自适应学习系统中“KCP学习者模型”研究

Research on “KCP Learner Model” in Adaptive Learning System

为解决自适应学习系统推送学习资源的准确性、丰富性以及动态可定制性等问题,提出了一种"KCP学习者模型",并将该学习者模型应用于自适应学习系统之中,以提高自适应学习系统的学习效果。首先,设计"KCP学习者模型",主要包括学习者的知识水平、认知能力以及学习偏好信息;其次,将抽象化的"KCP学习者模型"进行量化表示,用特征值反映学习者的学习特性,便于自适应学习系统更好地识别学习者的学习特性,使自适应学习系统推送学习有据可依,提高自适应学习效率;最后,从用户满意度和学习者测试成绩优秀率两个维度,对比分析了应用"KCP学习者模型"的自适应学习系统与传统自适应学习系统,验证了前者具有提升学习的效果。

In order to solve the problem of accuracy, abundance and dynamic customization of push learning resources in adaptive learning system, we propose a ＂KCP learner model＂ and applies it to an adaptive learning system to improve the learning effect of the adaptive learning system. First of all, the ＂KCP learner model＂ is designed, which mainly includes learners＇ knowledge level, cognitive ability and learning preference information. Secondly, the abstract ＂KCP learner model＂ is quantified, and the eigenvalues is used to reflect the learner＇ s learning characteristics,which is convenient for the adaptive learning system to better recognize the learners＇ learning characteristics and make the adaptive learning system push improve the efficiency of adaptive learning. Finally, the adaptive learning system using the ＂KCP learner model＂ and the traditional adaptive learning systemare are compared and analyzed in two dimensions of customer satisfac- tion and learner test seores,and it is proved that the adaptive learning system with ＂KCP learner model＂ has the effect of improving learning.