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Review of Recommender Systems for Learners in Mobile Social/Collaborative Learning

ISSN 2223-4985
Journal from gdlhub / 2017-08-14 11:52:32
Oleh : Nana Yaw Asabere , International Journal of Information and Communication Technology Research
Dibuat : 2012-06-23, dengan 1 file

Keyword : Mobile Learning, Collaborative Learning, Social Learning, Recommender Systems
Subjek : Review of Recommender Systems for Learners in Mobile Social/Collaborative Learning
Url : http://esjournals.org/journaloftechnology/archive/vol2no5/vol2no5_2.pdf
Sumber pengambilan dokumen : Internet

Social/collaborative learning is a learning procedure that is student-centred and involves a task-based and activity-based approach


that collaboratively provides several advantages such as: communication, interpersonal and social co-operation, sharing, caring,


openness, creativity, management, practicality, responsibility, involvement and participation. Social and collaborative learning


improves pedagogy and are very important aspects of education. Inclusion of social and collaborative learning needs to be


considered as a priority in all educational modes. Mobile learning, a new flexible learning landscape is currently being adopted


worldwide in both academia and industry. The inclusion of social/collaborative learning in mobile learning is of utmost and vital


importance due to its benefits and contributing factors to education/learning efficiency and sustainability. The inclusion of social


/collaborative leaning in mobile learning requires the effective management of social activities/data used in learning. Mobile social


activities/data involving: non-textual/multimedia (voice/audio and video) and textual that are used by learners and teachers in mobile


learning can be extremely large and disorganised with some of the data being educationally irrelevant to the mobile learning process.


How educationally relevant mobile social activities/data are realized, structured and managed as well as the filtering of relevant


social learning activities/data in mobile learning for learners is a critical issue and needs to be tackled. This paper surveys relevant


literature, and proposes recommender systems that can be implemented in mobile social/collaborative learning to solve problems


involving the recommendation of relevant social data and learning materials for learners.

Deskripsi Alternatif :

Social/collaborative learning is a learning procedure that is student-centred and involves a task-based and activity-based approach


that collaboratively provides several advantages such as: communication, interpersonal and social co-operation, sharing, caring,


openness, creativity, management, practicality, responsibility, involvement and participation. Social and collaborative learning


improves pedagogy and are very important aspects of education. Inclusion of social and collaborative learning needs to be


considered as a priority in all educational modes. Mobile learning, a new flexible learning landscape is currently being adopted


worldwide in both academia and industry. The inclusion of social/collaborative learning in mobile learning is of utmost and vital


importance due to its benefits and contributing factors to education/learning efficiency and sustainability. The inclusion of social


/collaborative leaning in mobile learning requires the effective management of social activities/data used in learning. Mobile social


activities/data involving: non-textual/multimedia (voice/audio and video) and textual that are used by learners and teachers in mobile


learning can be extremely large and disorganised with some of the data being educationally irrelevant to the mobile learning process.


How educationally relevant mobile social activities/data are realized, structured and managed as well as the filtering of relevant


social learning activities/data in mobile learning for learners is a critical issue and needs to be tackled. This paper surveys relevant


literature, and proposes recommender systems that can be implemented in mobile social/collaborative learning to solve problems


involving the recommendation of relevant social data and learning materials for learners.

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