Recommendation

Has Potential

Link

http://nova.umuc.edu/~jarc/idsv

Delivery Method

Java Applet

License

By Request

Language

English

Author

Duane J. Jarc

Institution

University of Maryland University College

Project

IDSV

RelationshipToProject

PartOfProject

Works

Yes

Description

This AV performs fundamental operations of Binary Search Trees (BST): Find, Insert and Delete. Find operation examines a given search key or detect that it is not present in the tree. Insert operation inserts a node with a given key to the tree only if it is not found. Delete operation remove a node with a given key and restore the tree if necessary. Three operations are smoothly animated and not hard to follow them. The dataset and keys (nodes) for three operations are randomized each time users performs operations, or it provides a option to choose “I’ll pick” mode which allows users to directly enters keys. Thus, users can construct their own tree or the AV can randomly generate the trees. The AV shows fairly simple visualizations, and it provides the option to either animate the algorithm procedures or step through the visualization by users. It has an "I'll Try" mode and in this mode users are asked to select what are the next steps or keys of BST for selected operations. Also, users can check their progress how many their tries are correct or incorrect. While animation is running or users are interacting with the visualization, it provides textual feedbacks about how the steps take. It must use IE.

Evaluation

Unlike most of the other AV, this AV provides an interactive prediction features. Users can not only watch animations, but also interactively predict the next step of BST by answering question given by the visualization or directly clicking a proper node. Thus, users can ensure their understanding of BST algorithm by actively predicting the next steps. In this prediction mode, the AV provides textual feedbacks which are accompanied by every user activity and visualization. In many AV, the lack of the significant benefits of using AV was often attributable to the AV that failed to actively engage the students, but this AV allows learners to test whether being able to predict the future steps of the BST algorithm, and that would improve learning about the algorithm. In particular, since the user’s activities are coupled with the textual feedback about each answer that the users enter or click a node for BST, the visualization can proactively engage and involve users. This AV provides relatively simplistic features, and many of useful features, such as multiple views, pseudo codes, algorithm explanation and performance information, are not present in the visualization. Simple stepwise presentation of the behavior of BST using animation which comes with a short description would be useful for understanding it. Users can speed up for the easy part and slow down the difficult part to take a moment to examine what is happening. Although it is static and not connected to the AV, a brief overview of BST algorithm was useful. It would have been more beneficial if explanation of entire algorithm or pseudo code is coupled with the visualization. Overall, a good AV, but a bit simplistic since all the user can do is show where the node is inserted, or click on node to delete.

ActivityLevel

Random Data; Predictions

GoodFor

Lecture Aid; Self Study; Lab Exercise

Screenshots

Videos

References

HowToUse

First Visited

2006-08-01

Last Visited

2008-07-15

Last Updated

2005-12-03

Topic

BinarySearchTrees

Community

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