Why study maths? When Will I Ever Use This?

🎓 Student Experience?

The maths that we learn in high school often doesn’t appeal to people, and often students feel that it is “dry” and “boring”. Research consistently shows that students are dissatisfied with mathematics in the classroom. Many students, regardless of their ability, view the subject as dull and irrelevant to their lives and future aspirations.

This feeling is exacerbated by the high stakes and high pressure of exams, as well as the dreaded entrance systems, such as the ATAR (Australian Tertiary Admissions Rank). If we examine the enrolments in Maths in the NSW HSC, we can see that the proportion of students taking Calculus-based (Maths Adv, Maths Ext 1, Maths Ext 2) courses has been trending downward over the last five years (2019-2024). Overall, the number of students taking maths has remained stable (around 65,400).

As shown overall the trend has been to do less Calculus based maths (higher levels of maths)

The motivation to learn maths comes from two factors:

• Marks - Maths scales well, and so can assist students with ATARs
• Tertiary Studies - Many tertiary studies have minimum levels they don’t mandate, but recommend.

In this environment, subject choices can become less about intellectual curiosity or long-term development and more about short-term optimisation. Studies and university statistics show that a significant number of students select less challenging mathematics courses because they believe it is a safer route to maximising their ATAR or a way to manage a perceived heavy workload.

This strategy of short-term optimisation hides a significant long-term risk in the changing world. The choices made to secure a place at university can paradoxically undermine a student's ability to thrive once they are there. Students often report feeling underprepared for the rigorous cognitive demands of their tertiary studies. Students perceive subjects as isolated silos of information because the compelling story of why the learning matters is rarely told.

🧠 The Elasticity of the Brain

To truly understand the importance of mathematical studies, we must appreciate that the brain is malleable and adaptable. It likes to adapt and change over time. A brain that is active and engaged in critical thinking and inquisitive problem-solving will stay healthy and effective.

To truly understand the value of this challenging academic work, it is necessary to shift the perspective entirely. Viewing school subjects as mere collections of facts to be memorised is like walking into a gym and seeing only the equipment. It misses the entire point. The equipment itself is not the goal; the strength, endurance, and resilience it builds are.

Maths is a tool to teach your brain how to adapt to future challenges. Rather than seeing maths (and other STEM subjects) as facts, we need to see them as tools to build skills that are invaluable in the future (and more so now in a new environment).

A complex algebra problem is not just a bunch of x's and y's; it is a heavy cognitive lift for the logical reasoning muscles. The solution to the problem involves:

Understand and define problems: This translates to a real-world ability to clearly define problems before attempting to solve them.

Devise strategies: There are often multiple ways to approach a mathematical problem. Exploring different methods fosters flexibility in thinking and the ability to strategise effectively.

Implement and refine solutions: The process of working through a problem and checking the solution for accuracy and logic builds a methodical approach to task execution and quality control.

While we don’t think we use this skill in our day-to-day life, the study of maths and these subjects makes it second nature.

🪛 The Core Cognitive Toolkit: Beyond Subject Boundaries

Subjects are often thought as being in a silo, separate classrooms. The cognitive skills they cultivate are not bounded, instead they form an integrated learning environment. Your mental capabilities are a web.

We often think of skills as a technology tree, but the truth is our cognitive skills are a learning web.

Mathematics serves as the training ground for thought. It is where we learn the discipline of logical reasoning, analytical thinking, and complex problem-solving.

When a student works through a multi-step proof or models a real-world scenario with an equation, they are learning to deconstruct problems into manageable components, to work with abstract systems and within their rules, and to follow structured, logical pathways to a verifiable solution; which is how the modern world functions.

🖥️ The New Job Requirement: A Mind That Can Outthink a Machine

The Great Automation Shift

The future is here, AI is starting to affect the nature of work, just like the internet did in the 1990s. However, just as in that instance (and all others), jobs will still be available; the nature of those jobs will change. Those who can adapt to changes are the ones who will ultimately succeed.

Data from leading global institutions, such as the World Economic Forum and McKinsey, confirm that AI is already being deployed to perform sophisticated cognitive functions, including advanced data analysis, drafting legal documents, writing software code, and generating marketing content.

