Talks and Poster Presentations (with Proceedings-Entry):

G. Futschek:
"Extreme Didactic Reduction in Computational Thinking Education";
Talk: WCCE 2013, Torun; 2013-07-01 - 2013-07-07; in: "learning while we are connected, vol. 3, book of abstracts,", N. Reynolds, M. Webb, M. Syslo, V. Dagiene (ed.); (2013), ISBN: 9788323130956; 106.

English abstract:
To master complex education scenarios, as for example learning algorithms, data structures, programming or data modelling, the educational technique of "didactic reduction" is very useful. For getting better educational results at the end the teacher may reduce details of the learning amount at the beginning. The goal of learning computational thinking is an understanding of principles and concepts of computer science. Depending on the learner and the learning situation the amount of details of the learning content or the size of learning objects or the amount of abstraction may be reduced. The purpose of reduction is to ease or even allow the understanding of concepts. We call a didactic reduction an extreme didactic reduction if the reduction is in some aspects so extreme that it cannot be reduced any more. An extreme didactic reduction may omit completely usually essential content or learning aspects. We give some examples of learning scenarios with different forms of extreme didactic reduction.

Didactic reduction, learning algorithms and data structures, learning programming, learning without text, learning by contest

Created from the Publication Database of the Vienna University of Technology.