E-learning System with estimation of understanding level by associative Cellular Neural Network

本研究建构一个自我导向的数位学习系统，能够自主地给予学习者适当的回馈。本文采用联想型细胞神经网络对模糊数据具有显著的分类功能。本研究利用客观资料（正确率、回答时间及难度）产生学习者资料以供评估。实验结果证明了该系统的实用性，并鼓励我们开发未来的教育系统。

This study constructs self-directed e-learning system which can autonomously give appropriate feedback to learners. We designed the system with associative Cellular Neural Network which has remarkable classification function of ambiguous data. This study generated learner's data for estimation by using objective data(accuracy, answer time and difficulty). Experimental results demonstrated usefulness of the system, and encouraged us to develop future education systems.