WEBSITE BLOCKED

Access to this website has been blocked because it has been found to facilitate a contravention of section of the provisions of the Tertiary Education Quality and Standards Agency Act 2011 (TEQSA Act) regulating academic cheating services.
 

The relevant provisions in the TEQSA Act

• make it an offence for any person to provide or advertise academic cheating services relating to the delivery of higher education in Australia, whether that person is in Australia or elsewhere
• allow TEQSA to apply under section 127A to the Federal Court for an injunction requiring carriage service providers to take steps to disable access to websites found to contravene or facilitate a contravention of sections 114A or 114B of the TEQSA Act
• provide for financial and custodial penalties where an offence is proven of up to 500 penalty units, 2 years imprisonment, or both. The TEQSA Act distinguishes between cheating services provided on a commercial basis, and where the cheating service is provided without payment.

If you use academic cheating services you might not learn all the skills you need for your career. You also risk losing your money, your enrolment, and even your student visa. In some cases, you could be blackmailed by the cheating service providers who might threaten to tell your institution or a future employer that you cheated.
 

Cheating is never the right answer.

Why are we blocking academic cheating websites?

Australia’s anti-cheating laws make it an offence to provide or advertise academic cheating services in higher education, with penalties of up to 2 years’ imprisonment or fines of up to 500 penalty units ($111,000 on 30 June 2021) or both.

TEQSA  is working to disrupt access to these sites to protect students and the integrity of higher education.

Which academic cheating services have been blocked?

• View the alphabetical list of blocked illegal cheating websites

Complain about a commercial academic cheating website

How to complain

You can help to stamp out academic cheating. Complete the form to complain about suspected commercial academic cheating services (cheating websites).

If you are unable to submit your complaint using the online form, you can make a complaint by emailing TEQSA at integrityunit@teqsa.gov.au.

TEQSA may use any information it receives from any person who contacts it about suspected commercial academic cheating services in taking enforcement action (including in the pursuit of civil penalty or criminal penalty proceedings pursuant to sections 114A and 114B of the Tertiary Education Quality and Standards Act 2011), either independently or in conjunction with other agencies.

Complain or raise concerns about the blocking of a website

You can tell us why you think a particular website shouldn’t be blocked (you don’t have to give us any personal details) or that you have concerns about the blocking, by submitting the form you can access using the link above.

If you are unable to submit your complaint or concerns using the online form, you can make a complaint by emailing TEQSA at integrityunit@teqsa.gov.au.

TEQSA may use any information it receives from any person who contacts it about the disruption of access to an online location in taking enforcement action (including in the pursuit of civil penalty or criminal penalty proceedings pursuant to sections 114A and 114B of the Tertiary Education Quality and Standards Act 2011), either independently or in conjunction with other agencies.

This page contains resources to support institutions, staff and students in considering the potential impacts and benefits generative artificial intelligence (gen AI) tools pose for teaching, learning and assessment. TEQSA understands the uniqueness of each provider’s circumstances and therefore offers the following case studies and resources as examples of approaches being taken, both in Australia and beyond, for consideration. The resources on this page are not intended as guidance but rather seek to share approaches and practice.

Author: Benito Cao, The University of Adelaide

Focus area: Making academic integrity visible

The sudden irruption of generative artificial intelligence (gen AI) in higher education has sparked widespread concerns regarding the viability of essays as a form of assessment. Indeed, the argument often goes that large language models (LLMs) such as ChatGPT signal the death of the essay. But do they? Will they? Or, to paraphrase Mark Twain, is it that reports of the essay’s death are greatly exaggerated?

This case study outlines a pedagogical initiative designed to promote academic integrity and secure the essay in the age of gen AI. The initiative reimagines the ‘two-lane’ approach that proposes the combination of secured assessments (lane 1) with unsecured open assessments (lane 2).

The reimagined approach resembles the two-lane model in its partial reliance on in person assessments to validate student learning. Yet, it challenges the unrestricted nature of the Lane 2 approach by illustrating the value and validity of a ‘middle lane’ approach which focusses on the ecosystem to foster and facilitate authentic learning (Curtis 2025). The initiative relies on a pedagogical ecosystem designed to develop trust between students and teachers notwithstanding that academic integrity requires that we ‘trust but verify’ in cases of potential academic misconduct.

