Prediction of user temporal interactions with online course platforms using deep learning algorithms

Author:

Ren JunruORCID,Wu ShaominORCID

Funder

Economic and Social Research Council

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,Education

Reference38 articles.

1. Sequential rule mining on the student behavior data of an e-learning platform in the field of financial sciences: Case study;Aktaş,2021

2. Learning quantile functions for temporal point processes with recurrent neural splines;Ben Taieb,2022

3. Discovery and temporal analysis of latent study patterns in MOOC interaction sequences;Boroujeni,2018

4. The first steps towards professional distance: A sequential analysis of students' interactions with patients expressing emotional issues in medical interviews;Brodahl;Patient Education and Counseling,2022

5. An introduction to the theory of point processes. volume II: General theory and structure;Daley,2008

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Leveraging Topic Modeling to Investigate Learning Experience and Engagement of MOOC Completers;Methodologies and Intelligent Systems for Technology Enhanced Learning, 13th International Conference;2023

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