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 shows simple algorithm animations for graph representation. Using this AV, it allows the user to learn how an undirected graph can be represented by an adjacency matrix. In order to understand the graph operations, users can watch animations which shows transformations between two different types of graph representations: Graph and Matrix, or in "I'll try" mode, they can predict the next step by clicking the target node in Graph or elements in the adjacency matrix. Users can construct Graph or Matrix representation by themselves in the "I'll try" mode. User can select one of the representations by choosing the radio buttons, and that selected representation is transformed into the other representation, and their transformations are smoothly illustrated by animation. For example, if the user selects Graph, the AV shows how that Graph is transformed into the adjacency matrix. On the other hand, if the user selects Matrix, it illustrates how each element in the matrix can be transformed into Graph which consists of nodes and edges. The animations allow users to step through the algorithm operations or to passively watch continuous animation. Also, the user can change the speed of animation.

Evaluation

This AV includes some necessary controls which allow the user to control animations such as the change of animation speed, stepping forward. The animation which shows transformations between graph and adjacency matrix can be paused, resumed and even aborted, thus the user can take some time to examine the steps of graph representations and what is happening in both Graph and Matrix. The most efficient benefits I could observe for this AV is that it provides “I’ll try” mode in which users can construct graph or adjacency matrix representation by themselves. Users can construct graph corresponding to adjacency matrix by clicking edge nodes, or construct their own adjacency matrix corresponding to a graph by clicking matrix cells. It provides textual feedbacks at each user try, whether or not each try was correct. Thus, it encourages the users to self-evaluate and check their leanings and understandings about between Graph and adjacency matrix representation. It also allows the users to check their progress how many their tries are correct or incorrect. Its visualization is very straightforward, and somewhat shows how graph or adjacency matrix can transform into the other representation. However, the biggest problem with this visualization is that the users cannot specify and construct their own input dataset and the data set for graph is only randomized by this AV. That means the users cannot experiment their own graphs or adjacency matrix. It is very difficult for users to observe specific properties of undirected graphs such as cycles, trees, or connected from the AV generated graph. The “I’ll try’ mode would improve learning outcomes because it is coupled with the textual feedback about each answer that the user tries. However, A minor problem could arise from this approach, if the students/users interpret the AV as a guessing game. I think this AV can be used for a classroom presentation or student’s hand-on lab. Instructors can easily measure students’ performance by simply checking how many users’ tries were correct on the progress window. However, it seems that this AV can support only for basic level of leanings for graph-adjacency matrix. Advanced users could rarely benefit from this AV.

ActivityLevel

Random Data; Predictions

GoodFor

Lecture Aid; Self Study; Lab Exercise

Screenshots

Videos

References

HowToUse

First Visited

2008-06-10

Last Visited

2008-07-15

Last Updated

2005-12-03

Topic

GraphRepresentations

Community

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