영어 모의고사 (자동 편성)

As technology continues to reshape the job market, educators and employers increasingly agree on which skills ①will matter most in the coming decades. Technical literacy, including basic coding and data analysis, has ②became nearly as fundamental as reading and writing once were. Beyond technical knowledge, however, employers consistently rank problem-solving and adaptability among the most valuable qualities in job candidates. Workers who can quickly learn new tools and adjust to unfamiliar situations tend ③to remain employable even as entire industries transform. Communication skills also matter more than ever, since many future jobs will require ④collaborating with both human colleagues and intelligent systems. Schools have begun redesigning curricula to emphasize these competencies, ⑤moving away from memorization toward project-based learning.

A smart thermostat that learns a family's daily rhythm can lower the temperature automatically before everyone wakes up cold, while smart lights ①that follow a resident's schedule no longer need to be switched on and off by hand. These small conveniences rest on a shared foundation: sensors collect data about temperature, motion, and light throughout the home, and an algorithm gradually learns ②which settings match each household's actual habits rather than a factory default. Over months of use, the system becomes noticeably better at ③anticipate needs, often adjusting settings moments before a resident would have reached for a switch. Yet convenience comes with a trade-off that many households ④overlook. Every one of these small adjustments depends on constant data collection, meaning that a detailed record of when people wake, leave, and return home is quietly ⑤being stored somewhere beyond their immediate control.

Blue, for instance, is frequently used by financial and technology companies because it tends to evoke feelings of ①trust and stability. Green typically signals ②freshness or environmental responsibility, making it a popular choice for organic food brands. Despite these general patterns, cultural context matters significantly, since a color that suggests luck in one country might suggest ③mourning in another. Marketers who ④ignore these cultural differences risk sending ⑤intended messages to international audiences. For this reason, companies expanding into new markets often conduct extensive research before finalizing a logo's color scheme.

For most of last year, Junho refreshed his social media feed constantly, ①terrified of missing a party, a trending meme, or gossip among his friends. This restless anxiety, often called FOMO, or the fear of missing out, left him ②relaxed and strangely unsatisfied even after hours of scrolling. One weekend, his phone battery died during a hiking trip, and, to his surprise, he actually ③enjoyed the quiet afternoon without notifications interrupting his thoughts. Curious about this ④unexpected calm, Junho began deleting social apps for a few hours each day. This shift in attitude reflects what psychologists now call JOMO, a mindset that treats disconnection as ⑤freedom rather than loss.

Instead of typing keywords into a search bar, a growing number of people now simply upload a photo and let an algorithm figure out what it contains. This process, known as reverse image search, compares the visual patterns in a picture against a massive database, identifying everything from a landmark in the background to the exact model of a pair of sneakers. Shoppers use it to find where an item seen on the street can be purchased, while students use it to ①identify plants, insects, or historical artworks in seconds. The system works by breaking an image down into countless small features, such as edges, colors, and shapes, then matching that pattern against millions of stored examples. It is ②flawless, however; a ③blurry photo, an unusual camera angle, or an object partly hidden behind another can easily ④confuse the algorithm, leading to search results that have ⑤nothing to do with the original picture at all.

When Daniel was a child, he dreamed of becoming an astronaut, yet he assumed such careers belonged only to a handful of government scientists. During an internship, he helped design a small satellite intended to monitor crop health from orbit, a project that combined engineering with agricultural science. He realized that ___________. After graduation, Daniel joined a startup developing lunar landing equipment, a job that barely existed when he first imagined his future career.

The rapid rise of the gig economy has led researchers to examine both its opportunities and its risks. (A) In addition, because their income depends heavily on the number of tasks completed, many gig workers find it difficult to save money consistently. (B) On the positive side, gig platforms allow workers to set their own schedules and take on projects that match their skills. (C) Yet this freedom comes at a price, since most gig workers are not entitled to employer-provided benefits like health insurance.

Telemedicine has sparked debate among healthcare professionals about its proper role in modern medicine. (A) Critics counter that virtual visits cannot fully substitute for physical examinations, which remain essential for diagnosing certain conditions accurately. (B) Most experts, weighing both sides, conclude that telemedicine works best as a complement to, rather than a replacement for, traditional care. (C) Supporters point out that virtual visits save time and extend healthcare access to patients living far from hospitals.

Across many countries, high schools begin classes early in the morning, often before eight o'clock. (A) Researchers who study this mismatch argue that the underlying problem is not laziness or poor discipline among students, but a scheduling system built around adult rhythms rather than adolescent ones. (B) This schedule assumes that teenagers can simply go to bed earlier to compensate, but biology tells a different story, because the body's internal clock shifts later during adolescence, delaying the release of melatonin until well after ten at night. (C) As a result, most teenagers are not physiologically ready to fall asleep until much later than adults, and when early start times force them to wake before completing a full sleep cycle, the mismatch accumulates into a chronic sleep debt.

This is precisely what makes the condition so difficult to catch before it becomes severe. Ambitious young athletes and the parents who support them sometimes assume that more training automatically produces better results, a belief that occasionally leads to a condition known as overtraining syndrome. ( ① ) Unlike ordinary fatigue that resolves after a few days of rest, overtraining syndrome develops gradually over weeks or months of insufficient recovery relative to training load, eventually producing persistent exhaustion, declining performance despite continued hard work, and increased susceptibility to illness and injury. ( ② ) Adolescents may be especially vulnerable, since their bodies are simultaneously coping with the physical demands of growth and the added stress of intensive training schedules. ( ③ ) Warning signs are often subtle at first, including disrupted sleep, irritability, and a loss of enthusiasm for a sport the athlete once genuinely enjoyed, which adults often mistake for ordinary moodiness. ( ④ ) Recovery from full-blown overtraining syndrome can take months rather than days. ( ⑤ )