영어 모의고사 (자동 편성)

Every morning, our broadcasting club airs a short news program for the entire school. Last Tuesday, I was ①chosen to read the weather report for the very first time. My hands were ②shaking as the red light on the camera turned on. Halfway through my sentence, I suddenly forgot the next line completely. For a few seconds, only silence filled the studio, and I could hear my own heartbeat. My partner Minho, ③who was sitting beside me, quickly slid the script closer to me. I took a deep breath and calmly continued reading from where I ④had stopped. Somehow, my voice sounded steadier than I expected, and I ⑤finishing the report smoothly. After the broadcast ended, several classmates told me they had not even noticed the pause. That morning taught me that small mistakes rarely matter as much as we fear.

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.

City governments increasingly market dense networks of surveillance cameras as a straightforward safety upgrade, promising ①faster emergency response and lower crime rates. In many cases, the technology delivers exactly what it promises, helping investigators identify suspects within hours rather than weeks. Yet the same infrastructure that catches criminals also creates a ②permanent record of where ordinary, law-abiding citizens go about their daily lives. Once a camera network exists, its purpose can quietly ③shrink, from tracking traffic accidents to monitoring political protests, often without new public debate or explicit approval. Civil liberties groups argue that a city should decide how much surveillance it wants before the cameras go up, not years ④afterward when the infrastructure is already impossible to remove. Convenience installed today, in other words, can quietly become ⑤control tomorrow.

Artificial intelligence has begun to play a surprising role in creative industries once thought to be uniquely human. Some artists ①welcome this technology, using AI tools to explore new styles or overcome creative blocks that once took weeks to resolve. Others, however, argue that AI-generated art ②lacks the emotional depth that comes from genuine human experience. Despite this debate, most experts agree that AI is unlikely to fully ③replace artists anytime soon. Instead, it functions best as a collaborative tool, helping creators experiment ④faster while leaving final artistic decisions to humans. Therefore, artists who learn to work alongside AI may find themselves with a distinct ⑤disadvantage in this rapidly changing industry.

Turning off lights when you leave a room seems like a ①huge action, but it saves more energy than most people expect. Both actions seem ②harmless in the moment, but they add up to a ③serious waste over time. However, when an entire school forms this habit together, the total amount of saved energy becomes ④significant. Therefore, this small daily habit can create a surprisingly ⑤large positive effect for the whole planet.

When engineers design the software that controls a self-driving car, they inevitably face a question that philosophers have debated for ①decades. If a crash becomes unavoidable, should the vehicle protect its own passenger at all costs, or should it be programmed to ②minimize total harm, even if that means steering toward the person inside? Surveys reveal an uncomfortable ③contradiction: most people say a car should be programmed to save the greater number of lives, yet the same people admit they would never buy a vehicle designed to sacrifice its own owner. This gap between the ideal and the personal choice suggests that ethical programming cannot be settled by public opinion alone. Manufacturers, regulators, and philosophers must instead agree on ④transparent rules before autonomous vehicles are ⑤forbidden to make such decisions on the road.

During the sports day relay race, Jun was nervous, and his hands were shaking as he waited for the baton. When his turn came, he grabbed the baton but nearly dropped it while turning the first corner. His teammates, watching from the field, shouted his name and encouraged him to keep running. Even though Jun felt embarrassed, their cheering gave him confidence to focus on the runner ahead of him. As he handed the baton smoothly to the next runner, he realized that the team's effort mattered more than his mistake. After the race, his teammates gathered around him and said that his recovery had kept the team in the competition. Jun understood then that _______________. His class did not win first place, but they celebrated together as if they had.

Temporal discounting offers a useful lens for understanding why long-term goals so often lose out to short-term pleasures. (A) Consequently, replacing distant, abstract goals with smaller, immediate milestones can make future rewards feel psychologically closer and more motivating. (B) Research shows that people consistently prefer a smaller reward available today over a considerably larger reward promised weeks later. (C) This preference persists even when the delayed reward is clearly the more rational choice, revealing how strongly immediacy influences decision-making.

주어진 문장: This constant tracking allows algorithms to build a detailed profile of each user's interests over time. Internet activist Eli Pariser introduced the term filter bubble to describe a phenomenon created by online algorithms. Social media platforms and search engines constantly track which links users click and how long they linger on certain posts. ( ① ) Based on this data, algorithms predict what each individual is most likely to enjoy and quietly prioritize similar content in future results. ( ② ) As a result, two people who type the same search query can receive strikingly different results, each tailored to personal history. ( ③ ) This automatic filtering happens silently, without users ever deciding to limit what they see. ( ④ ) Consequently, many people gradually lose access to viewpoints that challenge their existing beliefs, even though they never intended to avoid them. ( ⑤ ) Pariser warned that this invisible curation could weaken democratic debate by narrowing public discussion. Therefore, some experts argue that platforms should reveal how content is filtered, letting users knowingly escape their own bubbles.

This reveals an uncomfortable truth about the underlying business model itself. Social media platforms rarely show users a neutral stream of information. ( ① ) Instead, recommendation algorithms are optimized to maximize engagement, and content that provokes strong emotion tends to hold attention longer than balanced reporting ever could. ( ② ) Researchers describe this as a distorted mirror: the platform reflects not society as it truly is, but a version shaped by whatever keeps people scrolling. ( ③ ) Some platforms have experimented with reducing the visibility of outrage-driven content. ( ④ ) Yet these experiments consistently saw user engagement drop. ( ⑤ )