Abstract
Through analyzing the behavior data of MOOCs learners, a MOOCs learner's score prediction model is constructed based on clustering algorithm and neural network in this paper. By using this model, we can find out the neglected information and hidden learning rules in the MOOCs learning process. The model can provide personalized guidance for each user and improve learning efficiency. The model can provide personalized service to help learners form personalized learning strategies, and it also can alert learners with low grades and risk of dropping out.
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Zhang, Y., & Jiang, W. (2018). Score prediction model of MOOCs learners based on neural network. International Journal of Emerging Technologies in Learning, 13(10), 171–182. https://doi.org/10.3991/ijet.v13i10.9461
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