Visual analytics of video‐clickstream data and prediction of learners' performance using deep learning models in MOOCs' courses-Reference-Cited by-同舟云学术

Visual analytics of video‐clickstream data and prediction of learners' performance using deep learning models in MOOCs' courses

Published:2020-09-09 Issue:4 Volume:29 Page:710-732
ISSN:1061-3773
Container-title:Computer Applications in Engineering Education
language:en
Short-container-title:Comput Appl Eng Educ

Author:

Mubarak Ahmed A.¹²^ORCID,Cao Han¹^ORCID,Zhang Weizhen¹^ORCID,Zhang Wenli¹^ORCID

Affiliation:

1. School of Computer and Science Shaanxi Normal University Xian China

2. Faculty of Education, Department of Computer Science Ibb University Ibb Yemen

Publisher

Wiley

Subject

General Engineering,Education,General Computer Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cae.22328

Reference65 articles.

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3. Fast unfolding of communities in large networks

4. C. G.Brintonet al. Mining MOOC clickstreams: On the relationship between learner video‐watching behavior and performance CoRR. (2015) http://arxiv.org/abs/1503.06489

5. Q.Chenet al. Peakvizor: Visual analytics of peaks in videoclickstreams from massive open online courses IEEE. Trans. Vis. Comput. Graph.22(2015) no. 10 2315–2330.https://doi.org/10.1109/TVCG.2015.2505305

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