Educating students on GenAI use

Learning to work with GenAI is becoming a critical capability for most graduates (Lodge, et al., 2023). Given the status quo of GenAI, digital literacy education is critical, and AI tools should be included in the curriculum to foster student skill development for employability (Rudolph et al., 2023). The notion of digital literacies and critical thinking have long been core outcomes for students in higher education (White, 2021), however, we now need to extend this to incorporate the emergence of the AI context.

TEQSA holds the position that critical, ethical, and productive engagement with GenAI should be taught and also integrated into assessment tasks in meaningful ways so students will regard it as an essential part of their learning, rather than a supplementary component (Lodge, et al., 2023). Similarly, the AAIN (2023) informs that students should have opportunities to develop capabilities in the ethical use of GenAI relevant to their discipline and future professional practice through ethical engagement with these tools in both learning and teaching activities and assessments.  Guidelines for teaching staff, students and academic support staff (e.g. learning coaches and librarians) are clearly articulated (AAIN, 2023), with the following key points serving as a summary: 

  • Students should have opportunities to develop AI literacy in addition to traditional information literacy skills and digital literacy skills.
  • AI literacy skills development will serve to critically evaluate AI technologies; communicate and collaborate effectively with AI; and use AI as a tool online, at home, and in the workplace.
  • Ethical and responsible use of AI tools in academic writing and research conversations needs to be promoted.
    • This includes guidance on correct attribution and acknowledgment conventions when incorporating generative AI outputs.
  • Invest in conversations early in units and courses to ensure a shared understanding with students of how and when AI tools can be used

At SCU, appropriate use of GenAI is encouraged and supported where unacceptable risks to academic integrity and standards are not posed. In addition, we have the responsibility of educating students about the benefits and mitigating against the risks of using GenAI technology.  

Given the sector's and our organisation's emphasis on our responsibility for educating students in using GenAI productively, effectively and responsibly, we are providing guidance and examples for approaches that may be taken. 

Consider the broad guiding principles: 

  1. Take responsibility for developing student GenAI capabilities. Drawing explicitly from Lodge et al. (2023), the first guiding principle is that assessment and learning experiences equip students to participate ethically and actively in a society where AI is ubiquitous.
  2. Embed GenAI capability development into the curriculum. Evidence supports generic skills development, such as academic and digital literacies, is more effective through embedded approaches rather than bolt-on approaches (Munn & Small, 2017). With intensive curriculum delivery, as is the case with the SCM, this may be critical to maximise student uptake of support for skill development. Embedding capability development within the curriculum also provides opportunity for targeted approaches within disciplines, connected to the way GenAI tools may be used in the workplace. This affords opportunities for authentic learning and AI literacies can be scaffolded so students are learning discipline content and GenAI capabilities concurrently.  
  3. Leverage off examples of how GenAI is being used within disciplines/ professions to assist productivity and to stimulate student engagement through authenticity. As an educator, take what you know about your discipline and good pedagogy, and think about how GenAI may support this (Rudolph et al., 2023).
  4. Connect learning activities with what is required in assessment tasks. Meaningful alignment between learning outcomes, activities, classes, content and assessment is a key feature of the SCM. Think about the parameters around acceptable use of GenAI for assessment and model tasks around this or, where GenAI tools are not permitted for completing assessments, consider other ways these tools might be used to support learning, for example, generating practice questions and feedback, and understanding concepts.
  5. Establish a secure environment where students can freely pose questions and learn, without the fear of being reprimanded for academic dishonesty. At SCU we take an educative approach to Academic Integrity. Students are encouraged to ask Unit Assessors to clarify any uncertainty they have around GenAI and it is the UA's responsibility to answer these questions. Here are some conversation starters from TEQSA you may like to use with your students to generate an open dialogue around GenAI use. 

A framework for developing AI literacies

Hillier (2023) proposed a framework for developing AI literacies in higher education built around: the ethical use of AI;  knowledge of AI affordances; effective use of AI; evaluation of AI output, and integration of AI tools into practice. The framework has been adapted here:

Ethical use of AI tools

Knowledge of AI affordances

Working effectively with AI & evaluating outputs

Use and integration into practice

Apply critical thinking skills to consider the ethical implications of using GenAI. Some issues to consider are:

  • data ownership
  • intellectual property
  • privacy and security
  • biases
  • fraud and cheating
  • undisclosed plagiarism
  • digital divide and equity
  • exploitation.

Awareness of the capabilities and limitations of AI tools will help users choose appropriate tools for their intended purpose.


Capabilities for prompt writing and evaluation of e-generated outputs need developing. Skills for critiquing and making evaluative judgements about information sources are essential and must be applied to GenAI outputs, as they can be unreliable and inaccurate.

GenAI can add value and improve productivity for study, personal and professional purposes.


AI Literacy Framework (adapted from Hillier, 2023)

For learning and teaching ideas, and links to resources to support AI literacy development using this framework, please download: AI literacy framework _staff resources.

For more information on embedding literacies into the curriculum see: Embedding academic literacy support when designing curriculum.


References

AAIN Generative AI Working Group. (2023). AAIN Generative Artificial Intelligence Guidelines, Australian Academic Integrity Network, https://doi.org/10.26187/sbwr-kq49

Hillier, M. A. (2023, March 30). A proposed AI literacy framework. TECHE. https://teche.mq.edu.au/2023/03/a-proposed-ai-literacy-framework/

Lodge, J. M., Howard, S., Bearman, M., Dawson, P, & Associates. (2023). Assessment reform for the age of Artificial Intelligence. Tertiary Education Quality and Standards Agency https://www.teqsa.gov.au/sites/default/files/2023-09/assessment-reform-age-artificial-intelligence-discussion-paper.pdf

Munn, J., & Small, J. (2017). What is the best way to develop Information Literacy and academic skills of first year health science students? A systematic review. Evidence Based Library and Information Practice, 12(3), 56–94. https://doi.org/10.18438/B8QS9M

Rudolph, J., Tan, S., & Tan, S. (2023). ChatGPT: Bullshit spewer or the end of traditional assessment in higher education? Journal of Applied Learning & Teaching, 6 (1). https://doi.org/10.37074/jalt.2023.6.1.9

White, A. M. J. (2021). Information literacy and critical thinking in higher education: Some considerations. In M. Khosrow-Pou (Ed.), Research anthology on developing critical thinking skills in students (pp. 111- 124). IGI Global. https://doi.org/10.4018/978-1-7998-3022-1.ch007