Ruedi Arnold, Institute for Pervasive Computing, ETH Zurich, Switzerland.

InfoTraffic – Teaching Important Concepts of Computer Science and Math through Real-World Examples

Introduction

The use of suitable examples is a key to teach abstract, theoretical concepts. Interactive computer software allows us to use such examples to create attractive learning environments that not only appeal to students, but also enhance knowledge transfer in class. However, developing such highly specialized systems is costly, resulting in only few of these tools being developed for higher education. We argue that this effort can be amortized if the covered topics are fundamental concepts, built a collection of new learning environments in our project called InfoTraffic [1, 2, 3]. We here elaborate on its didactical concept and evaluate its use.

LogicTraffic: Propositional Logic and Safe Intersections

The LogicTraffic application offers an introduction to propositional logic (PL) using the example of traffic lights control at an intersection. The main task for the student is to find a formula in PL that makes a given intersection "safe", i.e., which prevents collisions through appropriate signaling on the corresponding traffic lights. With each lane corresponding to a variable, and true and false indicating a green and red light, respectively, a "safe" formula is one that avoids any two crossing lanes to simultaneously have their traffic lights on green. The learning targets of LogicTraffic include the basics of PL, and cover concepts such as variables, truth values, logical operators, formulas, equivalence of formulas, and normal forms. By using the intersection/traffic light metaphor, students can immediately connect the concept of PL to realworld situations, and the use of interactivity allows direct feedback (i.e., animated collisions) whenever conflicting assignments are made.

QueueTraffic: Queueing Theory and Traffic Jams

QueueTraffic offers a gentle introduction to queueing theory by letting students simulate and analyze traffic at an intersection. Important system parameters can easily be changed and their impact directly analyzed through simulation and statistical summaries. The learning goals of QueueTraffic include the basics of queueing theory and cover concepts such as throughput, arrival rate, average waiting time, and Poisson distribution. The main idea is that students gain an intuitive understanding of basic queueing theory through experimentation with a range of different intersections, by changing parameters like the arrival rate of cars for individual streets and the timing of the individual traffic lights, and observing the resulting system behavior.

Theoretical background

Goals of the research

Current status and interim conclusions

Open issues

Current stage in your program of study

PhD student at ETH Zurich, working about 2 years on this project. Targeted completion: summer/fall 2007.

What you hope to gain from participating in the Doctoral Consortium

Bibliographic references

[1] Learning environment InfoTraffic, online available along with teaching material. http://swisseduc.ch/compscience/infotraffic.
[2] R. Arnold, M. Langheinrich and W. Hartmann. InfoTraffic Teaching Important Concepts of Computer Science and Math through Real-World Examples. ACM SIGCSE Technical Symposium 2007, Covington, Kentucky, USA, March 2007.
[3] R. Arnold and W. Hartmann. LogicTraffic Logik in der Allgemeinbildung. Informatik-Spektrum, Springer Verlag, to appear.
[4] D. P. Ausubel. The use of advance organizers in the learning and retention of meaningful verbal material. Journal of Educational Psychology, 51:267.272, 1960.
[5] D. A. Bligh. What is the Use of Lectures? Penguin Books, Harmondsworth, England, 1972.
[6] J. S. Bruner. The Process of Education. Harvard University Press, 1960.
[7] J. S. Bruner, R. R. Oliver, and P. M. Greenfield. Studies in Cognitive Growth. John Wiley and Sons, New York, 1966.
[8] W. Hartmann, M. Naef, and R. Reichert. Informatikunterricht planen und durchführen. Springer, Berlin, 2006.
[9] R. Schulmeister. Taxonomy of Multimedia Component Interactivity. A Contribution to the Current Metadata Debate. Studies in Communication Sciences. Studi di scienze della communicazione., 3(1):61.80, 2003.
[10] A. Schwill. Fundamental ideas of computer science. EATCS-Bulletin, 53:274.295, 1994.