NDLI: The Best Learning Order Inference Based on Blue-Red Trees of Rule-Space Model for Social Network -- Case in ITE Course

Content Provider	IEEE Xplore Digital Library
Author	Yung-Hui Chen Deng, L.Y. Ku-Chen Huang
Copyright Year	2011
Abstract	Network Learning is becoming increasingly popular today. It is getting important to develop adaptive learning by social network that can be applied in intelligent e-learning systems, and provide learners with efficient learning paths and learning orders for learning objects. Therefore, we use the Rule-Space Model to infer reasonable learning effects of Blue-Red trees and their definitions through analyzing all learning objects of courses within system. We can also define all part learning of sub-binary trees from a course and derive all learning paths from each part learning of sub-binary tree based on the premise that we had inferred nine learning groups of social network grouping algorithms. Most importantly, we can define the Relation Weight of every learning object associated with the other learning objects, and separately calculate the Confidence Level values of between two adjacent learning objects from all learning paths. And finally, we can find the optimal learning orders among all learning paths from a sub-binary tree in the case of ITE course.
Starting Page	466
Ending Page	471
File Size	489349
Page Count	6
File Format	PDF
ISBN	9781457719080
DOI	10.1109/INCoS.2011.154
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-30
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Knowledge engineering Analytical models Learning Path Social network services Computational modeling Blue-Red tree Rule-Space Model Relation Weight Confidence Level Binary trees Educational institutions Local area networks
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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