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Generative Artificial Intelligence in Learning and Teaching

This resource provides SCU academics with recommendations for using Generative Artificial Intelligence (GenAI) in learning, teaching and assessment within the context of the University’s policies, procedures and guidelines.


thumbnail for GenAI video 1 GenAI in learning and teaching at SCU

This video provides a brief overview of the CTL’s resource on Generative Artificial Intelligence in Learning and Teaching.

Generative Artificial Intelligence (or GenAI) refers to AI models and algorithms designed to generate new content There is an ever-increasing number of GenAI tools, including the ChatGPT and Bard chatbots, which generate text, and Dall-E, which generates images.

Since GenAI tools will soon be integrated into most of the everyday software we use, such as search engines and Microsoft office, and with the increasing use of these tools in the workplace, it’s important that both students and academics have GenAI literacy and are capable and comfortable using these tools.

However, we can’t ignore the threat that GenAI tools pose to academic integrity.

Our resource has been created to provide SCU academics with recommendations for learning, teaching and assessment within the context of our organisation’s policies, procedures and guidelines.

Generally, at SCU, the use of GenAI is supported and encouraged where it does not pose an unacceptable risk to the assurance of academic integrity and standards.

Our approach at SCU is also consistent with the Australasian Academic Integrity Network Generative Artificial Intelligence Guidelines and the Tertiary Education Quality and Standards Agency’s position on GenAI in higher education.

Here on our landing page, we provide:

  • a brief introduction to GenAI,
  • ​key links for the use of GenAI in the higher education sector

and

  • an overview of SCU’s approach to GenAI, with links to find out more about SCU’s position, including reference to policy and guidelines.

In short, SCU embraces the use of GenAI and considers skills in using GenAI tools important in future workplaces, but also recognises the need to mitigate against unacceptable risk to the assurance of academic standards and integrity.

There are also links to:

  • the SCU Academic Integrity Framework for more information on academic integrity and GenAI use,

and

  • The library’s GenAI resources, which provides information on use, ethics and referencing.

In the next section, we provide recommendations for considering GenAI in assessment design, incorporating current higher education practice recommendations and SCU policy and guidelines.

To help guide academics we have developed the Assessment Adaptation Model-GenAI and you can find out more about this in the next video.

It’s important to keep in mind that GenAI capabilities are evolving rapidly. We can’t possibly stay ahead of it, or even know exactly which GenAI tools students are using. The best we can do is take the necessary steps to maintain academic standards while staying flexible in our approach and focusing on helping students use GenAI ethically and in ways that are authentic to their professions.

As GenAI technologies progress and guidance in the higher education sector continues to evolve, the Centre of Teaching and Learning will continue to add support resources for academics to the knowledge base.

GenAI in learning and teaching at SCU

This video provides a brief overview of support resources for SCU academics on this topic. 

GenAI refers to AI models and algorithms designed to generate new content, including text, images, videos, music and code. GenAI tools learn patterns from existing data and then regenerate it to create new data outputs in response to prompts. The content generated can be refined and improved by modifying the prompts. There are an increasing number of both open access and commercially available GenAI tools (Futurepedia). Recently, GenAI tools, such as ChatGPT and CopyAI, have become popular. Such tools are deemed to have legitimate and beneficial uses for both study and productivity in education and the workplace but also hold potential risks ethically and for academic integrity and rigour, particularly in the absence of reliable and valid detection tools for GenAI outputs.

For further information on GenAI in education see:

Tertiary Education Quality and Standards Agency (TEQSA) outlines directions for the future assessments providing guiding principles and propositions for higher education assessment and artificial Intelligence. Assessment Reform for the age of Artificial Intelligence.

The Australian Academic Integrity Network (AAIN) provides guidance on the appropriate use of generative AI in higher education, aligned with the Higher Education Standards Framework (1.4.4) See  AAIN Generative Artificial Intelligence (AI) Guidelines

TEQSA provide resources responding to advances in GenAI, including policies, upholding academic integrity, engaging with students, assessment design and using AI to support teaching and learning, in their higher education good practices hub.  https://www.teqsa.gov.au/guides-resources/higher-education-good-practice-hub/artificial-intelligence

SCU’s approach is consistent with these guidelines and practice recommendations. 

SCU is taking a “first principles approach” in recognising that GenAI software is not inherently good or bad and is a tool that can be used constructively to enhance students' and staff's efficiencies in the way they learn and teach. The approach to the use of GenAI tools at SCU is based around the following: 

  1. appropriate use of GenAI technology is supported and encouraged; 
  2. use of GenAI technology is prohibited when it would pose an unacceptable risk to assurance of academic standards and integrity; and 
  3. suitable measures will be employed to educate about the benefits and mitigate against the risks of using GenAI technology.

Find out more

For students, the SCU Library Guide on GenAI is a helpful resource.

