Usability of a cloud-based collaborative learning framework to improve learners' experience. (October 2015)

• Record Type: Journal Article
• Authors: Shorfuzzaman, Mohammad; Alelaiwi, Abulhameed; Masud, Mehedi; Hassan, Mohammad Mehedi; Hossain, M. Shamim
• Is Part Of: Computers in human behavior. Volume 51:Part B(2015)
• Page Start: 967
• Page End: 976
• Publication Date: 2015-10
• Subjects: Collaborative learning -- Cloud computing -- Dynamic programming -- Replication -- Learners' experience -- Data access time; Interactive computer systems -- Periodicals; Man-machine systems -- Periodicals; 004.019
• DOI: 10.1016/j.chb.2014.10.002
• Languages: English
• ISSNs: 0747-5632

Abstract

Highlights: Usability of a cloud based framework is presented for collaborative learning. Focus on the importance of data replication in the design of such a framework. A distributed replication technique to improve learners' data access performance. The replication problem is formulated using dynamic programming. Experimental studies show the efficacy of the proposed framework. Abstract: Computer-Supported Collaborative Learning (CSCL) is concerned with how Information and Communication Technology (ICT) might facilitate learning in groups which can be co-located or distributed over a network of computers such as Internet. CSCL supports effective learning by means of communication of ideas and information among learners, collaborative access of essential documents, and feedback from instructors and peers on learning activities. As the cloud technologies are increasingly becoming popular and collaborative learning is evolving, new directions for development of collaborative learning tools deployed on cloud are proposed. Development of such learning tools requires access to substantial data stored in the cloud. Ensuring efficient access to such data is hindered by the high latencies of wide-area networks underlying the cloud infrastructures. To improve learners' experience by accelerating data access, important files can be replicated so a group of learners can access data from nearby locations. Since a cloud environment is highly dynamic, resource availability, network latency, and learner requests may change. In this paper, we present the advantages of collaborative learning and focus on the importance of data replication in the design of such a dynamic cloud-based system that a collaborative learning portal uses. To this end, we introduce a highly distributed replication technique that determines optimal data locations to improve access performance by minimizing replication overhead (access and update). The problem is formulated using dynamic programming. Experimental results demonstrate the usefulness of the proposed collaborative learning system used by institutions in geographically distributed locations.