基于认知诊断的自适应学习材料智能推送算法研究
The Material Recommendation System for Adaptive Learning Based on Cognitive Diagnosis

将认知诊断和自适应学习相结合,利用认知诊断方法先诊断学习者对知识的掌握情况,然后依据遗传算法和多岛遗传算法为每个学习者智能化提供合适的学习材料,提出了基于认知诊断框架下的自适应学习材料智能推送算法.通过Monte Carlo模拟实验考察了新算法的科学性及其效果,研究结果表明:(i)基于认知诊断框架下的自适应学习材料智能推送算法具有较理想的效果;(ii)遗传算法和多岛遗传算法选取的学习材料具有低惩罚函数值和高学习材料匹配的正确率;(iii)遗传算法和多岛遗传算法选取的材料比随机算法更加适合学习者.
Cognitive diagnosis and adaptive learning are combined,cognitive diagnosis method is used to diagnose learners' knowledge mastery,and then genetic algorithm or multi-island genetic algorithm is used to provide appropriate learning materials for each learner.The material recommendation system for adaptive learning based on cognitive diagnosis is built.In this paper,the Monte Carlo simulation experiment is used to investigate the effect of adaptive algorithm based on cognitive diagnosis.The research results show that the adaptive material recommendation algorithm based on cognitive diagnosis has an ideal effect.Learning materials selected by genetic algorithm and multi-island genetic algorithm have low penalty function value and high success rate.The selected materials based on genetic algorithm and multi-island genetic algorithm are more suitable for learners than the random algorithm