The pedagogical ecosystem includes the following elements:

1. an exploration of the potential for gen AI tools to fabricate information, with illustrations of real-world ‘hallucinations’
2. the provision of clear guidelines, with references to university policies and industry standards to showcase the rationale and relevance of the guidelines
3. the requirement to include a gen AI appendix when students use gen AI in the production of their essays
4. a reminder that students are expected to fully understand every aspect of their essay, and that if there is a concern about the use of gen AI tools exceeding the assessment guidelines, they may be asked to discuss the assignment before the mark is finalised
5. explicit advice to keep drafts, notes, annotated readings and any other materials students have used, as evidence of how their essay has been produced in case its authorship is questioned
6. the reliance on secured (in-person) assessments, worth between 30% and 50% of the overall mark, to help validate student learning and to compare with the essay preliminary mark if there are academic concerns regarding the production of the essay.

This pedagogical ecosystem is designed to enable the (relatively secured) implementation of a ‘middle lane’ approach, that permits a limited use of gen AI. Specifically, students are allowed to use gen AI tools to assist with idea generation and language expression. For example, I tell students:

• if they struggle to come up with ideas for their essays, they can use gen AI but any ideas suggested by the tool must be validated
• while they can use gen AI to assist with language expression, they should not allow the tool to take control of the narrative, that the narrative should reflect their own voice.

In essence, students are allowed a limited use of gen AI but are expected to remain the authors of their essays and to be transparent regarding their use of gen AI tools. Students are reminded of this basic expectation of transparency in the assignment submission portal. This is the last thing they read before uploading their essay:

Don't forget to include a gen AI appendix if you have used gen AI tools (for example, ChatGPT, Copilot, Gemini, Claude, Grammarly, etc.)  in the production of the essay. The absence of this appendix is equivalent to stating: I did not use GenAI. If this statement turns out to be false, this would constitute a breach of academic integrity. Remember the slogan: Don't be sorry, just declare it.

The approach which I have titled, Don't be sorry, just declare it, reflects the integration of four normative principles: caution, trust, relevance and transparency  (Cao 2025). It is a slogan used by Australian Customs and Biosecurity warning people who arrive in Australia to declare all goods they might not be permitted to bring into the country, rather than apologise afterwards for the lack of a declaration.

The evidence suggests that this approach can go a long way in addressing some of the most urgent pedagogical challenges posed by gen AI, particularly concerns with academic integrity. The evidence also suggests that this approach can improve security of the essay and thus contribute to its preservation as a valuable form of assessment in the age of gen AI.

References

Cao, B. (2025). Don’t Be Sorry, Just Declare It: Pedagogical Principles for the Ethical Use of ChatGPT, Master Bullshit Artist of Our Time. In: 11th International Conference on Higher Education Advances (HEAd’25). Valencia, 17-20 June 2025.

Curtis, G. J. (2025). The two-lane road to hell is paved with good intentions: why an all-or-none approach to generative AI, integrity, and assessment is insupportable. Higher Education Research and Development. (Published online: 18 March 2025).

Authors: Tanya Henry and Associate Professor Christine Slade, Institute for Teaching and Learning Innovation (ITaLI), The University of Queensland

Focus area: Assessment design

The Lead through learning strategy 2025 - 2027 (the Strategy) is a whole-of-university strategy at The University of Queensland (UQ) aimed at addressing the impact of generative artificial intelligence (gen AI) in education and sits within the UQ’s AI in Education Action Plan (2025 – 2027). This initiative is a partnership between 5 faculties and the Deputy Vice-Chancellor (Academic) (DVC(A)) portfolio which aims to ensure graduates can use gen AI ethically and responsibly and that assessment practices assure learning outcomes.

Learning designers are embedded in the faculties for 3 years to spearhead the cultural change in assessment and teaching practices in the light of gen AI.  As this is one piece of a broader program of work within the Strategy, the Learning Design (LD) team is led by a Strategic Lead based in the central teaching unit, who provides leadership and mentorship to the team of faculty-based learning designers and is the conduit between LDs and the DVC(A).

