Please use this identifier to cite or link to this item: https://elib.vku.udn.vn/handle/123456789/2312
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dc.contributor.authorPham, Vu Thu Nguyet-
dc.contributor.authorNguyen, Quang Chung-
dc.contributor.authorNguyen, Van To Thanh-
dc.contributor.authorHo, Thanh Phong-
dc.contributor.authorNguyen, Quang Vu-
dc.date.accessioned2022-08-17T01:51:22Z-
dc.date.available2022-08-17T01:51:22Z-
dc.date.issued2022-07-
dc.identifier.issn978-604-84-6711-1-
dc.identifier.urihttp://elib.vku.udn.vn/handle/123456789/2312-
dc.descriptionThe 11th Conference on Information Technology and its Applications; Topic: Data Science and AI; pp.51-60.vi_VN
dc.description.abstractAs students proceed through their university degrees, they are confronted with a plethora of course options. It is critical that they get assistance based not only on their interests, but also on the "predicted" course achievement, in order to improve their learning experience and academic success. In this study, we suggest the next-term grade prediction task as a suitable course selection guide. We offer a machine learning framework for predicting course success in a certain term based on prior student-course data. In this framework, we create a prediction model utilizing Long Short Term Memory (LSTM) that takes into account both student and course qualities as well as previous student course grade data.vi_VN
dc.language.isoenvi_VN
dc.publisherDa Nang Publishing Housevi_VN
dc.subjectSuccess Predictionvi_VN
dc.subjectRNNvi_VN
dc.subjectLSTMvi_VN
dc.subjectDeepLearningvi_VN
dc.titleNext-Term Academic Success Prediction Using Deep Learningvi_VN
dc.typeWorking Papervi_VN
Appears in Collections:CITA 2022

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