Date
Publisher
arXiv
With the emergence of Artificial Intelligent chatbot tools such as ChatGPT
and code writing AI tools such as GitHub Copilot, educators need to question
what and how we should teach our courses and curricula in the future. In
reality, automated tools may result in certain academic fields being deeply
reduced in the number of employable people. In this work, we make a case study
of cybersecurity undergrad education by using the lens of ``Understanding by
Design'' (UbD). First, we provide a broad understanding of learning objectives
(LOs) in cybersecurity from a computer science perspective. Next, we dig a
little deeper into a curriculum with an undergraduate emphasis on cybersecurity
and examine the major courses and their LOs for our cybersecurity program at
Miami University. With these details, we perform a thought experiment on how
attainable the LOs are with the above-described tools, asking the key question
``what needs to be enduring concepts?'' learned in this process. If an LO
becomes something that the existence of automation tools might be able to do,
we then ask ``what level is attainable for the LO that is not a simple query to
the tools?''. With this exercise, we hope to establish an example of how to
prompt ChatGPT to accelerate students in their achievements of LOs given the
existence of these new AI tools, and our goal is to push all of us to leverage
and teach these tools as powerful allies in our quest to improve human
existence and knowledge.
Study at a glance
- Question: How should educators update college cybersecurity learning objectives in response to artificial intelligence tools like ChatGPT?
- Setting and data: Undergraduate cybersecurity program courses and learning objectives at Miami University.
- Method: Case study and thought experiment analyzing course learning objectives using the Understanding by Design framework.
Why it matters
With the emergence of AI tools like ChatGPT and GitHub Copilot, educators need to question what and how to teach. In reality, automated tools may deeply reduce the number of employable people in certain academic fields.
Key findings
- In an undergraduate cybersecurity program at Miami University, basic AI queries can achieve certain course learning objectives previously used to assess student mastery.
- Automated tools may deeply reduce the number of employable people in certain academic fields.
- Prompting AI chatbots can accelerate students toward achieving higher-level learning objectives that go beyond simple, automated queries.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
What is the application?
Who is the user?
Who age?
Why use AI?
Study design
