IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i15p3340-d1206505.html
   My bibliography  Save this article

Achieving Effective Learning Outcomes through the Use of Analogies in Teaching Computer Science

Author

Listed:
  • Pawan Saxena

    (Amity Institute of Information Technology, Amity University, Lucknow 226010, Uttar Pradesh, India)

  • Sanjay Kumar Singh

    (Amity Institute of Information Technology, Amity University, Lucknow 226010, Uttar Pradesh, India)

  • Gopal Gupta

    (Department of Computer Science, University of Texas, Dallas, TX 75080, USA)

Abstract

Analogy-based learning methods map the concept being learned to a concept well understood by the learner. An analogy is primarily useful when learners do not know the topic being studied. Computer science is an area where the concepts exhibit a high level of abstraction and, hence, are hard for students to comprehend. The use of analogies in instruction can significantly reduce the cognitive load a student faces in learning abstract computer science concepts. The role of analogies in helping students learn computer science topics has not been explored adequately. This paper presents our efforts related to using analogy-based teaching in computer science. Over the last several years, we have developed extensive analogies for many advanced computer science concepts. We have used these analogies extensively in classroom teaching at our institution. We list the analogies that we have developed and used in our classroom teaching and, as illustration, discuss two analogies: one from the field of operating systems and another one in modular software design. We have also conducted experiments to evaluate the impact of using these two analogies on student learning outcomes. Our results confirm our hypothesis that analogy-based instruction techniques are effective and result in improved student learning outcomes.

Suggested Citation

  • Pawan Saxena & Sanjay Kumar Singh & Gopal Gupta, 2023. "Achieving Effective Learning Outcomes through the Use of Analogies in Teaching Computer Science," Mathematics, MDPI, vol. 11(15), pages 1-18, July.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:15:p:3340-:d:1206505
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/15/3340/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/15/3340/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Javier Alejandro Jiménez Toledo & César A. Collazos & Manuel Ortega, 2021. "Discovery Model Based on Analogies for Teaching Computer Programming," Mathematics, MDPI, vol. 9(12), pages 1-21, June.
    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. Carmen Lacave & Ana Isabel Molina, 2023. "Advances in Artificial Intelligence and Statistical Techniques with Applications to Health and Education," Mathematics, MDPI, vol. 11(6), pages 1-4, March.

    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:jmathe:v:11:y:2023:i:15:p:3340-:d:1206505. 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.