A Study on Learning Analytics with Recommended System
Main Article Content
Abstract
Education data mining is becoming popularfrom the education data we can derives the insights using data mining techniques. Insights which are used for students, faculty, and education organizations and one of the famous applications in data mining is recommender system. In the field of learning analytics recommender system have become common in recent years. In education sector student performance can increase by using different tools, which are used in recommender system application implementation. The style and expectations of the user should be correctly constructed to include the most appropriate suggestions. Researchers have proposed various types of recommender systems in learning analytics (RSL).The authors of this paper reviewed several current state of recommendation system models and presented their selection criteria in learning analytics. Authors investigated various significant preference factors and classified them based on their similarity in the RS (Recommender System).This article presents the future directions of RSL (Recommender Method in Learning Analytics) models and compiles a detailed.
Downloads
Metrics
Article Details
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.