Adaptive Online Training and Evaluation Systems
Practice is the key step in training softwareoperation skills. Unfortunately, teachers Grading of operational assignments is a laborious and tedious task, a problem also accompanied by numerous urge for the real time instruction from the students. Our solution to this problem is to automate the processes of assignment grading and knowledge-level evaluating such that students can receive tailored feedback instantly. This paper presents the architecture and mechanism of the adaptive training system, and generalizes a universal approach for grading operational assignments. In addition, for diagnosing uncertain knowledge level of students, Bayesian Networks and Computer Adaptive Tests (CAT) technologies were adopted. This system has been successfully employed in hundreds of universities and schools. The results obtained from the educational activities indicate its excellent performance in both efficiency and accuracy.
Adaptive training evaluation Operational skills Bayesian Networks CAT
ZHANG Liang ZHUANG Yueting YUAN Zhenming ZHAN Guohua
School of Computer Science and Technology Zhejiang University Hangzhou, China;School of Information School of Computer Science and Technology Zhejiang University Hangzhou, China School of Information Engineering Hangzhou Normal College Hangzhou, China
国际会议
厦门
英文
463-467
2006-07-27（万方平台首次上网日期，不代表论文的发表时间）