Lesson 8 • Genetic counselling

Genetic testing for particular diseases has been available since the 1950s. Mutations in the BRCA1 and BRCA2 genes are associated with a significantly increased risk of breast cancer and ovarian cancer, as well as some other cancers. Genetic testing for these mutations can help individuals and their healthcare providers make informed decisions about screening programs for early detection, disease prevention, and treatment options. Some individuals are reluctant to undergo genetic testing due to concerns about the use of genetic information by life insurance companies.

Traditionally, life insurers in Australia have assessed applicants according to their level of risk. This process, known as underwriting, allows insurers to consider a range of factors, including age, health status, medical history and family history, when deciding whether to offer cover and how much to charge. Before October 2026, life insurers could also take certain predictive genetic test results into account when assessing applications for products such as life cover, income protection, trauma insurance and total and permanent disability insurance. Depending on the results, insurers could increase premiums, apply exclusions or conditions, or in some cases refuse cover.

Private health insurance operates differently from life insurance in Australia. Private health insurance is community-rated, meaning insurers cannot refuse cover or charge higher premiums because of a person’s genetic test results or family history of a genetic condition. Although waiting periods may apply for pre-existing conditions, health insurers are not permitted to use genetic information to determine eligibility or premium costs. The concerns about genetic discrimination have therefore primarily related to life insurance products that rely on individual risk assessment.

To address these concerns, the Australian Government introduced legislation that prohibits life insurers from using protected genetic information when assessing new life insurance applications. The new law came into effect on 8 October 2026. Under the new legislation, life insurers are no longer allowed to consider predictive genetic test results when making decisions about new life insurance policies. The ban applies to a wide range of genetic information, including tests that predict future disease risk, pharmacogenomic tests, direct-to-consumer genetic tests and genetic tests conducted for research purposes. It also protects information about whether a person has had, plans to have, or has been advised to have a genetic test, as well as information relating to genetic testing of family members.

However, the legislation does not prevent insurers from considering diagnosed medical conditions. If a person has already developed a disease, insurers may continue to use information about that diagnosis when assessing risk, even if the diagnosis was made using genetic testing. The law therefore distinguishes between a person's inherited risk of future disease and diseases that have already been diagnosed.
 

References

Treasury Laws Amendment (Genetic Testing Protections in Life Insurance and Other Measures) Bill 2025. (2025). Aph.gov.au. https://www.aph.gov.au/Parliamentary_Business/Bills_Legislation/Bills_Search_Results/Result?bId=r7409

Lacaze, P., Tiller, J., Brotchie, A., Nguyen-Dumont, T., Steen, J., Belluoccio, D., Young, M.-A., Willis, A. M., Mitchell, L. A., Terrill, B., Nowak, K. J., Burns, B., Horton, A. E., Nicholls, S. J., Ademi, Z., Green, R. C., Manchanda, R., Thompson, B. A., Thomas, D., & Milne, R. L. (2026). Feasibility and outcomes of the DNA Screen nationwide adult genomic screening pilot. Nature Health, 1(1), 90–98. https://doi.org/10.1038/s44360-025-00020-x

One of the key aims of the science curriculum is for students to develop “an ability to solve problems and make informed decisions about current and future uses of science while taking into account ethical, environmental, social and economic implications of decisions”.

The study of genetics is an ideal opportunity to examine the difference between scientific information and social judgement. In the next routine, students will examine genetic screening as a way of identifying biological differences, but it is also important to ask what happens when those differences are described as “normal” or “abnormal”.

Key question: “What can science tell us about a genetic condition, and what questions require values, ethics or personal judgement?”

Encourage students to ask what information a genetic test provides and, equally importantly, what it does not provide. Highlight the difference between genetic influence and genetic determination—remind students that many human characteristics involve complex interactions between genes, environment and individual experience.

When discussing the history of eugenics, help students look beyond the idea that it was simply an error made by scientists in the past. Eugenic thinking developed alongside concerns about immigration, poverty, crime and rapid social change. Encourage students to ask why particular scientific explanations became attractive at that time.

