IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v12y2020i9p152-d408538.html
   My bibliography  Save this article

Generic Tasks for Algorithms

Author

Listed:
  • Gregor Milicic

    (Institute of Mathematics and Computer Science Education, Goethe University Frankfurt, 60325 Frankfurt, Germany)

  • Sina Wetzel

    (Institute of Mathematics and Computer Science Education, Goethe University Frankfurt, 60325 Frankfurt, Germany)

  • Matthias Ludwig

    (Institute of Mathematics and Computer Science Education, Goethe University Frankfurt, 60325 Frankfurt, Germany)

Abstract

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.

Suggested Citation

  • Gregor Milicic & Sina Wetzel & Matthias Ludwig, 2020. "Generic Tasks for Algorithms," Future Internet, MDPI, vol. 12(9), pages 1-16, September.
    • Handle: RePEc:gam:jftint:v:12:y:2020:i:9:p:152-:d:408538
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/12/9/152/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1999-5903/12/9/152/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stefania Bocconi & Augusto Chioccariello & Giuliana Dettori & Anusca Ferrari & Katja Engelhardt, 2016. "Developing Computational Thinking in Compulsory Education - Implications for policy and practice," JRC Research Reports JRC104188, Joint Research Centre.
    2. Michael Pollak & Martin Ebner, 2019. "The Missing Link to Computational Thinking," Future Internet, MDPI, vol. 11(12), pages 1-13, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yen-Cheng Chen & Pei-Ling Tsui & Ching-Sung Lee, 2021. "Is Mathematics Required for Cooking? An Interdisciplinary Approach to Integrating Computational Thinking in a Culinary and Restaurant Management Course," Mathematics, MDPI, vol. 9(18), pages 1-16, September.
    2. World Bank, 2019. "Children Learning to Code," World Bank Publications - Reports 31528, The World Bank Group.
    3. Ramón García-Perales & Ascensión Palomares-Ruiz, 2020. "Education in Programming and Mathematical Learning: Functionality of a Programming Language in Educational Processes," Sustainability, MDPI, vol. 12(23), pages 1-15, December.
    4. Michal Fojtík & Martin Cápay & Janka Medová & Ľubomíra Valovičová, 2023. "Activities with BBC micro:bit as a Foundation for Statistical Reasoning of Lower-Secondary Students," Mathematics, MDPI, vol. 11(14), pages 1-16, July.
    5. Margarida Rodrigues & Federico Biagi, 2017. "Digital technologies and learning outcomes of students from low socio-economic background: An Analysis of PISA 2015," JRC Research Reports JRC106999, Joint Research Centre.
    6. Ľubomíra Valovičová & Ján Ondruška & Ľubomír Zelenický & Vlastimil Chytrý & Janka Medová, 2020. "Enhancing Computational Thinking through Interdisciplinary STEAM Activities Using Tablets," Mathematics, MDPI, vol. 8(12), pages 1-15, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:12:y:2020:i:9:p:152-:d:408538. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.