摘要
智能训导系统(ITS)以提高学习者学习自主性,实现个性化的学习过程为目标.学习者的学习偏好根据学习者本身的属性,如学习目的,认知能力等变化.因此,为所有学生设计统一的学习路线已不能很好满足单个学习者的学习需要.首先将学习者进行特征聚类,然后将每个学习者作为一个粒子,将其在学习过程中的路径选择和评价值作为其空间代表值,使用粒子群算法进行个性化学习路径寻优,并通过实验证明其有效性.
Intelligent Tutor System （ITS） aims at improving the learner autonomy, and implementing personalized learning process. Learner＇s preference changes with their learning target, cognitive ability and so on. We introduced a method which first organized the leaner through common character, then viewed the learner as a particle in a swarm, using their learn path selection and evaluation as a representative value of its space, used particle swarm optimization （PSO）to make personalized learning path optimization. At the end, we proved the effectiveness of the method through experiment.
出处
《河南科学》
2013年第12期2190-2193,共4页
Henan Science
基金
河南省基础与前沿技术研究计划项目资助(132300410011)
关键词
粒子群
学习路径
智能推荐
在线学习
particle swarm optimization
learning path
intelligent recommendation
online learning