Draw students’ attention to the repeated use of language such as “normal”, “abnormal”, “disease”, “difference”, “fit”, and “unfit”. Using these terms has implied assumptions that difference is less and that some people are more or less worthy.

Key question: “What social problems were people trying to explain, and why might heredity have seemed like a convincing explanation?”

An understanding of the laws of inheritance lead to the development of family trees during a time of poverty and drought. A variety of traits were followed down generations, eventually leading to judgements about intelligence and the identification of people considered “unfit” by those who considered themselves “more fit”.

The American example of Buck v. Bell can be used to illustrate the relationship between science, law and authority. This court case involved the American Supreme court making the decision that Carrie Buck (pictured above on the left), a young woman who had been abused as a child and became pregnant, was feeble-minded and immoral and that these conditions were hereditary because her mother had been poor and had children out of wedlock. This “science” was used by the court to justify Carrie’s sterilisation, the first of over 60,000 in America.

This social interpretation of the science was extended by the Nazi regime in Germany, where groups of people were dehumanised, and science was used to validate racism, antisemitism and authoritarian political power.

Asking students to identify both the decision-makers and those affected can help them understand why authority and coercion were a key feature of the eugenics movement.

Social pressure is still an influence in current genetic screening. Contemporary reproductive decision-making requires informed consent. For this to occur, an individual needs accurate information, understanding of alternatives, freedom from coercion and respect for personal values. A decision can be legally voluntary while still being influenced by expectations about what a “healthy” or “normal” child should be.

Encourage students to consider autonomy, dignity, equality, informed consent, disability rights and critical evaluation of scientific claims.

Throughout the lesson, avoid asking students to decide whether particular people with disabilities or genetic conditions should have been born. A formal pro-life vs pro-choice debate may shift attention away from genetics and encourage students to defend personal identities or beliefs.

Instead, this lesson uses an ethical inquiry. For example:

“Imagine a couple receives genetic information during pregnancy. What factors might they need to consider before making a decision?”

Students might identify:

• the nature and severity of the condition.
• uncertainty in the test result.
• available medical treatment.
• disability support.
• quality-of-life considerations.
• the parents’ values and circumstances.
• advice from medical professionals.
• reproductive autonomy.
• possible social pressure.
• legal considerations.

The discussion can then lead to "Which of these questions can genetics answer, and which require ethical or personal judgement?”

This keeps the focus on systems, ideas, evidence, choices and power. The central message is that human biological variation can be studied scientifically, but deciding how society should respond to that variation involves ethical and social questions. The history of eugenics reminds us that scientific authority must be accompanied by critical thinking, humility, respect for human diversity and protection of individual rights.

References

Roberts, W. C. (2020). Facts and ideas from anywhere. Baylor University Medical Center Proceedings, 1–5. https://doi.org/10.1080/08998280.2020.1811835

The ethical issues used in this teaching sequence were designed to allow students to select particular positions and to consider the evidence and arguments that support those positions.

The initial classroom discussion allows critical thinking to be modelled before students move to the role-play in the Communicate routine.

During classroom discussion, the role of the teacher is to:

• encourage talking and listening.
• encourage students to justify their comments with evidence.
• help students construct arguments to justify or refute decisions.
• model evaluating arguments and evidence.
• encourage reflecting on the argument process (mind change).

Students often have difficulty either making a decision or using evidence to justify their decision. Support can be provided by guiding students to first identify each of the stakeholders involved. This allows the students to identify an individual stakeholder when discussing the short- and long-term risks and benefits, instead of using their own perspective.

Bioethical principles can assist in decision-making about genetic testing. The bioethical principles that can be used in this lesson include:

• autonomy: the personal free will and right to choose or consent.
• beneficence: maximising the benefit for self and others.
• non-maleficence: minimising the harm to all involved.
• justice: fairness and equity of access and choice.

