IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i23p10741-d1807600.html

Transforming Digital Signal and Image Processing Education: An AI-Driven Approach to Pedagogical Advancements

Author

Listed:
  • Dipali Bansal

    (Department of Electronics & Communication, Manav Rachna University, Faridabad 121004, Haryana, India)

  • Rashima Mahajan

    (Manav Rachna International Institute of Research & Studies, Faridabad 121010, Haryana, India)

  • Priyanka Bansal

    (Department of Electronics & Communication, Manav Rachna University, Faridabad 121004, Haryana, India)

  • Neha Chaudhary

    (Department of Electronics & Communication, Manav Rachna University, Faridabad 121004, Haryana, India)

  • Vimlesh

    (Manav Rachna International Institute of Research & Studies, Faridabad 121010, Haryana, India)

  • Himani

    (Department of Electronics & Communication Engineering, Ajay Kumar Garg Engineering College, Ghaziabad 201015, Uttar Pradesh, India)

  • Lorenzo Luchesini

    (Department of Mathematics, Polytechnic University of Milan, 20133 Milan, Italy)

  • Shabana Urooj

    (Department of Electrical Engineering, College of Engineering, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia)

Abstract

This paper explores the history of evolving teaching techniques in Digital Signal and Image Processing (DSIP) education with a focus on integrating Artificial Intelligence (AI) tools to close the continuing gap between theory and practice. Since DSIP has been at the center of Telecommunication, Medical Imaging, Robotics and AI, this paper examines active and student-centered learning paradigms, like collaborative, situation-based, and project-based learning (PBL) as viable pedagogical methods. The research methodology includes analyzing a survey using Data Visualization Tools in Python-3.12, 2023. This paper overviews the application of digital tools including MATLAB-R2024a, Python, Cloud-based systems, and AI-based learning analytics to promote experiential and adaptive learning to enable students to test complex signal and image processing systems. The findings emphasize the fact that these practices contribute to developing conceptual knowledge, critical thinking, and solving problems through engaging learners in real-life and data-driven scenarios. The results also indicate how the teachers can upgrade their instructional approach to technological innovations in teaching. Finally, this paper highlights the nature of AI-enriched pedagogies and practical experience to build the skills needed to operate in a more data-intensive, technologically advanced and sustainable engineering environment.

Suggested Citation

  • Dipali Bansal & Rashima Mahajan & Priyanka Bansal & Neha Chaudhary & Vimlesh & Himani & Lorenzo Luchesini & Shabana Urooj, 2025. "Transforming Digital Signal and Image Processing Education: An AI-Driven Approach to Pedagogical Advancements," Sustainability, MDPI, vol. 17(23), pages 1-18, December.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:23:p:10741-:d:1807600
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/23/10741/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/23/10741/
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:jsusta:v:17:y:2025:i:23:p:10741-:d:1807600. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.