基于HMM模型的网络课程学习过程多维评价研究

Research on Multidimensional Evaluation of Learning Procedure in Network Course Based on HMM Model

网络课程学习过程评价形式单一的问题亟待解决。因此提出一种基于隐马尔可夫模型的多维评价方法,对学生学习事件进行持续跟踪和统计,运用隐马尔可夫模型识别隐含在学习事件序列中不同维度学习状态序列,将其作为网络课程学习过程多维度评价结果。实验表明,该评价方法准确率、精度和召回率分别平均达到0.64、0.75和0.80。基于HMM模型的网络课程学习过程多维评价结果可有效反映学生学习状态过程性变化。

Limited ways of evaluation is an issue that must be solved in learning procedure in network courses.A multidimensional evaluation method based on hidden markov model was proposed.The learning events of students were tracked and counted continuously followed by being analyzed via the hidden markov model to identify sequences of learning states in different dimensions,as the result of multidimensional evaluation of learning procedure in network courses.Experiments show that the proposed evaluation method achieves 0.64 accuracy,0.75 precision and 0.80 recall value in average.The result of HMM-based multidimensional evaluation of learning pro⁃cedure in network courses can effectively portray the procedural changes of students’learning states.