In the early 20th century, eugenic ideas were particularly prominent among academics, medical professionals, educators, and government officials in Melbourne, who saw eugenics as a modern scientific approach to addressing social issues.

A key figure in the movement was Richard Berry, Professor of Anatomy at the University of Melbourne from 1906 to 1929. Berry and his supporters promoted the belief that traits such as intelligence, morality, and social behaviour were largely inherited. They argued that people considered “mentally deficient” or socially undesirable should be prevented from reproducing.

Eugenic ideas influenced public policy in Victoria. Between 1926 and 1939, several Mental Deficiency Bills were introduced into the Victorian Parliament. These proposed the institutionalisation and possible sterilisation of people classified as “unfit”, including those with intellectual disabilities, people living in poverty, alcoholics, and other groups who were viewed through the lens of eugenic theory. First Nation peoples were also frequently included in these discriminatory classifications. Although one bill was passed in 1939, it was never enacted, partly due to the outbreak of World War II and growing awareness of the atrocities associated with Nazi racial policies.

Modern eugenics

Although organised eugenics movements declined after World War II, some eugenic practices, including involuntary sterilisation, institutionalisation, and discrimination against people with disabilities, continued in various countries (including America) into the 1970s and, in some cases, beyond. Advances in genetics and reproductive technologies have prompted renewed ethical discussions about what some scholars call “modern eugenics”. Developments such as prenatal genetic screening, embryo testing and reproductive technologies can provide valuable information to prospective parents and help identify serious genetic conditions. However, some ethicists and disability advocates have expressed concern that widespread use of these technologies could create social pressure to avoid the birth of individuals with certain genetic traits or disabilities. New techniques that estimate the likelihood of complex traits and conditions have also raised questions about whether selecting embryos based on genetic characteristics could resemble historical eugenic goals of shaping future populations. While modern genetic counselling emphasises informed choice and individual autonomy rather than state control, debates continue about the ethical implications of using genetic information in reproductive decision-making and how society can balance medical advances with respect for diversity, disability rights, and human dignity.

References

Jones, R. L. (2011, September 20). Eugenics in Australia: The secret of Melbourne’s elite. The Conversation. https://theconversation.com/eugenics-in-australia-the-secret-of-melbournes-elite-3350

In the optional cystic fibrosis dilemma, students role-play a genetic counsellor who guides the parents (Mr and Mrs C) through the decision-making process where Mr C is determined not to be the genetic parent of the unborn child.

From previous lessons, students will be aware of the inheritance pattern (autosomal recessive), diagnosis (through predictive carrier screening or genetic testing at birth), symptoms (chronic chest infections, digestive problems, infertility and reduced life span) and treatment (lifelong treatment).

Encourage students to consider the needs, rights and responsibilities of not only the parents (Mr and Mrs C) but also the baby who has cystic fibrosis, the potential genetic father, other family, medical staff, and genetics counsellor.

Constructing an argument encourages students to make the processes visible as they make their decision, justify the decision with their peers, become aware of different views within their group and whole class, and have the option of changing their mind.

The dilemma has been trialled with Year 10 students in many contexts, including Catholic schools where the purpose of testing is to prepare for the birth of the child. Initially, some students may focus on the morality or not of Mrs C, whose paternity is not in doubt. Through questioning, the focus can shift to the needs of the baby.

In reinforcing the autosomal recessive inheritance, some students will propose that perhaps Mr C had a spontaneous mutation in his otherwise normal allele or that there is an error in the testing. Mr C may be aware that he is not the biological father. From the genetic counsellor’s perspective, the parents have attended to see if their baby has cystic fibrosis, and that is the information that would be provided to Mr and Mrs C. The debrief stage at the conclusion is very important as students may hold strong opposing views.

Artificial intelligence tools can provide support in developing assessment rubrics, however, the quality of the output depends heavily on the clarity of the prompt, the inclusion of curriculum standards, and the specificity of the assessment criteria provided. The draft rubric produced will need to be carefully checked for clarity, coherence, and class-appropriate content. AI cannot replace professional judgement; rather, it assists when it is used strategically.

