Writing Part 2
Choose Your Task

Dear Editor,

I am writing in response to your invitation to describe a skill every young person should learn before adulthood, and for me the answer is unmistakable: managing money.

Very few schools teach this properly, and the gap shows. I remember opening my first bank account at eighteen with no real idea how interest, budgeting, or credit actually worked, and I made mistakes that took years to unravel. Nobody had ever sat me down and explained any of it in simple, practical terms. Watching my older sister struggle with debt taught me more about the subject than any lesson ever did, which says something troubling about how we prepare young people for adult life.

What makes this skill so essential is not simply avoiding debt, important as that is. Someone who understands money can make genuinely free choices: whether to take a lower-paid job they love, save for something meaningful, or simply sleep at night without financial worry hanging over them. Without that understanding, every other decision in adulthood becomes harder than it needs to be.

I am not suggesting complicated economics lessons. Even a single term covering budgeting, saving, and the basics of borrowing would transform how confidently young people step into independence.

I hope your readers will recognize how much difference this single, practical skill could make, and perhaps some will even push their own schools to take it seriously.

Yours faithfully,
A reader

Introduction

This proposal outlines two measures designed to reduce the stress students experience around examinations, a concern raised repeatedly in student feedback this year. Drawing on conversations with students across several year groups, it explains how each measure would ease pressure without lowering academic standards or adding to teachers’ workload.

A structured revision timetable

Many students arrive at exam season with no clear plan, cramming unevenly across subjects and losing sleep as a result, which in turn affects their performance in the exams themselves. I therefore recommend that the college provide a shared, subject-balanced revision timetable several weeks before exams begin, drawn up jointly by department heads. Giving students this structure would remove much of the anxiety that comes from simply not knowing where to start, while still leaving them free to adapt it to their own personal circumstances.

A quiet, drop-in study space

During exam weeks, the library becomes overcrowded and noisy at precisely the moment students need calm, and many are left with nowhere suitable to work between exams. Converting the currently underused music practice rooms into quiet, bookable study spaces would give students somewhere genuinely peaceful to prepare, particularly those who find revising at home difficult or share a bedroom with siblings.

Conclusion

Neither measure requires significant expense, yet together they would send a clear message that student wellbeing is taken seriously during the most demanding period of the academic year. I would strongly encourage the college to introduce both measures as soon as possible, ideally before the next examination period begins.

Introduction

The aim of this report is to assess how students currently use AI tools for coursework and to recommend two clear guidelines for their appropriate and responsible use going forward.

Current use

A brief survey of students across several subjects suggests that AI tools are now used almost universally, most commonly for generating essay outlines, checking grammar, and explaining difficult concepts that a textbook alone cannot clarify. Few students report using them to write entire assignments outright, though several admitted the temptation was strong under deadline pressure, particularly during exam term. Teachers, meanwhile, remain uncertain where reasonable assistance ends and academic dishonesty begins, and this uncertainty is causing genuine anxiety on both sides of the classroom.

Recommended guidelines

First, the college should publish a clear, subject-by-subject statement of what AI assistance is acceptable at each stage of an assignment, rather than relying on a single vague policy that attempts to cover every subject identically. Second, students should be required to briefly declare how they used any AI tool alongside their submission, treating this as a normal part of academic honesty rather than an admission of wrongdoing.

Conclusion

Clear, subject-specific guidelines would remove much of the current confusion, protect students from accidental misconduct, and allow teachers to focus their energy on assessing genuine understanding rather than policing technology they cannot fully see or control.

“Undercurrents”, a documentary podcast now in its second season, examines the growing crisis of plastic pollution in our oceans through the eyes of scientists, fishing communities, and the inventors trying to solve it. On paper it sounds like familiar environmental territory, yet the series handles its subject with unusual nuance and genuine curiosity.

What impressed me most was the decision to spend entire episodes with people who depend on the ocean for their livelihood, rather than treating them as background detail to the science. Listening to a fisherman describe nets returning full of fragments rather than fish is more affecting than any statistic, and the effect stays with you long after the episode ends. The production itself is understated too, letting silence and ambient sound do work that a lesser series would fill with dramatic music.

The podcast is not without flaws. A handful of technical episodes on chemical breakdown processes drag slightly, and newcomers may need to pause and look things up along the way. Even so, these are minor complaints against the series’ genuine achievements.

Above all, “Undercurrents” treats its subject as a shared human problem rather than a distant scientific one, and it trusts its audience to sit with uncomfortable detail rather than offering easy reassurance. I would recommend it without hesitation to anyone who assumes they already understand the scale of the problem.