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A Web-Based Recommendation System for Engineering Education E-Learning Systems

In: Engineering Education 4.0

Author

Listed:
  • Thorsten Sommer

    (RWTH Aachen University, Faculty of Mechanical Engineering, ZLW - Center for Learning and Knowledge Management, IfU - Institute for Management Cybernetics, IMA - Institute of Information Management in Mechanical Engineering)

  • Ursula Bach

    (RWTH Aachen University, Faculty of Mechanical Engineering, ZLW - Center for Learning and Knowledge Management, IfU - Institute for Management Cybernetics, IMA - Institute of Information Management in Mechanical Engineering)

  • Anja Richert

    (RWTH Aachen University, Faculty of Mechanical Engineering, ZLW - Center for Learning and Knowledge Management, IfU - Institute for Management Cybernetics, IMA - Institute of Information Management in Mechanical Engineering)

  • Sabina Jeschke

    (RWTH Aachen University, Faculty of Mechanical Engineering, ZLW - Center for Learning and Knowledge Management, IfU - Institute for Management Cybernetics, IMA - Institute of Information Management in Mechanical Engineering)

Abstract

Today there is a flood of e-learning and e-learning related solutions for engineering education. It is at least a time consuming task for a teacher to find an e-learning system, which matches their requirements. To assist teachers with this information overload, a web-based recommendation system for related e-learning solutions is under development to support teachers in the field of engineering education to find a matching e-learning system within minutes. Because the e-learning market is subject of very fast changes, an agile engineering process is used to ensure the capability to react on these changes. To solve the challenges of this project, an own user-flow visual programming language and an algorithm are under development. A special software stack is chosen to accelerate the development. Instead of classical back-office software to administer and maintain the project, a web-based approach is used – even for a complex editor. The determining of the necessary catalog of related solutions within “real-time” is based on big data technologies, data mining methods and statistically text analysis.

Suggested Citation

  • Thorsten Sommer & Ursula Bach & Anja Richert & Sabina Jeschke, 2016. "A Web-Based Recommendation System for Engineering Education E-Learning Systems," Springer Books, in: Sulamith Frerich & Tobias Meisen & Anja Richert & Marcus Petermann & Sabina Jeschke & Uwe Wilkesmann (ed.), Engineering Education 4.0, pages 279-291, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-46916-4_22
    DOI: 10.1007/978-3-319-46916-4_22
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