Real-time and open online course resources of MOOCs have attracted a large
number of learners in recent years. However, many new questions were emerging
about the high dropout rate of learners...
For MOOCs platform, predicting the
learning status of MOOCs learners in real time with high accuracy is the
crucial task, and it also help improve the quality of MOOCs teaching. The
prediction task in this paper is inherently a time series prediction problem,
and can be treated as time series classification problem, hence this paper
proposed a prediction model based on RNNLSTMs and optimization techniques which
can be used to predict learners' learning status. Using datasets provided by
Chinese University MOOCs as the inputs of model, the average accuracy of
model's outputs was about 90%.