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E-learning using big data and cloud computing

E-learning using big data and cloud computing

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E-learning is a learning system in which educational content and technologies are combined to facilitate the learner. The unprecedented increase in the number of students and educational contents and services provided makes the e-learning method grow at an exponential rate. Many challenges such as optimized resource utilization, storage necessities along with management of dynamic parallel requests concurrently necessitate the use of a platform that demands cost control to be satisfied by the environment of cloud computing. Cloud-based e-learning architecture provides an enriched learning experience, including interactive features to challenge the user's depth of understanding and level of preservation. Big data, in the context of e-learning, is the data that are gathered from learners during the learning process from many platforms such as the progress of the learners, evaluation results, discussion forums, messages, feedback, collaborations with the learner communities, teaching interactions and any other data generated related to the learning process. The data collected by these mediums are still large and difficult to manage. Hence big data in e-learning helps in a better analysis and management of these data. Using big data technologies, the enormous amount of data generated by e-learning can be processed, analyzed, organized, filtered, which can be visualized efficiently in less time. The useful information can be extracted from a large volume of data that help one to take better, smarter, and fast decisions. Hence, it is better to make use of big data for a better quality of e-learning systems. This chapter provides insight into the drawbacks of the conventional e-learning model, e-learning using the technology of cloud computing and big data. It also shows how big data and cloud computing are integrated to provide e-learning support. Moreover, it uncovers some of the case studies in e-learning industries and concludes with challenges.

Chapter Contents:

  • 8.1 Introduction
  • 8.2 Conventional e-learning system and its issues
  • 8.3 E-learning on cloud computing
  • 8.4 Characteristics of cloud in e-learning
  • 8.5 Cloud-based e-learning architecture
  • 8.6 Cloud computing service-oriented architecture for e-learning
  • 8.7 Big data in e-learning
  • 8.7.1 The need for big data in e-learning
  • 8.8 Review on big data-based e-learning systems
  • 8.9 Association of big data and cloud computing
  • 8.9.1 Infrastructure as a service (IaaS) in the public cloud
  • 8.9.2 Platform as a service (PaaS) private cloud
  • 8.9.3 Software as a service (SaaS) in a hybrid cloud
  • 8.10 Use of big data and cloud technology for e-learning
  • 8.11 Casestudies on e-learning
  • 8.12 Case study of a cloud and big data-based Evaluation and Feedback Management System (EFMS) in e-learning
  • 8.13 Open research challenges
  • 8.13.1 Limited control over security and privacy
  • 8.13.2 Limited control over compliance
  • 8.13.3 Limited control over institutional data
  • 8.13.4 Network dependency issues
  • 8.13.5 Latency problem
  • 8.14 Conclusion
  • 8.15 Future work
  • References

Inspec keywords: cloud computing; Internet; computer aided instruction; learning (artificial intelligence); Big Data; teaching

Other keywords: big data technologies; educational content; cloud computing; e-learning systems; cloud-based e-learning; learning process; enriched learning experience; e-learning method; learning system; e-learning support; conventional e-learning model

Subjects: Information networks; Computer-aided instruction; Internet software

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