2026年人教版中考英语专项复习中考拔尖-中欧美时事完形阅读专项

**基本信息** 聚焦中欧美时事热点，通过完形与阅读训练融合语言能力与跨文化思维，实现热点话题与语言知识的系统整合。 **专项设计** |模块|题量/典例|题型特征|知识逻辑| |----|-----------|----------|----------| |完形填空|8篇/120小题|语境词汇辨析与篇章逻辑理解|以AI教育、太空计算等热点为载体，构建"话题情境-词汇运用-逻辑推理"链条，培养语境分析能力| |阅读理解|12篇/60小题|时事话题细节与推理判断|围绕气候、科技合作等主题，形成"信息定位-深层理解-批判性思考"路径，提升跨文化理解与思维品质|

中考拔尖英语时事专项:中欧美热点完形与阅读 一、完形填空(共8篇,120小题) 阅读下面八篇短文,掌握其大意,然后从每题所给的A、B、C、D四个选项中选出最佳选项。 A. China: AI Education Beyond a New Tool At the 2026 World Digital Education Conference in Hangzhou, China launched a global AI education service platform. Many people saw the news as a sign that learning is becoming more open and 1_. Yet the real question is not whether AI can answer faster than a student. It is whether schools can use AI to make students think more 2_. A teacher in Ningbo asked her class to test an AI writing helper. Instead of letting it write the whole passage, she asked students to draft first. Then they used the tool to find unclear reasons, weak examples and grammar mistakes. Some students were surprised: the tool was quick, but it did not always understand local life or personal 3_. The teacher told them that AI should be a bridge, not a 4_. A bridge helps people cross a river, but people still choose where to go. In the same way, AI can collect resources, explain ideas and give feedback, but students must 5_ the final judgement. If they copy without checking, they may get an answer but lose the chance to learn. The conference also reminded educators that digital education is about 6_. A good platform can bring lessons to students in remote areas, but access alone is not enough. Students also need teachers who can guide them, classmates who can discuss with them and rules that protect their privacy. When these parts work together, technology becomes 7_. When one part is missing, technology may become a new 8_. For top students, the lesson is clear: the future learner is not the one who asks AI for every answer, but the one who asks better questions, checks sources and uses tools 9_. That kind of student will not be replaced by AI; instead, he or she will learn to work with it 10_ and creatively. The platform is new, but the goal of education is still old: to help people become 11_ thinkers. In this sense, AI is not the end of hard work. It is a test of whether learners can become more 12_, more careful and more human in a digital world. If a school forgets this, it may look modern on the surface but remain weak at the 13_. If it remembers this, a screen can become a window, a model can become a partner, and a classroom can reach 14_ the walls of one building. That is why the Hangzhou meeting matters not only to experts, but also to every student preparing for a 15_ future. 1. A. connected B. crowded C. hidden D. silent 2. A. slowly B. deeply C. cheaply D. loudly 3. A. memory B. traffic C. weather D. price 4. A. shortcut B. river C. window D. habit 5. A. avoid B. make C. doubt D. borrow 6. A. fairness B. danger C. speed D. fashion 7. A. meaningful B. expensive C. nervous D. empty 8. A. mistake B. barrier C. journey D. promise 9. A. wisely B. secretly C. suddenly D. angrily 10. A. safely B. blindly C. lazily D. noisily 11. A. independent B. lonely C. ordinary D. careless 12. A. passive B. responsible C. satisfied D. impatient 13. A. centre B. edge C. market D. gate 14. A. against B. beyond C. beside D. below 15. A. digital B. broken C. narrow D. private B. China: Space Computing and the New Meaning of Distance In 2026, China's space industry drew attention not only because of rockets, but also because of computing power in orbit. A satellite network developed with Zhejiang Lab had already tested AI models in space, showing that data could be 16_ before it was sent back to Earth. For many readers, this changes the meaning of distance. In the past, satellites often collected information and waited for ground stations to process it. That process could be slow when huge pictures or scientific signals were involved. If part of the work is done in space, useful information may reach farmers, city managers or rescue teams much 17_. One example is remote sensing. A satellite may look at an area after a flood or heavy snow. An AI model can help find damaged bridges, blocked roads or changed river lines. This does not mean people can stop checking; it means experts can 18_ their attention on the most urgent places. The machine helps narrow the search, while humans make decisions. The idea also raises difficult questions. If satellites become computers, they must be safe, reliable and energy-efficient. They must handle data without increasing risks to 19_. They must also follow rules, because space is not an empty playground. More objects in orbit