Skip to main content

Virtual Labs for Neural Networks E-courses

  • Conference paper
  • First Online:
  • 575 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2687))

Abstract

Human learning over the Internet (e-learning) aims to improve both the availability of information and the performance of the students involved. Virtual laboratories are one form of e-learning in which students learn practical skills by carrying out practical work. Our work here discusses the impact of e-learning, virtual labs and intelligent tutoring systems in education. We also introduce a neural network e- lab, which has seve ral features that support active learning and assist the assessment of the students.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Juul-Olsen, K. (2001). Transforming the Current Learning Model, E-Learning Summit, Brussels 10–11 May 2001.

    Google Scholar 

  2. Rosenberg, M. J. (2000). E-Learning: Strategies for Delivering Knowledge in the Digital Age. New York: McGraw-Hill Professional Publishing.

    Google Scholar 

  3. Cisco Systems (2001). Learning on Demand: A Strategic Perspective. White paper. Available in digital format at http://www.cisco.com

  4. CEDEFOP (2001). Non-Formal Learning: An Executive Summary. Available in digital format at http://www.trainingvillage.gr/ety/nonformal/exsumEN.asp.

  5. Hartley, D. E. (2000). On-Demand Learning: Training in the New Millennium. Boston, MA: HRD Press.

    Google Scholar 

  6. Brown G., Bull J., Pendlebury M. (1997). Assessing Student Learning in Higher Education. London: Routledge, chapter 7.

    Google Scholar 

  7. Sleeman, D., & Brown, S. (Eds.). (1982). Intelligent Tutoring Systems. Computers and People Series. London: Academic Press.

    Google Scholar 

  8. Woolf, B. (1987). Theoretical Frontiers in Building a Machine Tutor. In Kearsley, G. P. (Ed.) Artificial Intelligence and Instruction-Application and Methods, Reading, MA: Addison-Wesley, pp. 229–267.

    Google Scholar 

  9. Burns, H. L., Parlett, J. W. & Redfield, and C. L. (Eds.). (1991). Intelligent Tutoring Systems: Evolutions in Design. Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  10. Costa, E. (Ed.). (1992). New Directions for Intelligent Tutoring Systems, NATO ASI Series F: Computer and Systems Sciences, Special Program: Advanced Educational Technology, Vol. 91. Belin: Springer-Verlag.

    Google Scholar 

  11. Gauthier, G., Frasson, C. & VanLehn, K. (Eds.). (2000). Intelligent Tutoring Systems, Lecture Notes in Computer Science, Vol. 1839, Berlin: Springer Verlag.

    Google Scholar 

  12. Jerinic, L. & Devedzic, V. (2000). The Friendly Intelligent Tutoring Environment: Teacher’s Approach, SIGCHI Bulletin, Vol. 32 No. 1. p. 83.

    Article  Google Scholar 

  13. Bradshaw, J. M. (Ed.) (1997). Software agents, Cambridge, MA: MIT Press.

    Google Scholar 

  14. Weiss, G. (Ed.) (1999). Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence. Cambridge, MA: MIT Press.

    Google Scholar 

  15. Edwards, P., Bayer, D., Green, C. L., Payne, T. (2001). Experience with Learning Agents which Manage Internet-Based Information. Technical Report.

    Google Scholar 

  16. Perraju, T. S. (1997). Personal Assistant System for UNIX Users: A Multi Agent System Approach. Wayne State University, Department of Computer Science. Available online at http://citeseer.nj.nec.com/241126.html

  17. Lieberman, H. (2001). Autonomous Interface Agents, Media Laboratory, MIT. Available in electronic format at http://www.media.mit.edu/.

  18. Lieberman, H. (1995). Letizia: An Agent that Assists Web Browsing. Proceedings of the 1995 International Joint Conference on Artificial Intelligence, Montreal, Canada, August 1995. Available in electronic format at http://agents.www.media.rmt.edu/groups/agents/publications/.

  19. Davies, J.R., Gertner, A. S., Lesh, N., Rich, C, Rickel, J., Sidner, C. L. (2001). Incorporating Tutorial Strategies into an Intelligent Assistant. Proceedings of Intelligent User Interfaces 2001, January 2001, Santa Fe, New Mexico, USA. Available in electronic format at http://www.merl.com/projects/collagen/.

  20. Rich, C, Sidner, C. L. (2001). COLLAGEN: Applying Collaborative Discourse Theory to Human-Computer Interaction. To appear in AI Magazine (Special Issue on Intelligent User Interfaces), 2001. http://www.merl.com/projects/collagen/.

  21. Rich, C. & Sidner, C. L. (1997). COLLAGEN: When Agents Collaborate with People. Proceedings of the First Conference on Autonomous Agents, Marina del Rey, CA, February 1997. Available in electronic format at http://www.merl.com/projects/collagen/.

  22. Adamo, J. M. & Anguita, D. (1995). Object Oriented Design of a Simulator for Large BP Neural Networks, in Mira, J. & Sandoval, F. (Eds.). From Natural to Artificial Neural Computation. Lecture Notes in Computer Science, Vol. 930.

    Chapter  Google Scholar 

  23. Fuentes, L., Aldana, J. F. & Troya, J. M. (1993). An Object-Oriented Artificial Neural Network Simulation Tool, in Mira, J., Cabestany, J. & Prieto, A. (Eds.). New Trends in Neural Computation. Lecture Notes in Computer Science, Vol. 686.

    Chapter  Google Scholar 

  24. Gonzalez, E. J., Hamilton, A. F., Moreno, L., Sigut, J. F. & Marichal, R. L. (2001). Evenet 2000: Designing and Training Arbitrary Neural Networks in Java, in Mira, J. & Prieto, A. (Eds.). Bio-Inspired Applications of Connectionism. Lecture Notes in Computer Science, Vol. 2085.

    Chapter  Google Scholar 

  25. Coleman, D. et al. (1994). Object-Oriented Development: The Fusion Method. NY: Prentice Hall.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Bermejo, S., Revilla, F., Cabestany, J. (2003). Virtual Labs for Neural Networks E-courses. In: Mira, J., Álvarez, J.R. (eds) Artificial Neural Nets Problem Solving Methods. IWANN 2003. Lecture Notes in Computer Science, vol 2687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44869-1_91

Download citation

  • DOI: https://doi.org/10.1007/3-540-44869-1_91

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40211-4

  • Online ISBN: 978-3-540-44869-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics