An intelligent tutoring platform for educational assessment
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Abstract
K-12 education is an important part of educational psychology. Recently, online-learning has been widely accepted because of its significant effect on K-12 education. However, mostly based on the educational database, though existing online-learning systems and intelligent tutoring systems can provide useful resources for teachers and students, they seldom utilize offline test data to offer personalized services. To the end, an intelligent tutoring platform for educational assessment(ITPEA) was proposed and implemented. The platform combines both offline examinations and online resources to offer analysis from the perspectives of test papers, students and teachers. Specifically, based on the data from offline examinations, educational theories were first employed to evaluate the quality of the questions. Then, diagnostic models were constructed on the key knowledge points that students should master to meet one’s personalized demands. Finally, new analytical methods for evaluating teacher’s influence on class abilities were proposed with data mining technologies to help find "unusual" students in class. The core technology of ITPEA is currently operating on an online-learning system, and obtains good results.
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