bring more chances of accidents. Therefore, future space development needs both ambition and 20_. For students in Ningbo, this news can be read as a lesson in problem solving. A city with ports, bridges and weather risks needs timely information. A country exploring deep space needs faster ways to understand data. A world facing climate change needs tools that can watch the planet carefully. Space computing may sound far away, but its 21_ can be close to daily life. The key is to ask what problem is being solved, who benefits and what new responsibility appears. The best technology is not the one that looks most 22_ in a picture. It is the one that makes information more useful without making society less 23_. In that sense, space AI is not only a scientific achievement. It is also a test of governance, cooperation and public 24_. Distance is no longer only measured in kilometres. It is also measured by how quickly knowledge can travel from a satellite to a person who 25_ it. If students understand this, they will see space not as a remote stage for heroes, but as a working system that supports life on Earth. Such a 26_ also 27_ young readers that science news is not only about the 28_. A clear 29_ must explain limits as well as progress, and international 30_ will be needed if space is to remain useful and safe for everyone. 16. A. processed B. forgotten C. wasted D. painted 17. A. later B. faster C. quieter D. harder 18. A. hide B. waste C. focus D. lose 19. A. privacy B. music C. sport D. shopping 20. A. courage B. patience C. caution D. humour 21. A. influence B. mistake C. shape D. colour 22. A. dramatic B. simple C. sleepy D. cheap 23. A. honest B. safe C. rich D. busy 24. A. trust B. anger C. silence D. competition 25. A. needs B. refuses C. sells D. hides 26. A. conclusion B. excuse C. tool D. joke 27. A. reminds B. prevents C. imagines D. cancels 28. A. question B. future C. market D. answer 29. A. report B. classroom C. river D. crowd 30. A. cooperation B. decoration C. pollution D. confusion C. China: Urban Renewal Is More Than New Buildings In May 2026, China's State Council discussed urban renewal, green transition and better basic education. For many students, 'urban renewal' may sound like replacing old buildings with new ones. But a city becomes better not simply because it looks newer; it becomes better when ordinary people can live more 31_. In one Ningbo community, students studied this idea through a small project. They walked around old streets and recorded three problems: narrow sidewalks, weak lighting and a lack of shade. At first, some students wanted to suggest big changes. Their teacher asked them to think 32_. If a plan is too expensive or ignores local residents, it may never happen. The students interviewed shop owners, grandparents and delivery workers. They discovered that different people used the same street in different ways. A grandmother cared most about safe crossings. A shop owner wanted enough space for customers. A delivery worker needed places to stop for a short time. The class learned that good planning must balance 33_ needs. Their final proposal was small but practical: add benches under trees, improve night lighting, paint clearer lines near the school gate and create a shared corner for bikes. These ideas did not make headlines, but they showed what renewal should do: reduce daily trouble and increase public 34_. The project also changed how students read news. They understood that national policies are not only about numbers or large projects. Policies become real when they enter streets, schools and homes. A green and low-carbon city is not created by one meeting. It is built through thousands of 35_ decisions: where to plant trees, how to protect old culture, how to make buses convenient and how to give children enough places to learn and play. The most difficult part is not drawing a beautiful plan, but listening to people who will use the place every day. If cities are renewed without memory, they may lose their 36_. If they are renewed without fairness, some groups may be pushed aside. If they are renewed without green thinking, future generations will pay the 37_. For top students, the challenge is to see development as a living problem, not a slogan. A better city is a text that must be read with eyes, feet and 38_. It asks young people to connect geography with English, science with society and personal comfort with public responsibility. That is why a small street survey can become a lesson in 39_ citizenship. Students also learned to 40_ change in realistic ways. Some problems were 41_ to many streets, while others were local. Good planners listen to 42_ from residents and look 43_ one beautiful drawing. Urban 44_ should make people not only impressed, but also 45_ in daily choices. 31. A. comfortably B. secretly C. noisily D. separately 32. A. proudly B. realistically C. angrily D. carelessly 33. A. similar B. hidden C. different D. foreign 34. A. safety B. speed C. silence D. wealth 35. A. daily B. sudden C. private D. strange 36. A. height B. memory C. weather D. traffic 37. A. bill B. prize C. visit D. message 38. A. patience B. hunger C. noise D. doubt 39. A. global B. active C. ancient D. digital 40. A. protect B. measure C. forget D. repair 41. A. common B. impossible C. narrow D. empty 42. A. results B. habits C. dreams D. warnings 43. A. beyond B. under C. against D. without 44. A. exam B. design C. game D. meal 45. A. stronger B. heavier C. wiser D. colder D. Europe: Teachers at the Centre of AI Learning In May 2026, the Council of the European Union called for a human-centred approach to AI in education. The message was not anti-technology. It was a warning against a simple belief: if a tool is smart, learning will automatically become 46_. Across Europe, schools are testing AI systems that can give feedback, translate texts or help teachers understand students' progress. These tools may save time, but they also raise concerns. If students depend on AI too much, they may stop 47_ before asking for help. If schools collect too much data, privacy may be at risk. If teachers are poorly trained, a useful system may become a confusing one. The Council therefore placed teachers at the heart of the learning process. This does not mean teachers must reject AI. It means they should decide when, why and how it is used. A teacher can ask students to compare AI answers with their own ideas, check sources and explain their choices. In this way, AI becomes a 48_ for thinking rather than a machine for copying. The European debate is useful for Chinese students too. Many teenagers already use translation apps, grammar checkers and chatbots. The key difference is between help and replacement. Help gives a learner more 49_; replacement takes away the learner's work. A student who asks AI to explain an error may grow stronger. A student who lets AI write everything may become weaker without noticing it. The hardest question is not technical but educational: What kind of learner do we want to create? If the answer is an independent learner, schools must protect time for reading, discussion and mistakes. They must also teach students to doubt politely, question data and understand that fast answers are not always 50_ answers. Europe is not trying to stop digital education; it is trying to keep education human. That is a subtle but important 51_. In a classroom, trust grows through eye contact, encouragement, humour and patient correction. No model can fully replace that. But a model can support it if it is used under clear rules. So the future classroom may not be a battle between humans and machines. It may be a careful 52_ in which each side does what it does best. Teachers guide values and judgement; AI offers patterns and practice. Students, meanwhile, must learn to become 53_ users, not silent followers. Clear school policies can 54_ students from careless use. Such 55_ should be based on classroom 56_, not fear alone. If education stays 57_, teachers can 58_ both the power and the limits of AI. Students then learn to use it 59_. That may be the most important 60_ from Europe’s debate. 46. A. fairer B. easier C. deeper D. automatic 47. A. thinking B. exercising C. travelling D. smiling 48. A. danger B. partner C. secret D. prize 49. A. pressure B. control C. money D. noise 50. A. right B. short C. public D. private 51. A. mistake B. difference C. tradition D. promise 52. A. competition B. balance C. accident D. memory 53. A. responsible B. sleepy C. lonely D. local 54. A. confuse B. complete C. protect D. avoid 55. A. rules B. storms C. tickets D. dishes 56. A. evidence B. fashion C. weather D. order 57. A. human B. foreign C. secret D. cheap 58. A. explain B. cancel C. punish D. hide 59. A. carefully B. wildly C. hardly D. blindly 60. A. lesson B. river C. model D. market E. Europe: Transparency in the Age of Generated Content From August 2026, people in the European Union will have to be informed when they are interacting with some AI systems or seeing certain AI-generated content. This rule may sound legal, but its purpose is easy to understand: people should know when a machine is 61_ part of the message. Imagine a student watching a video of a public figure. If the video is manipulated, the student may believe something false. Imagine a job seeker receiving advice from a chatbot without knowing it. The advice may still be helpful, but the person