The Strategy has 2 main goals:

• Preparing students for responsible gen AI use by equipping students with ethical and practical skills they can use in their studies, careers and communities, and preparing them to lead and shape the future of gen AI integration in their fields.
• Maintaining the integrity of the learning process by ensuring that academic standards are upheld through secure and credible assessment practices.

Partnering with faculties to achieve these goals enables contextualised approaches within disciplines, with each faculty developing an operational plan that reflects their individual context. The central teaching and learning unit, the Institute for Teaching and Learning Innovation (ITaLI), complements this approach, upskilling gen AI use and assessment transformation, providing institutional guidance and facilitating collaboration.

Within faculties learning designers, in collaboration with teaching staff, are developing and delivering workshops to support staff in using gen AI including how to enhance the validity and security of assessments. Across faculties staff are engaging in communities of practice including the establishment of an AI Steering Committee to explore the development of a whole-of-faculty gen AI curriculum.

Key lessons or points for implementation

• Define success and leverage existing data:
  Clearly articulate what success looks like in advancing the project’s core goals and how progress will be measured. Engage with colleagues who can identify existing data sources and explore future possibilities to support evidence-based decision-making.
• Integrate with other initiatives to maximise impact and minimise change fatigue:
  Assessment transformation should align with other strategic initiatives, such as inclusive design and indigenising the curriculum, to create synergies rather than silos. This approach fosters collaboration, reduces duplication of effort and helps avoid staff fatigue by streamlining change.
• Support educators through incremental, reflective change:
  Meet educators where they are and guide them through manageable, meaningful steps in assessment reform. Celebrate small wins, reflect on what works and what doesn’t, using a continuous improvement approach.
• Contextual partnerships across the university:
  Connecting both top down and ground up goals is important to support staff buy-in where success requires teaching and assessment practices to change.

Authors: Professor Ruth Greenaway, Dr Zachery Quince, Dr Joanne Munn, Southern Cross University

Focus area: Assessment design

Generative artificial intelligence (gen AI) enables students to generate sophisticated academic outputs with minimal effort, challenging traditional assessment methods and raising concerns about academic integrity. Southern Cross University (SCU) has responded to this challenge by developing the Assessment Adaptation Model – Gen AI (AAM-Gen AI), a comprehensive, pedagogically grounded model designed to help educators adapt assessments to be resilient and meaningful in the gen AI era.

Gen AI tools have made traditional assessment vulnerable to misuse, necessitating systemic changes that move beyond reactive policies and detection-based approaches, advocating for proactive, authentic assessment designs that foster deep learning, critical thinking and ethical reasoning.

Authentic assessments, mirroring real-world complexities that require personal engagement, are less susceptible to gen AI misuse and promote transferable graduate skills. SCU’s AAM-Gen AI model arises from this context, aiming to align assessment design with both academic integrity and the evolving digital landscape.

The AAM-Gen AI model consists of seven interrelated components spanning the assessment lifecycle. It promotes a holistic, proactive approach that integrates gen AI considerations into every stage of assessment, encouraging transparent, ethical and capability-building practices rather than punitive measures.

• Design: 
  Craft assessment tasks that emphasise higher-order thinking, contextual relevance and personal engagement reducing gen AI misuse and enhance learning.
• Analyse: 
  Critically evaluate assessments using a security risk matrix to identify and mitigate vulnerabilities to gen AI exploitation.
• Act: 
  Implement strategic changes like multi-stage tasks using security rating scales to strengthen assessment integrity.
• Inform: 
  Clearly communicate gen AI usage policies to students to support fairness and ethical learning.
• Educate: 
  Develop students’ AI literacy and critical thinking to foster ethical and informed engagement with gen AI tools.
• Check: 
  Verify authenticity through nuanced, evidence-based approaches while promoting a culture of trust and accountability.
• Evaluate: 
  Continuously review and refine assessment practices to ensure alignment with learning goals and responsiveness to gen AI developments.

Key lessons or points for implementation

• Spend time considering current assessment and proactively redesign with gen AI in mind.
• A security risk matrix is a conversation starting point to reconsider assessment design, it is not a definitive measure of assessment security.

Assessment Adaptation Model-Gen AI (AAM-Gen AI)