Note: Given the rapidly evolving nature of GenAI technologies and largely opinion-based and low-level evidence on emerging practices for use in higher education, this resource represents the status quo at the time of writing (Aug 2023). As changes to policies and technology develop and evidence for best practice emerges, practice recommendations outlined within GenAI resources are likely to continue to change and develop.  

Considering GenAI in assessment design

The following resource, the Assessment Adaptation Model-GenAI (AAM-GenAI), provides a step-by-step guide for considering GenAI in the assessment design cycle. The resource incorporates current practice recommendations in higher education and SCU policy, and procedure requirements for academic integrity and assessment. The approach also supports students' digital literacy development in a GenAI-enabled world.

GenAi workflow infographic showing 7 steps to consider in assessment design

Image: Assessment Adaptation Model-GenAI (AAM-GenAI)

Find out more about adapting your assessment for GenAI.

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Design

Where you have sufficient time to design assessments from scratch or completely rethink your assessment, consider what task would mitigate potential risks associated with GenAI use and how you might include acceptable use of GenAI by students in the task design. 
Start here when you have a longer timeframe, and it is possible to design the assessment from scratch or fully redesign the assessment.

View Design resource
icon with microscope and callout words 'shorter time frame, go with what you have got

Analyse

Where your assessment is already designed and you do not have capacity for major changes, look at your current assessment and determine how it holds up if GenAI tools were used to complete the task. 
Start here where you have a shorter timeframe and there is insufficient time for a major redesign of assessment.

View Analyse resource
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Act

After analysing the assessment, if concerns arise about academic rigour or integrity with GenAI use, consider the modifications you can make to the task instructions and what limits to GenAI use you need to define and implement to mitigate risks.  

View Act resource
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Inform

Now that you have reviewed your assessment and decided on what would be acceptable or unacceptable use of GenAI you need to clearly and explicitly communicate this to students.  

View Inform resource
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Educate

As an Academic at SCU it is your responsibility to educate students on the ethical and responsible use of GenAI. Direct them to available support resources and foster an environment for students to ask questions about acceptable and unacceptable GenAI use to help reduce the risk of academic integrity breaches in assessment. 

View Educate resource
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Check

As the Unit Assessor or Marker, review the assessment you are grading for signals of GenAI use beyond the defined acceptable limits identified in the assessment brief, adhering to SCU guidelines. 

View Check resource
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Evaluate

Engage in reflective practice to gain insights for future assessments. This evaluation should encompass broader assessment improvements and innovative approaches for incorporating GenAI into learning and assessment practices. 

View Evaluate resource
thumbnail for GenAI video 2 Introducing the Assessment Adaptation Model - GenAI

In this video, we introduce the Assessment Adaptation Model-GenAI.

This resource provides a guide for considering GenAI in assessment design at SCU.

We will show you how the Assessment Adaptation Model is organised and how it is intended to be used.

The Assessment Adaptation Model- GenAI steps through the assessment cycle, providing practice recommendations around GenAI within the context of SCU requirements.

In the design step, we design an assessment from scratch, considering all elements of best practice in assessment design, including GenAI resilience.

Analyse is where we follow steps to check an assessment for GenAI resilience.

Act is when we set boundaries for GenAI use in an assessment and mitigate any threats to academic integrity.

The next step is to inform students about the limits of GenAI use in their assessment.

Educate is where we find ways to develop students’ GenAI skills with the unit’s teaching and assessment.

Check is carried out during assessment grading, where we look for signs of unacceptable GenAI use.

Evaluate is where we reflect on the assessment and consider whether changes may be required in future iterations. This evaluation will inform the ‘design’ step should changes be required, which restarts the cycle.

Depending on where you are in the assessment design cycle, or how long before your unit opens to students will determine where you should start.

We define a long timeframe as being when you still have the capacity to change UCMS information, such as the ULOs or assessment type or length. In that instance, you will start with the ‘design’ step.

A short timeframe is when the UCMS deadline has passed and changes for the current assessment cycle are no longer possible. In that instance, you would start with the ‘analyse’ step.

This link will take you to the knowledge base for considering generative artificial intelligence in assessment design where we introduce the Assessment Adaptation Model-GenAI.

These links will take you to each of the knowledge bases where you can find detailed information for each step of the Assessment Adaptation Model- GenAI.

Within the knowledge base, you can also navigate to the individual page for each step by clicking on the relevant icon.

At each step, you will be guided through practice recommendations and SCU requirements for considering the use of GenAI and adapting the assessment and unit teaching accordingly.

It’s important to keep in mind that GenAI capabilities are evolving rapidly. We can’t possibly stay ahead of it, or even know exactly which GenAI tools students are using. The best we can do is take the necessary steps to maintain academic standards while staying flexible in our approach and focusing on helping students use GenAI ethically and in ways that are authentic to their professions.

Introducing the Assessment Adaptation Model - GenAI

This video gives an overview of the AAM-GenAI resource, and its intended use for providing practice recommendations within the context of SCU’s requirements.


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