Enhancing knowledge integration from multiple experts to guiding personalized learning paths for testing and diagnostic systems

Computers and Education: Artificial Intelligence

卷:2

Sasithorn Chookaew¹  Dechawut Wanichsan²  Patcharin Panjaburee³ 

[1] Corresponding author.;

[2] Faculty of Education, Rambhai Barni Rajabhat University, 41 moo 5, Raksakchamoon Road, Thachang, Muang, Chanthaburi, 22000, Thailand;

[3] Institute for Innovative Learning, Mahidol University, 999, Phuttamonthon 4 Road, Salaya, Nakorn Pathom, 73170, Thailand;

关键词: Computer-based testing;    Computer-assisted learning;    Testing and diagnostic learning problem system;    Multi-expert system;   

DOI  :  

来源: DOAJ

【 摘 要 】

The testing and diagnostic systems have been considered to be useful for students because they can point to their learning problems to provide helpful suggestions for improving the knowledge. The previous approach shows that using the knowledge from multiple experts can develop a testing and diagnostic system that provides more accurate suggestions for learners comparing to the system using a single expert. Nevertheless, the low-quality knowledge integration method of the multi-expert approach can provide some inaccurate learning suggestions. This work proposes a practical method for enhancing knowledge integration from multiple experts to provide more effective learning suggestions. An experiment has been conducted on freshmen in university to evaluate the effectiveness of the proposed method. The results show that the proposed approach not only improves the learning achievements of the students but also decreases the number of reconsidering cases.

【 授权许可】

Unknown