|
Title:
|
REAL WORLD, STUDENT SELECTABLE DATA FOR EDUCATION - LEARNING GRAPH ALGORITHMS |
|
Author(s):
|
Ville Karavirta |
|
ISBN:
|
978-972-8939-28-1 |
|
Editors:
|
Kinshuk, Demetrios G Sampson, J. Michael Spector, Pedro Isaías, Dirk Ifenthaler, Radu Vasiu |
|
Year:
|
2010 |
|
Edition:
|
Single |
|
Keywords:
|
elearning, graph algorithms, algorithm visualization, semantic data, location data |
|
Type:
|
Full Paper |
|
First Page:
|
129 |
|
Last Page:
|
136 |
|
Language:
|
English |
|
Cover:
|
|
|
Full Contents:
|
click to dowload 
|
|
Paper Abstract:
|
Learning data structures and algorithms is often boring. Interactive Algorithm Visualizations have been used to aid learning difficult concepts and make it more interesting. In addition to making visualization interactive, using real-life related examples is a good way to motivate students. In this paper, we introduce a web mashup for a more student-centered way of learning graph algorithms. The mashup is built on top of Google Maps and visualizes real-world semantic data fetched from DBPedia. The end product is a visualization of a graph on a map, where the nodes are real locations, such as Buildings in Tokyo. The students simulate graph algorithms by clicking nodes or edges on the graphs, thus engaging with the visualization. Furthermore, we report on our first experiences with students using these exercises. |
|
|
|
|
|
|
