WISEngineering: Achieving Scalability and Extensibility in Massive Online Learning.

Xiang Fu,Tyler Befferman, Jennie Chiu, M. D. Burghardt

WISE(2015)

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摘要
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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关键词
Online learning platform, Automated grading, Web application, Scalability, Extensibility
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