals
eISSN - 1868-8799
pISSN - 1863-0383
DOI - 10.3991/ijet.v16i09.22743
Subject(s) - computer science , login , trajectory , test (biology) , cluster analysis , data mining , process (computing) , test data , management system , sql server , machine learning , database , computer security , software engineering , engineering , paleontology , operations management , physics , astronomy , biology , operating system
The systematic management of English online test results can ensure the fairness of the test, guarantee the accuracy and safety of the test results, and reduce the consumption of manpower and materials. Unfortunately, the existing data mining and management strategy for learner scores cannot track the learning process or score change of learners. This paper innovatively applies the trajectory data mining technology to the design of an English online process test results management system. After analyzing the functional requirements of the system, four basic information lists were constructed in SQL Server 2005. Then, an improved k-means clustering algorithm and the trajectory frequent pattern mining algorithm were combined to cluster the test results and analyze the learning trajectory deviation of the learners. Next, the four system functions were detailed, including login, entry of test results, trajectory setting, and deviation analysis. The effectiveness of our algorithm, and the performance of our system were fully verified through experiments.