Improving the Educational Impact of Algorithm Visualization
Thomas L. Naps (naps@uwosh.edu)
Guido Rößling (roessling@acm.org)
Algorithm visualization (AV) has not yet fulfilled its pedagogical promises. At the same time, instructors lament that incorporating AV into their courses is too time-intensive. This working group therefore focuses on pedagogical strategies for effective AV incorporation with an impact on improving student understanding.
Participants should have some experience in using AV in instruction and be willing to share ideas on what can make AV usage effective or ineffective. At the early working group stages, these techniques will be collected together with examples. In Aarhus, the working group will focus on developing a strategy for coherently and systematically testing the effectiveness of the techniques. How can we define metrics for determining improved student understanding, if it occurs? The group's report will help provide the details for such testing.
After ITiCSE, the group members shall use AV in their instruction and monitor its effectiveness according to these metrics. The interaction between members will continue for comparing and reviewing results and building a solid basis for further instructional use of AV. The working group participants will hopefully collaborate in writing follow-up papers describing their efforts in more detail.
Members of this group are:
- Wanda Dann, Ithaca College
- Vicki Almstrum, University of Texas
- Rocky Ross, University of Montana
- Myles McNally, Alma College
- Jay Anderson, Franklin and Marshall
- Angel Velazquez, Universidad Rey Juan Carlos
- Chris Hundhausen, University of Hawaii
- Susan Rodger, Duke University
- Rudolf Fleischer, Honk Kong University of Science and Technology
- Lauri Malmi, Helsinki University of Technology
- Ari Kohonen, Helsinki University of Technology
The final report of this Working Group is available here and in the ACM Digital Library.