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International Conference on Web Information Systems Engineering

WISE 2015: Web Information Systems Engineering – WISE 2015 pp 323–337Cite as

WISEngineering: Achieving Scalability and Extensibility in Massive Online Learning

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9418))

Abstract

Massive Open Online Courses (MOOCs) have raised many unique challenges to online learning platforms. For example, the low teacher-student ratio in MOOCs often means lack of feedback to students and poor learning experiences. We present WISEngineering, a MOOCs platform that provides a rich set of features for overcoming these challenges. The system embraces social media for fostering student reflection. Its automated grading system adopts an open-architecture and uses stack generalization to blend multiple machine learning algorithms. A Zookeeper based computing cluster runs behind auto-grading and provides instant feedback. A behavior tracking system collects user behavior and can be later used for learning outcome analysis. We report the design and implementation details of WISEngineering, and present the design decisions that allow the system to achieve performance, scalability and extensibility in massive online learning.

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Acknowledgments

This work is partially supported by the National Science Foundation Grants DRL-1422436 and DRL-1253523. The instant grading service cluster is hosted by Hofstra Big Data Lab, funded by grant ESD CFA 29409.

Author information

Authors and Affiliations

  1. Hofstra University, Hempstead, NY, 11549, USA

    Xiang Fu, Tyler Befferman & M. D. Burghardt

  2. University of Virginia, Charlottesville, VA, 22904, USA

    Jennie Chiu

Authors
  1. Xiang Fu
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  2. Tyler Befferman
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  3. Jennie Chiu
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  4. M. D. Burghardt
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Corresponding author

Correspondence to Xiang Fu .

Editor information

Editors and Affiliations

  1. Tsinghua University, Bijing, China

    Jianyong Wang

  2. Poznan University of Economics, Poznan, Poland

    Wojciech Cellary

  3. Florida Atlantic University, Boca Raton, Florida, USA

    Dingding Wang

  4. Victoria University, Melbourne, Australia

    Hua Wang

  5. School of Computing & Information, Florida International University, Miami, Florida, USA

    Shu-Ching Chen

  6. Florida International University, Miami, Florida, USA

    Tao Li

  7. Victoria University, Melbourne, Victoria, Australia

    Yanchun Zhang

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© 2015 Springer International Publishing Switzerland

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Fu, X., Befferman, T., Chiu, J., Burghardt, M.D. (2015). WISEngineering: Achieving Scalability and Extensibility in Massive Online Learning. In: Wang, J., et al. Web Information Systems Engineering – WISE 2015. WISE 2015. Lecture Notes in Computer Science(), vol 9418. Springer, Cham. https://doi.org/10.1007/978-3-319-26190-4_22

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  • DOI: https://doi.org/10.1007/978-3-319-26190-4_22

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26189-8

  • Online ISBN: 978-3-319-26190-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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