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A Knowledge Map Tool for Supporting Learning in Information Science

  • Helmut Vieritz
  • Hans-Christian Schmitz
  • Effie Lai-Chon Law
  • Maren Scheffel
  • Daniel Schilberg
  • Sabina Jeschke
Chapter

Abstract

Large classes at universities (> 1600 students) create their own challenges for teaching and learning. Audience feedback is lacking and fine tuning of lectures, courses and exam preparation to address individual needs is very difficult to achieve. At RWTH Aachen University, a course concept and a knowledge map learning tool aimed to support individual students to prepare for exams in information science through theme-based exercises were developed and evaluated. The tool was grounded in the notion of self-regulated learning with the goal of enabling students to learn independently.

Keywords

Knowledge Map Large Classes Self-Regulated Learning Higher Education Information Science 

Notes

Acknowledgements

The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7/2007–2013) under grant agreement no 231396 (ROLE project). Additional funding at the RWTH Aachen University was received from the Federal Ministry of Education and Research (BMBF) for the project Excellence in Teaching and Learning in Engineering Sciences (ELLI project).

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Helmut Vieritz
    • 1
  • Hans-Christian Schmitz
    • 2
  • Effie Lai-Chon Law
    • 3
  • Maren Scheffel
    • 2
  • Daniel Schilberg
    • 1
  • Sabina Jeschke
    • 1
  1. 1.IMA/ZLW & IfURWTH Aachen UniversityAachenGermany
  2. 2.Fraunhofer Institute of Applied Information Technology FITSankt AugustinGermany
  3. 3.Department of Computer ScienceUniversity of LeicesterLeicesterUK

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