1. Start with the standard, not the tool

Effective rubric design begins with curriculum alignment. Before using a Generative AI tool, identify the following criteria:

• the relevant achievement standard.
• the content descriptors being assessed.
• the cognitive demand (e.g. explain, analyse, evaluate, construct).

Providing the achievement standard directly within the prompt ensures that the Generative AI tool anchors the rubric to expected student performance. For example, including wording such as: “Students explain the processes that underpin heredity and genetic diversity…” directs the Generative AI tool to align descriptors to the required depth of knowledge and skill.

Without this anchor, Generative AI tools may generate generic criteria that lack alignment to reporting requirements.

2. Specify the assessment components clearly

Generative AI tools perform best when the task requirements are explicitly broken down. Instead of asking “Write a rubric for a genetic testing brochure”, a more effective prompt would include:

• the science concepts required.
• the skills students must demonstrate (data analysis, calculation, argument construction).
• the design or application component.
• the communication expectations.

Breaking the assessment into categories (e.g. science understanding, design, communication) produces a rubric that reflects the multidimensional nature of authentic tasks.

3. Define performance levels explicitly

To generate meaningful performance bands (e.g. Well Below Standard to Well Above Standard), the prompt should:

• provide the wording for “At Standard”.
• clarify what progression should look like (increasing complexity, accuracy, independence, evaluation).

Generative AI tools can then scale descriptors logically:

• Below Standard → partial understanding, limited analysis.
• At Standard → accurate application, appropriate analysis.
• Above Standard → detailed reasoning, evaluation, integration.
• Well Above Standard → sophisticated, critical, and reflective reasoning.

Without this structure, descriptors may become repetitive rather than developmental.

4. Use cognitive verbs intentionally

Assessment criteria should reflect increasing cognitive demand. Guide Generative AI tools by incorporating verbs such as define, describe, explain, etc.

This ensures that higher performance levels demonstrate deeper reasoning rather than simply “more detail”.

5. Prompt for evidence-based language

AI-generated rubrics are stronger when prompts require:

• evidence-based reasoning.
• identification of assumptions.
• consideration of conflicting evidence.
• data analysis and anomaly identification.

These elements align with upper-primary and secondary achievement standards and promote higher-order thinking.

6. Maintain professional judgement

AI-generated rubrics should always be reviewed and refined. Consider the accessibility of the language, the appropriateness of the context, and its ability to separate students’ grades appropriately. Generative AI drafts accelerate the process, but professional expertise ensures validity. If the first attempt is not appropriate for the class, readdress the prompt and try again.

Example of a strong generative AI prompt template

Write an Australian Year [year/level] assessment rubric for a task where students will [outline the task e.g. create a brochure that provides the background information on cystic fibrosis required before genetic testing].

Align the rubric to the following achievement standard:

[Paste the full Science Understanding standard]

The task requires students to: [outline all the Science as a Human Endeavour and Science Inquiry criteria required]

Organise the rubric into the following categories: [outline the key elements of the design e.g. DNA chromosomes and genes, random assortment during meiosis, using a Punnett square to demonstrate the inheritance of cystic fibrosis, difference between probability and outcome, why genetic counselling is important, the design, communication for appropriate audience.]

Include five performance levels in columns: Well Below Standard, Below Standard, At Standard, Above Standard, Well Above Standard.

“At Standard” must align directly to the achievement standard.

Ensure progression across levels reflects increasing depth of analysis, use of evidence, and critical thinking.

Include references to assumptions, data analysis, and evidence-based reasoning where appropriate.

References

Commonwealth of Australia. (2023). Australian framework for generative artificial intelligence in schools. Commonwealth of Australia. <https://www.education.gov.au/schooling/resources/australian-framework-generative-artificial-intelligence-ai-schools>