【摘要】 首先提出MOOCs平台高注册率和高流失率成明显反差这一严重现象,进而提出改进MOOCs平台的一些建议,使得可以收集更多的有关学习者信息的数据,紧接着通过这些数据运用Clementine平台中的神经网络数据分析技术来研究MOOCs学习者的流失状况,建立起MOOCs学习者流失的基本模型。最后通过输入需要预测的学习者的基本数据进行神经网络流失预测,如果发现该学习者有流失的可能性,即可采取必要的措施来挽留学习者。更多还原

【Abstract】 In this paper, we first propose the serious phenomenon of the high registration rate and high loss rate of MOOCs platform, and then put forward some suggestions to improve the MOOCs platform, so that we can collect more information about the learner, and then use Clementine neural network data analysis technology to study the loss of learners on MOOCs platform, and establish the basic neural network model of MOOCs. Finally, input the basic data of the learners through the neural network to predict whether the learners will loss. If it is found that the learner has the possibility of loss, then it is necessary to take the necessary measures to retain the learners.更多还原