.png){kind=icon}
Return
Automatic and interactive e-Learning auxiliary material generation utilizing particle swarm optimization
.png){kind=icon}
PRE
AI
DOI：10.1016/j.eswa.2007.09.039.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The purpose of this research was to utilize a PSO-based algorithm, serial blog article composition particle swarm optimization (SBACPSO) algorithm, to automatically and intelligently generate auxiliary materials. Contrary to previous fixed content auxiliary materials, the proposed auxiliary materials, which consist of blogs posted by learners, provide more interactive and cooperative characteristics for the learning process. With a few blog features such as comments, trackbacks, difficulty levels, and association degree related to a specific topic, the best combination of blog articles is produced as an auxiliary material. The generated auxiliary materials from a real course are presented in a system demonstration. The experimental results and satisfaction analysis also indicate that the proposed algorithm can achieve the expected convergence, with participants being satisfied with interaction, assistance, usability, and flexibility. (C) 2007 Elsevier Ltd. All rights reserved.
Keywords:
serial blog articles composition particle swarm optimization
auxiliary material
e-Learning
RSS
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.5
Papers:
3.0W
Citations:
10.2W
Organization
Cited Papers
.png){kind=icon}
ShareSaveShareSaveShareSave
ShareSaveShareSaveShareSave
View more