The Rise of "Human-in-the-Loop" Skills

The rise of AI does not render humans obsolete; rather, it enhances their capabilities and potential. Instead, it dramatically increases the value of a specific set of human capabilities. As AI systems become proficient at executing well-defined tasks and providing data-driven "answers," the economic and strategic premium shifts to the humans who can provide the context, judgment, and creativity that these systems lack. The future of work is not human versus machine, but human with machine.

The future of work means the skills students need will change. The skills needed are those that are uniquely human (for now) and the skills highlighted by the study of mathematics and sciences.

• Higher Cognitive Skills: While AI can process information, it struggles to structure an inquiry from scratch. AI handles the "what" (data analysis), the value shifts to the human who can determine the "why" and the "so what."
• Social and Emotional Skills: AI can analyse data, but it cannot inspire a team, negotiate a delicate compromise, or build a relationship of trust with a client. Skills such as leadership, communication, empathy, and collaboration are consistently cited as irreplaceable "power skills" that are essential for navigating the human elements of any organisation.
• Adaptability and Learning: Perhaps the most critical meta-skill in an era of constant technological disruption is the ability to learn, unlearn, and relearn. The rigorous process of mastering complex academic subjects builds more than just knowledge; it forges the habits of mind—discipline, persistence, and the confidence to tackle challenging new domains—that are the very foundation of adaptability.

The value proposition for human workers is shifting away from the ability to recall and process information and toward the ability to ask insightful questions. AI models can pass the legal exams or generate flawless code, which means the economic value of a human who can simply produce a correct answer to a known problem is diminishing.

The new premium is on the human capacity to formulate novel problems, structure complex inquiries, and critically evaluate the output of an AI.

🤖 AI vs. Human Intelligence in the Future of Work

The following table provides a clear summary of the complementary roles of AI and human intelligence in the modern workplace. It illustrates how AI acts as a tool for execution, while humans provide the essential strategic and creative direction.

📈 Your Education as a Strategic Investment

The conclusion we have come to at Intuition is that a rigorous education is a strategic investment in one's own cognitive capacity. The choices made during school years should not be viewed as a stressful series of hurdles to clear. Instead, each subject selection, each challenging assignment, and each moment of intellectual struggle should be seen as a conscious act of personal development—the deliberate construction of a mind that is flexible, powerful, and prepared for the future.

The more we think of education as an investment in the future, the better we, as a society, will be. Trade skills, such as those of electricians and plumbers, which are in huge demand, still require the skill set that math teaches us. The critical thinking and problem-solving skills that stem from mathematics and the sciences are foundational for the future of work, even in trades.

🧐 The Future-Proofing Mindset

Taking control of this cognitive development requires a shift in mindset. It starts now, in high school rather than after University. The following principles can serve as a guide for this process:

Choose Challenge over Comfort: Actively seek out the subjects, teachers, and problems that feel difficult. The feeling of "struggle" is not a sign of failure; it is the sensory feedback of cognitive growth.

Focus on the Process, Not Just the Grade: When a problem is answered incorrectly or an argument in an essay is weak, the most valuable learning opportunity arises. Instead of simply memorizing the correct answer for the test, deconstruct the thinking process that led to the error. Was it a calculation mistake, a logical flaw, or a misinterpretation of the evidence?

Build Your Cognitive Toolkit: View every subject as a different kind of tool for the mind. Mathematics provides the logical framework, essential for breaking down problems and reassembling them in a structured way. Literature and history provide the persuasive screwdriver and the critical lens, vital for constructing arguments and evaluating information.

Embrace Lifelong Learning: The single greatest certainty about the future is the necessity of continuous change. The world of AI demands constant adaptation, and the most valuable skill an individual can possess is the skill of learning new skills.

References

• The Science of Maths (2022)
• Development of Scientific Problem (2023)
• Reskilling and upskilling: Lifelong learning opportunities (2025)
• A new future of work: The race to deploy AI and raise skills in Europe and beyond - McKinsey (2025)
• Gen AI: A cognitive industrial revolution (2025)
• Historical content matters: a response to the critical thinking skills agenda (2025)