Studying Academic Indicators within Virtual Learning Environment Using Educational Data Mining

Clicks: 31
ID: 282531
2016
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Popular

Ranked #704 of 803 articles by views in arXiv

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 803 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Our main goal is to discover the main factors influencing students' academic trajectory and students' academic evolution within such environment. Our results indicate strong correlation in this virtual learning environment between student average and some factors like: student's English level (despite the fact that Arabic language is the teaching language), student's age, student's gender, student's over-stay and student's place of residence (inside or outside Syria). Our results indicate also a need to modify the academic trajectory of students by changing the prerequisites of few courses delivered as a part of BIT diploma like Advanced DBA II, Data Security. In this research, the results also highlight the effect of the Syrian Crisis on students. Finally, we've suggested some future recommendations based on our observations and results to develop the current information system in SVU in order to help us to deduce some indicators more easily.
Reference Key
ajami2016studying Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Eid Aldikanji; Khalil Ajami
Journal arXiv
Year 2016
DOI
DOI not found
URL
http://arxiv.org/abs/1612.01090v1
Keywords
cs.cy cs.db h.2.8

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.