should understand its 62_. Transparency does not solve every problem, but it gives people a fair chance to judge what they see. The rule also shows a larger European challenge: how to encourage innovation while reducing harm. If rules are too heavy, small companies may struggle. If rules are too weak, citizens may lose trust. The EU is trying to find a middle path, simplifying some rules while keeping protection for high-risk areas such as education, employment and public services. For teenagers, this debate has a practical meaning. Online life is full of pictures, voices and texts that look real. The question is no longer only 'Is this interesting?' but also 'Who made it? Why was it made? Can I check it?' A strong reader in the AI age must become a careful 63_. Schools can help by teaching students to read labels, compare sources and slow down before sharing. A false image may travel faster than a correction. A dramatic headline may get more attention than a balanced report. Therefore, the ability to pause is a modern literacy skill. Transparency rules are like warning signs on a road. They do not drive the car for us, but they 64_ danger and guide better choices. The deeper lesson is that trust cannot be built only by technology. It must be built by clear rules, honest design and educated users. When students learn this, they become less easy to fool and more able to take part in digital society. In the long run, transparency is not a limit on creativity. It is a way to keep creativity from becoming 65_. Good readers still need 66_. A 67_ can require labels, but users must 68_ different sources before deciding what is 69_. The most useful digital society is not the one with the most exciting images; it is the one with 70_ communication. As students become 71_ readers, they learn to 72_ what they see. This kind of 73_ builds judgement. Without 74_, even a label may be ignored; with it, transparency becomes real 75_. 61. A. shaping B. breaking C. hiding D. losing 62. A. source B. colour C. price D. speed 63. A. tourist B. editor C. athlete D. customer 64. A. create B. reduce C. signal D. enjoy 65. A. harmful B. useful C. public D. normal 66. A. evidence B. weather C. dinner D. sleep 67. A. law B. joke C. song D. map 68. A. compare B. follow C. forget D. decorate 69. A. accurate B. popular C. playful D. local 70. A. hidden B. impossible C. honest D. useless 71. A. stronger B. simpler C. colder D. narrower 72. A. share B. question C. print D. copy 73. A. reading B. swimming C. selling D. cleaning 74. A. silence B. judgement C. anger D. hunger 75. A. problem B. protection C. secret D. result F. Europe: What One Warm April Can Teach The Copernicus Climate Change Service reported that April 2026 was among the warmest Aprils globally. Such a sentence is easy to repeat but hard to understand well. A global average is not a photograph of every place; it is a 76_ that needs careful reading. In Europe, April was not the same everywhere. Western and central parts were drier than average under high pressure, while other areas, including parts of the UK, Ireland, Spain and Italy, were wetter. This contrast matters because climate is not experienced as one number. Farmers care about soil moisture. City managers care about water supply. Families care about heat, floods and travel safety. A Ningbo student reading this report might ask, 'Why should I care about Europe?' One answer is that climate systems are connected. Another is that climate reports teach a method: never stop at the headline. Ask which area, which period, which comparison and which human activities are affected. This habit is useful far beyond climate study. The report also helps students understand uncertainty. Scientists can measure temperature and rainfall, but future risk still depends on choices: how cities use water, how quickly warnings reach people and how communities protect vulnerable groups. Data does not remove responsibility; it makes responsibility more 77_. In English reading, climate news is especially valuable because it combines facts with interpretation. Students must separate what the report says from what a writer thinks it means. They must notice words such as 'average', 'region', 'risk' and 'trend'. These words look simple but carry scientific meaning. A high-level reader does not only find answers; he or she follows the logic behind them. April 2026, then, is more than a record. It is a lesson in reading the planet with care. If students can read weather and climate data thoughtfully, they may also read social changes more 78_. In both cases, the goal is the same: to see patterns without ignoring people. A 79_ report asks readers to 80_ places and years, not just remember one number. It also asks for 81_: maps, charts and local observations. A 82_ view connects science with daily life. This kind of 83_ gives students useful 84_ for other subjects too. When they notice a 85_, they should ask who may be affected and what choices are 86_. A 87_ may catch attention, but 88_ need more than attention. They need 89_ that is accurate, fair and 90_. 