영어 모의고사 (자동 편성)

Across many countries, high schools ①begins classes early in the morning, often before eight o'clock. This schedule assumes that teenagers can simply go to bed earlier to compensate, but biology tells a different story. During adolescence, the body's internal clock shifts later, ②delaying the release of melatonin until well after ten at night. As a result, most teenagers are not physiologically ready to fall asleep until much later than younger children or adults. When early start times force them ③to wake before their bodies have completed a full sleep cycle, the mismatch accumulates into a chronic sleep debt ④that affects concentration and mood throughout the school day. Researchers who study this mismatch argue that the underlying problem is not laziness or poor discipline among students, but a scheduling system ⑤built around adult rhythms rather than adolescent ones.

Smart speakers have quietly become a fixture in many households, ①responding to spoken requests for weather updates, music, or kitchen timers. Behind this simple exchange lies a complex process: the device converts sound waves into text, interprets the meaning using language models, and then generates a spoken reply, all within a second or two. Because these assistants improve by ②learning from millions of interactions, they gradually become better at recognizing regional accents and casual phrasing that once confused them. Still, the technology remains far from perfect. Background noise, overlapping voices, or an unusual sentence structure can cause the assistant ③misunderstanding a simple request, sometimes with amusing results. Engineers continue to refine these systems, but many admit that truly natural conversation, the kind ④that flows without repeated commands or awkward pauses, ⑤remains one of the hardest goals in the entire field of artificial intelligence.

Climate scientists frequently warn about tipping points, thresholds beyond which a small additional change ①triggers a large, often irreversible shift in the climate system. Unlike gradual warming, which unfolds steadily over decades, crossing a tipping point can produce dramatic consequences within a short period. For instance, as Arctic ice melts, it exposes darker ocean water that ②absorb more sunlight than reflective ice, accelerating further melting in a self-reinforcing cycle. Similarly, scientists worry that a major ocean current, which currently ③redistributes heat across the planet, could slow dramatically if enough freshwater from melting glaciers dilutes the surrounding seawater. Once such thresholds are crossed, ④restoring the original balance may become nearly impossible, even if emissions are later reduced. Therefore, researchers argue that preventing these transitions ⑤matters more than merely slowing average temperature increases.

Many companies now advertise themselves as environmentally responsible, yet a growing number of these claims turn out to be ①misleading. This practice, known as greenwashing, occurs when a business spends more effort marketing its products as eco-friendly than actually reducing environmental harm. A company might launch a recycled-packaging line while continuing to pollute rivers through its main factories, creating a false impression of genuine change. Such tactics ②deceive well-intentioned consumers who wish to shop responsibly but lack the tools to ③verify corporate claims. In contrast, truly sustainable businesses publish detailed, independently verified data about their emissions and supply chains, allowing outsiders to check their progress. Therefore, shoppers should look beyond vague labels like green or natural and instead search for ④recognized certifications, transparent reports, and measurable targets. Without such scrutiny, greenwashing will keep ⑤declining, undermining public trust and slowing the broader shift toward an economy that truly protects the planet.

A small riverside village had ①endured severe flooding almost every summer, watching helplessly as rising water damaged homes and destroyed crops year after year. Frustrated residents eventually decided to pursue climate adaptation, adjusting their infrastructure and habits to reduce the damage caused by increasingly unpredictable weather. Engineers widened the drainage canals surrounding the village, allowing excess rainwater to flow away more efficiently instead of pooling in low-lying streets. Meanwhile, several families whose houses stood in the most ②vulnerable areas relocated to higher ground, even though leaving their long-time homes was emotionally difficult. The village also installed an early warning system that sent alerts to residents' phones whenever river levels rose dangerously fast. When a powerful storm struck three years later, the new measures proved ③useless, and the village suffered only minor damage instead of the ④devastating losses it had previously faced. Their ⑤resilience became a model for neighboring communities.

A growing number of health apps now track steps, sleep, and heart rate throughout the day, quietly building a detailed picture of a user's physical condition without requiring a single visit to a doctor's office. By comparing this stream of data against patterns drawn from millions of other users, the app's algorithm can ①flag early warning signs, such as an irregular heartbeat, long before the person experiencing it would have noticed anything unusual on their own. For people living far from specialists or unable to afford frequent checkups, this kind of constant monitoring can feel like a genuine ②safety net. Doctors caution, however, that these apps are designed to ③diagnose illness, not merely to detect patterns, and that a worried user should always confirm any alarming reading with a professional rather than trusting an app's suggestion alone. Treating a wellness app as a ④substitute for medical expertise, they warn, can be just as risky as ⑤ignoring a warning altogether.

Imagine two factories making the same product: one in a country with strict carbon rules, and one in a country with almost none. The factory facing stricter rules often spends more, which can make its goods pricier than those made elsewhere. To fix this imbalance, some governments have introduced the carbon border adjustment mechanism, a policy charging imported goods a fee based on how much carbon was released while producing them. Supporters argue that the system _______________. However, critics claim it unfairly burdens developing countries, which often lack money to modernize factories quickly. For example, a small exporter in a poorer nation might struggle to pay the added charge, though it contributes little to global emissions. Still, if wealthier nations pair the policy with technical support, it could become a genuinely fair tool for cutting emissions worldwide.

Long before a user finishes typing a sentence, the keyboard on most smartphones has already begun guessing what word comes next. This feature relies on a language model trained to notice which words commonly follow one another, so it can offer a shortlist of likely candidates, saving users countless keystrokes over the course of a day. This constant personalization, however, creates a subtle side effect that few users notice: some linguists worry that _______________.

After a viewer finishes an episode, a streaming service rarely leaves the choice of what to watch next entirely up to chance. (A) The system is not without drawbacks, however, since favoring titles similar to what a viewer already enjoys can quietly narrow someone's exposure to unfamiliar genres, directors, or cultures. (B) Instead, a recommendation algorithm compares that viewer's habits with patterns drawn from millions of other users, then ranks thousands of titles in order of predicted interest. (C) This approach keeps viewers engaged far longer than a simple list of new releases ever could, which is precisely why streaming companies invest so heavily in refining it.

A joke that depends on wordplay in one language, for example, may become confusing or even meaningless once it is translated literally into another. Only a decade ago, translation apps produced sentences so awkward that users often laughed at the results rather than trusting them. ( ① ) Today, many of these apps rely on neural networks that analyze entire sentences at once, capturing context instead of translating word by word. ( ② ) This shift has made everyday tasks such as reading a foreign menu or chatting with an overseas friend remarkably smooth. ( ③ ) Frequent travelers now point their phone cameras at street signs and receive an instant translation overlaid on the screen. ( ④ ) Even so, the technology still struggles with humor, sarcasm, and cultural nuance, areas where a single wrong word can completely change the intended meaning. ( ⑤ ) For this reason, professional translators argue that these apps are best treated as a helpful starting point rather than a final, polished result.