MAVIS: A multi-level algorithm visualization system within a collaborative distance learning environment

I. Koifman, I. Shimshoni, A. Tal

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We present a new model for an algorithm visualization system. Our model views the visualization system as an integral part of a broader distance learning environment. As such, it supports the heterogeneity of the Internet, the visualization and the diversity of the expected users. It does so by defining a few ways for handling multi-level visualizations. First, a visualization can run in various abstraction levels of the algorithm, depending on the familiarity of the students with the studied materials. Second, a visualization can use various levels of graphics, depending on the capabilities of the client machines. Third, the messages sent between the machines can be of various levels, depending on the communication loads. Another important aspect of a distance learning environment, which is supported by our model, is to facilitate collaboration and data sharing between the students and the instructor and between the students themselves. This paper also presents a system, MAVIS, that realizes the model and demonstrates its use on case studies.

Original languageEnglish
Title of host publicationProceedings - IEEE 2002 Symposia on Human Centric Computing Languages and Environments, HCC 2002
Pages216-225
Number of pages10
DOIs
StatePublished - 2002
Externally publishedYes
Event2002 IEEE Symposia on Human Centric Computing Languages and Environments, HCC 2002 - Toronto, ON, Canada
Duration: 3 Sep 20026 Sep 2002

Publication series

NameProceedings - IEEE 2002 Symposia on Human Centric Computing Languages and Environments, HCC 2002

Conference

Conference2002 IEEE Symposia on Human Centric Computing Languages and Environments, HCC 2002
Country/TerritoryCanada
CityToronto, ON
Period3/09/026/09/02

Bibliographical note

Funding Information:
We would like to thank the following people for implementing algorithms and visualizations within MAVIS: Lior Komem, Eli Cohen, Marina Magitman, and Tanya Kostanovich. This work was partially supported by the Israeli Ministry of Science, Grant 01-01-01509, by the Smoler Research Fund, by the Technion Fund for The Promotion of Research, and by the Ollendorff foundation.

Keywords

  • Algorithm visualization
  • algorithm animation
  • collaboration
  • distance learning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering

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