TY  - JOUR
A1  - Milicic, Gregor
A1  - Wetzel, Sina
A1  - Ludwig, Matthias
T1  - Generic tasks for algorithms
T2  - Future Internet
N2  - Due to its links to computer science (CS), teaching computational thinking (CT) often involves the handling of algorithms in activities, such as their implementation or analysis. Although there already exists a wide variety of different tasks for various learning environments in the area of computer science, there is less material available for CT. In this article, we propose so-called Generic Tasks for algorithms inspired by common programming tasks from CS education. Generic Tasks can be seen as a family of tasks with a common underlying structure, format, and aim, and can serve as best-practice examples. They thus bring many advantages, such as facilitating the process of creating new content and supporting asynchronous teaching formats. The Generic Tasks that we propose were evaluated by 14 experts in the field of Science, Technology, Engineering, and Mathematics (STEM) education. Apart from a general estimation in regard to the meaningfulness of the proposed tasks, the experts also rated which and how strongly six core CT skills are addressed by the tasks. We conclude that, even though the experts consider the tasks to be meaningful, not all CT-related skills can be specifically addressed. It is thus important to define additional tasks for CT that are detached from algorithms and programming.
KW  - computational thinking
KW  - generic tasks
KW  - algorithms
KW  - K–12
KW  - problem solving
Y1  - 2020
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/56120
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-561201
SN  - 1999-5903
N1  - 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
VL  - 12
IS  - 9, art. 152
SP  - 1
EP  - 16
PB  - MDPI
CY  - Basel
ER  -