Intelligent information-sharing systems
Communications of the ACM
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
User Modeling and User-Adapted Interaction
Building a Recommender Agent for e-Learning Systems
ICCE '02 Proceedings of the International Conference on Computers in Education
NCM '09 Proceedings of the 2009 Fifth International Joint Conference on INC, IMS and IDC
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Collaborative Filtering for teaching in a learning 3.0 environment is an approach in which teachers or learners who share the same interest could start collaboration easily as they have the same background. Through collaborative filtering, the system highly recommends other teachers or learners who have performed the same tasks in a large number of times to become good collaborator. For instance, this collaborative filtering is a significant tool when a learner searches for peer help to solve a problem. The system identifies the process by matching the learner's actions and the other learners. Thus, opens up more opportunities for educators to practise diverse teaching styles that integrate wide dimension of technologies elements to suit the learners' needs. In this paper, results from a preliminary study provide useful information to portray the early perception and readiness of the teachers towards Collaborative Filtering (CF) for teaching in a 3.0 learning environment. Finally, it enables teachers to better understand new technology and use it collaboratively to integrate technology into Malaysian education for learners' benefit as well.