76. A. signal B. secret C. joke D. prize 77. A. visible B. boring C. distant D. private 78. A. quietly B. critically C. cheaply D. luckily 79. A. simple B. local C. global D. empty 80. A. compare B. copy C. cancel D. hide 81. A. pressure B. direction C. evidence D. promise 82. A. balanced B. broken C. crowded D. ancient 83. A. reading B. cooking C. drawing D. singing 84. A. methods B. mistakes C. markets D. meals 85. A. disaster B. pattern C. silence D. habit 86. A. flexible B. responsible C. sleepy D. narrow 87. A. headline B. building C. vehicle D. ticket 88. A. citizens B. actors C. pilots D. singers 89. A. knowledge B. weather C. comfort D. fiction 90. A. useful B. harmful C. expensive D. impossible G. US: Artemis II and the Discipline of Testing NASA's Artemis II mission in 2026 attracted worldwide attention because humans travelled around the Moon again after more than half a century. Yet the mission was not designed as a final victory. It was a test flight, and the word 'test' is the 91_ to understanding it. A test flight asks questions before making promises. Can Orion support astronauts safely in deep space? Can communication networks keep the crew connected? Can space weather forecasters protect astronauts from solar storms? These questions may sound technical, but they all point to one idea: courage without preparation is not courage; it is 92_. NOAA space weather experts supported the mission by watching solar activity. A strong solar event could affect communications or increase radiation risk. The public may see only the rocket launch, but behind that moment stands a large system of scientists, engineers, doctors and operators. Space exploration is a team sport played at a distance. For students, Artemis II offers a lesson different from science fiction. It shows that progress is often slow, checked and full of limits. The mission did not land on the Moon. That was not a failure, because landing was not its 93_. Its job was to prove that the next steps were possible. The same idea applies to learning. A difficult exam paper is not only a score; it is a test of what still needs work. A failed experiment is not the end; it is information. A careful reader does not ask only 'Did they succeed?' but 'What were they trying to prove?' When students read news this way, they become less attracted to simple labels and more able to understand 94_. Artemis II reminds us that big dreams need small checks. The Moon may look romantic in the night sky, but returning there requires lists, simulations, repairs and patience. In that sense, the mission is not just about space. It is about disciplined hope: the belief that humans can go farther, but only if they are willing to test every step 95_. The spacecraft also had to remain 96_ to Earth. Astronauts needed 97_ support and engineers worked under great 98_. A 99_ mission uses 100_ to guide decisions. It is often 101_ work, because a huge 102_ must be checked again and again. To 103_ well, teams study both successes and 104_ before they move 105_ a risk becomes too large. 91. A. key B. door C. wall D. prize 92. A. wisdom B. risk C. friendship D. freedom 93. A. problem B. design C. purpose D. excuse 94. A. process B. weather C. grammar D. fashion 95. A. carefully B. secretly C. quickly D. loudly 96. A. refused B. connected C. forgot D. copied 97. A. public B. medical C. random D. weak 98. A. pressure B. silence C. decoration D. luck 99. A. romantic B. responsible C. impossible D. empty 100. A. data B. dinner C. music D. law 101. A. narrow B. patient C. crowded D. broken 102. A. answer B. image C. system D. conflict 103. A. avoid B. test C. damage D. punish 104. A. failures B. tools C. stories D. colours 105. A. before B. after C. beyond D. against H. US: Weather Data, AI Models and Public Trust In May 2026, American climate and weather reports again reminded the public that forecasts are not magic. NOAA's April climate analysis showed unusual warmth in some regions, and researchers also discussed how AI can find hidden patterns in precipitation. At the same time, some experts warned that reducing weather data programmes could make forecasts less 106_. This debate is important because AI models depend on data. A model can learn patterns only if it receives enough high-quality information. If observations become fewer or less reliable, even a powerful