Dynamic Assessment and Prediction in Online learning: Exploring the Methods of Collaborative Filtering in a Task Recommender System.

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Bibliographic Details
Title:	Dynamic Assessment and Prediction in Online learning: Exploring the Methods of Collaborative Filtering in a Task Recommender System.
Authors:	Leping Liu¹ liu@unr.edu, Ying Liang², Wenzhen Li¹
Source:	International Journal of Technology in Teaching & Learning. 2017, Vol. 13 Issue 2, p103-117. 15p.
Subject Terms:	Distance education, Internet in education, Student attitudes, Theory of knowledge, Recommender systems
Abstract:	Dynamic learning is a featured learning style in the second decade of the 21st century, emphasizing on the processes of individual or collaborative learning. Conducting dynamic assessment becomes critical to achieve the goals of learning. As learning becomes more individualized, online learning platforms have embedded a task recommender system to identify and predict individual needs, and to recommend different exercises or tasks for each learner so they can gain knowledge more efficiently. This article introduces the logistics of a task recommender system that can be used to perform dynamic assessment, and the methods of the learner-based collaborative filtering in a task recommender system, followed by an example that demonstrates the methods and procedures to assess the recommender effect. [ABSTRACT FROM AUTHOR]
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Database:	Education Research Complete

Description
Abstract:	Dynamic learning is a featured learning style in the second decade of the 21st century, emphasizing on the processes of individual or collaborative learning. Conducting dynamic assessment becomes critical to achieve the goals of learning. As learning becomes more individualized, online learning platforms have embedded a task recommender system to identify and predict individual needs, and to recommend different exercises or tasks for each learner so they can gain knowledge more efficiently. This article introduces the logistics of a task recommender system that can be used to perform dynamic assessment, and the methods of the learner-based collaborative filtering in a task recommender system, followed by an example that demonstrates the methods and procedures to assess the recommender effect. [ABSTRACT FROM AUTHOR]
ISSN:	19375204