영어 모의고사 (자동 편성)

Minji had tried for years ①building a bedtime reading habit but always forgot once under the blanket. During summer, she found a method called habit stacking. It means ②attaching a new habit to an existing one so it acts as a reminder. Her existing habit was brushing her teeth every night, so she decided ③to place her book beside her toothbrush. After brushing her teeth, she would pick up the book, ④letting one action trigger the next. Encouraged by this success, Minji stacked another habit onto her morning routine, ⑤reviewing vocabulary words after making her bed.

Fast fashion refers to cheap, trendy clothing ①**produced** quickly and replaced almost as fast as it is bought. Because these garments are ②**designed** to be worn only a few times, huge amounts of fabric end up in landfills every year, and the dyeing process pollutes rivers near factories. In contrast, a growing number of brands are turning toward the circular economy, an economic model in which materials are ③**reused**, repaired, or recycled instead of being thrown away after a single use. For example, some companies collect old clothes, break down the fibers, and weave them into new fabric, while others let customers ④**to rent** outfits for special occasions rather than buying garments they will barely wear. These approaches keep resources ⑤**circulating** within the system longer, reducing demand for raw materials. Therefore, shifting from a throwaway habit toward a circular one may be essential for making the fashion industry sustainable.

When choosing a future career, students often face a common question: should I follow what I love, or what I am good at? Passion can provide strong ①motivation, pushing a person to practice for hours without feeling tired. However, loving an activity does not always mean a person will become ②unskilled at it professionally. On the other hand, natural talent can lead to quick success, but without genuine interest, that success may eventually feel ③empty or exhausting. Career experts suggest looking for an ④overlap between the two instead of choosing only one side. Finding this balance takes time and self-reflection, but it often leads to a more ⑤satisfying and sustainable career.

Devices that translate brain activity directly into digital commands have moved from laboratory experiments to real medical use, allowing paralyzed patients to control a robotic arm or type a message using thought alone. As the technology ① improves, some developers envision a future in which brain-computer interfaces extend beyond restoring lost function toward enhancing healthy minds. This prospect raises a philosophical question that medicine alone cannot answer: if a device can alter memory, mood, or decision-making, at what point does the assistance stop being a tool and start ② reshaping the very identity of the person using it. Neuroethicists argue that mental privacy, the ability to keep one's own thoughts ③ exposed to external access or manipulation, may need to be recognized as a fundamental right before this technology becomes ④ widespread. This concern is likely to grow ⑤ more urgent as the devices become more powerful.

When people recall precisely where they were and what they were doing at the moment they learned of some momentous public event, the resulting memory often feels extraordinarily vivid, as though it had been etched into the mind with photographic precision; researchers have termed such recollections flashbulb memories. (A) Proponents of this concept once argued that the emotional intensity and surprise accompanying such events trigger a distinct neural mechanism that preserves details with unusual fidelity, effectively exempting them from the gradual decay that afflicts ordinary memories. (B) This persistent mismatch between subjective certainty and objective consistency implies that flashbulb memories, far from being flawless recordings, are reconstructed narratives shaped by rehearsal, media exposure, and the passage of time. (C) Subsequent longitudinal studies, however, have complicated this picture considerably: when researchers compared accounts gathered within days of an event to accounts gathered years later, they discovered that details had frequently been altered, omitted, or even fabricated, even though the individuals reporting them expressed unwavering confidence in their accuracy.

When people face a difficult decision, they often weigh not only the expected outcome of each option but also how painful it would feel to discover later that a different choice had been better. (A) Researchers have found that people feel sharper regret over losses that resulted from taking action than over identical losses that resulted from doing nothing. (B) Investors, for example, sometimes continue holding a declining stock rather than selling it, because selling would force them to confront the possibility of having made a clear mistake. (C) This helps explain why so many individuals default to inaction whenever a decision feels uncertain, even when remaining passive is not actually the safer choice.

New jobs related to technology are appearing in many different fields. (A) In the field of energy, technicians now install and repair solar panels and wind turbines. (B) In healthcare, meanwhile, specialists design digital tools that help elderly patients manage their health. (C) In the world of data, analysts help companies make sense of huge amounts of information.

As artificial intelligence becomes more advanced, questions naturally arise about which human skills will remain irreplaceable. (A) A machine can recommend a treatment plan based on statistics, for example, but it cannot comfort a frightened patient the way a compassionate nurse can. (B) For this reason, educators are placing growing emphasis on skills such as collaboration, critical thinking, and emotional intelligence. (C) Research suggests that AI still struggles with tasks requiring genuine empathy, ethical judgment, and creative problem-solving in unfamiliar situations.

주어진 문장: Back then, few people could have predicted that such a job would even exist. When Mina graduated from college five years ago, she had never even heard the term "data scientist." ( ① ) She had studied statistics simply because she enjoyed solving puzzles with numbers. ( ② ) Everything changed when a small tech startup, which was building an app to predict traffic patterns, hired her to analyze massive amounts of data. ( ③ ) Mina quickly discovered that she loved turning raw numbers into insights that helped real people make better decisions. ( ④ ) Within two years, demand for professionals like her had exploded, as companies in every industry realized how valuable data could be. ( ⑤ ) Today, Mina leads a team of ten analysts, mentoring young graduates.

The software company, in turn, may argue that no algorithm can be expected to be perfect. Hospitals are increasingly adopting artificial intelligence tools that can scan medical images and flag potential tumors faster than experienced radiologists. ( ① ) When an AI system misses a diagnosis that a human doctor would likely have caught, responsibility becomes difficult to assign. ( ② ) The doctor may argue that they simply trusted a tool the hospital required them to use. ( ③ ) The hospital, meanwhile, may argue that the software company guaranteed its accuracy. ( ④ ) Until legal systems clarify this chain of responsibility, patients harmed by an algorithmic error may find themselves with no clear party to hold accountable. ( ⑤ )