IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v25y2023i2d10.1007_s10796-022-10332-y.html
   My bibliography  Save this article

RQ Labs: A Cybersecurity Workforce Skills Development Framework

Author

Listed:
  • Clinton Daniel

    (University of South Florida)

  • Matthew Mullarkey

    (University of South Florida)

  • Manish Agrawal

    (University of South Florida)

Abstract

This research contributes to the knowledge of how Information Systems (IS) researchers can iteratively intervene with practitioners to co-create instructional programs with a framework designed for fast-paced, rapidly changing IS fields such as cybersecurity. We demonstrate how complex fields, such as cybersecurity, have the need for a skilled workforce that continues to rapidly outpace supply from universities. IS researchers partnering with practitioners can use this research as an exemplar of a method to design, build, and evaluate these innovative co-curricular IS programs. Moreover, we find these co-curricular IS programs are essential to upskilling students, integrating training on the latest tools, systems, and processes in these rapidly evolving disciplines.

Suggested Citation

  • Clinton Daniel & Matthew Mullarkey & Manish Agrawal, 2023. "RQ Labs: A Cybersecurity Workforce Skills Development Framework," Information Systems Frontiers, Springer, vol. 25(2), pages 431-450, April.
    • Handle: RePEc:spr:infosf:v:25:y:2023:i:2:d:10.1007_s10796-022-10332-y
    DOI: 10.1007/s10796-022-10332-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-022-10332-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10796-022-10332-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Matthew T. Mullarkey & Alan R. Hevner & Pär Ågerfalk, 2019. "An elaborated action design research process model," European Journal of Information Systems, Taylor & Francis Journals, vol. 28(1), pages 6-20, January.
    2. Sanjay K. Sahay & Nihita Goel & Murtuza Jadliwala & Shambhu Upadhyaya, 2021. "Advances in Secure Knowledge Management in the Artificial Intelligence Era," Information Systems Frontiers, Springer, vol. 23(4), pages 807-810, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sagar Samtani & Ziming Zhao & Ram Krishnan, 2023. "Secure Knowledge Management and Cybersecurity in the Era of Artificial Intelligence," Information Systems Frontiers, Springer, vol. 25(2), pages 425-429, April.

    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. Shivam Gupta & Sachin Modgil & Choong-Ki Lee & Uthayasankar Sivarajah, 2023. "The future is yesterday: Use of AI-driven facial recognition to enhance value in the travel and tourism industry," Information Systems Frontiers, Springer, vol. 25(3), pages 1179-1195, June.
    2. Anthea Venter & Marne Vries, 2023. "Demonstrating the Elaborated Action Design Research (eADR) Model to Address Communication Challenges During Software Development," Systemic Practice and Action Research, Springer, vol. 36(3), pages 407-425, June.
    3. Bag, Surajit & Dhamija, Pavitra & Singh, Rajesh Kumar & Rahman, Muhammad Sabbir & Sreedharan, V. Raja, 2023. "Big data analytics and artificial intelligence technologies based collaborative platform empowering absorptive capacity in health care supply chain: An empirical study," Journal of Business Research, Elsevier, vol. 154(C).
    4. Antoine Harfouche & Bernard Quinio & Mario Saba & Peter Bou Saba, 2023. "The Recursive Theory of Knowledge Augmentation: Integrating human intuition and knowledge in Artificial Intelligence to augment organizational knowledge," Information Systems Frontiers, Springer, vol. 25(1), pages 55-70, February.

    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:spr:infosf:v:25:y:2023:i:2:d:10.1007_s10796-022-10332-y. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.