International Journal of Computer Applications · 2018 · 30 citations · 3 references
ComputingComputer ScienceEducational TechnologyEducational Data MiningMachine LearningTime Series AnalysisDeep LearningStudent Risk IdentificationTime Series ClassificationTime Series ForecastingTime Series ModelingTime Series PredictionLearner Performance PredictionNeural ForecastingNeural Network ModelingNeural Time Series ForecastingPredictive Achievement ModelingPredictive Modeling In EducationRecurrent Neural Network ForecastingRecurrent Neural Networks
Educational Data Mining able to gain a handsome amount of attention of the researcher of educational technology in recent times. In this paper, Recurrent Neural Network (RNN) is used to predict a student's final result. RNN is a variant of neural network that can handle time series data. The final term class is predicted using the first and second term class along with fifteen others features of a student. This analysis help the teacher to identify the students, who are 'at risk' and based on that he can offer proper remedy to them. In this paper, a comparison based study is also made with Artificial Neural Network and Deep Neural Network with the proposed Recurrent Neural Network.
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