영어 모의고사 (자동 편성)

When Mina was a freshman, she often ①spent her allowance within a few days. Her older cousin told her about the marshmallow experiment, a famous study ②in which children could eat one marshmallow immediately or wait for two. Researchers found that children who waited longer ③shown better academic performance and self-control years later. Inspired by the study, Mina began ④saving half of her allowance each week instead of spending it all on snacks. After three months, however, she had saved enough to buy a bicycle she had ⑤wanted for over a year.

Carbon neutrality refers to a state in which the amount of greenhouse gases a country or company releases into the atmosphere ①is balanced by the amount it removes, resulting in zero net emissions. Achieving this goal typically requires several sequential stages rather than a single sudden action. First, organizations attempt to reduce emissions directly ②by replacing fossil fuels with renewable energy sources such as solar or wind power. Next, they improve efficiency throughout their operations, ③minimizing the energy wasted during production and transportation. Only after these direct measures have been maximized do most organizations turn to offsetting, ④which involve funding projects like reforestation or carbon capture to compensate for emissions that cannot yet be eliminated. Critics argue, however, that some companies exploit offsetting too early, ⑤using it to avoid making genuine reductions. Therefore, experts insist that a credible roadmap must always prioritize actual emission cuts before relying on compensation.

Many students ①take a career aptitude test at some point in high school. This test, ②which is designed to measure a person's interests and strengths, does not simply tell students which job to choose. Instead, it helps them understand themselves better. For example, a student ③who enjoy solving problems might discover a hidden interest in engineering. However, the results should ④be used only as a guide, not as a final answer. Therefore, students should treat the test as a useful starting point for ⑤exploring various career paths, rather than a fixed decision.

A hamburger patty need not come from a slaughtered animal at all if a small sample of muscle cells can be ①discouraged to multiply inside a steel tank. Cultured meat begins with a biopsy of animal muscle tissue, from which scientists isolate cells capable of dividing repeatedly, then feed those cells a nutrient broth that supplies the sugars, proteins, and minerals an animal's bloodstream would ②normally provide. Inside a bioreactor, the cells multiply across scaffolding designed to encourage them to align into fibers, ③gradually thickening into something that begins to resemble muscle tissue rather than a shapeless clump of cells. Supporters argue that because the process never requires raising and slaughtering a whole animal, it could shrink the land, water, and greenhouse gas emissions ④associated with conventional meat production. Skeptics counter that producing the specialized broth at a large enough scale remains prohibitively ⑤expensive, meaning cultured meat is unlikely to compete with conventional meat in price until the technology matures considerably further.

Generative AI systems learn to write, draw, and compose by studying ①enormous collections of existing human work, much of which was created without the artists' knowledge or consent. Supporters of the technology argue that this process resembles how a human student learns by studying the masters, ②absorbing style and technique rather than copying specific pieces. Critics respond that the comparison ③holds up perfectly at scale, since a single AI model can absorb millions of works in days. Courts around the world are now being asked to decide whether training an algorithm on copyrighted material counts as fair use or as ④infringement. Until clearer rules emerge, artists, developers, and publishers remain locked in a legal ⑤gray zone that satisfies almost no one.

As companies collect enormous amounts of personal data to improve their products and target advertisements, serious ethical questions have emerged about how that information should be handled. Employees who work with big data now face ①minimal responsibilities that previous generations rarely encountered, since a single careless decision can expose millions of people's private information. Some argue that strict regulations should govern data collection, even if such rules ②slow innovation and increase costs for businesses. Others insist that self-regulation within companies, guided by clear ethical training, can protect consumers just as ③effectively without stifling progress. Most experts agree that professionals handling sensitive data must be trained not only in technical skills but also in ethical ④decision-making. Universities have begun adding data ethics courses, recognizing that future employees will need to ⑤balance innovation with responsibility.

The twenty-hour rule proposes that years of practice are not needed to become skilled at a new activity. Only about twenty hours of effort are needed to reach a useful level. Unlike theories claiming true mastery requires ten thousand hours, this rule targets a more modest goal. That goal is simple competence for everyday use. According to supporters, ___________, since a beginner has room to grow. Someone learning guitar can typically strum simple chords and follow a basic song within twenty hours of daily practice. Likewise, a language learner may soon order food or ask directions without years of formal study. Advocates emphasize that the twenty hours must be deliberate and focused, broken into short daily sessions rather than one long stretch. The hours should be aimed at fixing weaknesses rather than repeating what one already knows.

Many people believe that building a new habit requires strong willpower or motivation. However, psychologist BJ Fogg argues that habits form more easily when a behavior itself becomes simple to perform. His theory, called the Fogg Behavior Model, states that ___________. When motivation is low, the task must be made extremely easy, or it will not happen at all. For instance, a person who wants to exercise daily succeeds more often by committing to one push-up than to a long workout. Fogg calls this idea the law of least effort, since people naturally choose the option requiring the least energy. A student who wants to read more might leave a book open on the desk rather than setting a vague goal. By lowering the required effort, people reduce the ability barrier and make steady action far more achievable.

Attention, students! Our school festival is going green this year, and we truly need your help. This event aims to reduce the disposable waste that usually piles up during the celebration. (A) First, please bring your own cup, plate, and utensils to every food booth you visit. Second, each booth should use reusable decorations rather than paper banners that get thrown away within hours. (B) If your booth needs supplies, please contact the student council office before Friday. Let us work together to create a festival that is both fun and eco-friendly. (C) Students who join as Green Helpers will manage the recycling stations, sorting cans, bottles, and paper carefully all day long. Therefore, everyone's small cooperation will directly lower the amount of trash sent to the landfill. However, single-use plastic bags are strictly prohibited at every booth this year.

Instead, these trainers help workers use AI tools wisely, without becoming fully dependent on them. As artificial intelligence becomes part of everyday life, entirely new job titles are appearing in the workplace. ( ① ) Prompt engineers, for instance, design effective instructions that help AI programs produce accurate and useful results. ( ② ) AI ethics officers examine whether a company's technology treats users fairly and avoids harmful bias. ( ③ ) Meanwhile, human-AI collaboration trainers do not simply teach employees to use every new AI feature available. ( ④ ) These jobs did not exist even ten years ago, yet they are growing quickly across many industries. ( ⑤ ) This suggests that success in an AI-driven future will depend more on uniquely human skills.