model may learn the wrong 107_. In other words, AI does not remove the need for human measurement; it increases the need for good measurement. Weather forecasting is a public service. Farmers plan planting, airlines plan routes, cities prepare for heat and families decide whether to leave home before storms. A small error may become costly when many people depend on the same forecast. Therefore, trust is built not by saying a model is advanced, but by showing how it is tested, where its data comes from and when uncertainty remains. For students, this topic is a useful warning against blind confidence in technology. AI may help discover climate links that humans miss, but it should be checked against physics, observations and experience. When an AI forecast fails, the question should not be 'Is AI useless?' but 'What did the model learn, and what did it ignore?' The best future may combine human experts, traditional models and AI tools. Each has strengths and weaknesses. Human forecasters understand local context. Traditional models follow physical rules. AI can search large datasets quickly. If they are used together, society may receive better warnings. If one is treated as a 108_ for all the others, risk may grow. Public trust in forecasts is like a bridge: it is built slowly and damaged quickly. To keep it strong, science must be open about uncertainty and serious about data. For a coastal city like Ningbo, where typhoons and heavy rain matter, this lesson is not distant. It is part of learning how to live 109_ with a changing climate. A useful 110_ should tell people what is likely, 111_ also making limits clear. Students can 112_ different reports and look for 113_ information. Because weather warnings affect 114_ safety, the 115_ of data is not a small detail. Local 116_ matters too: a warning may mean different things for a farm, a port or a school. When knowledge is 117_ openly and explained in a 118_ way, people can 119_ earlier. That is why evidence, not excitement, should be the 120_ of trust. 106. A. colourful B. reliable C. private D. popular 107. A. patterns B. songs C. prices D. jokes 108. A. replacement B. reason C. classroom D. memory 109. A. safely B. silently C. secretly D. suddenly 110. A. forecast B. promise C. storm D. model 111. A. because B. although C. unless D. while 112. A. compare B. praise C. ignore D. destroy 113. A. cheap B. missing C. careful D. bright 114. A. public B. personal C. funny D. empty 115. A. failure B. quality C. vacation D. language 116. A. context B. colour C. speed D. prize 117. A. shared B. hidden C. useless D. foreign 118. A. final B. balanced C. careless D. secret 119. A. prepare B. refuse C. promise D. forget 120. A. evidence B. fashion C. laughter D. shadow 二、阅读理解(共12篇,60小题) 阅读下面十二篇长文,然后从每题所给的A、B、C、D四个选项中选出最佳选项。 A. China’s AI Education Platform: Sharing Is Not the Same as Learning China announced the launch of a global AI education service platform during the 2026 World Digital Education Conference in Hangzhou. The platform aims to support cross-border sharing of high-quality educational resources and deepen the use of AI in education. For a student in Ningbo, the news may sound distant, but the questions behind it are close to daily study: What should a digital platform provide? How should students use it? And how can schools make sure technology strengthens learning rather than weakens it? A platform can make resources easier to reach. A student in a small town may watch a lesson by an excellent teacher. A teacher may compare teaching materials from different countries. A school may use AI to find which grammar points students often misunderstand. These are real benefits. However, sharing resources is not the same as learning. A video does not guarantee attention. An AI explanation does not guarantee understanding. A student who only collects materials without using them carefully may become busier but not wiser. That is why the human part remains important. Teachers need to design tasks, ask follow-up questions and help students reflect on mistakes. Students need to take notes, check sources and explain ideas in their own words. Parents need to understand that a smart device is not a private tutor unless the child uses it with discipline. Digital education works best when it connects people, not when it isolates them behind screens. The Hangzhou conference also showed that education has become a global conversation. Countries want to use AI, but they also worry about fairness, privacy and quality. If rich schools benefit first and poor schools wait, the digital gap may widen. If student data is not protected, trust may fall. If AI answers are accepted without checking, false information may spread in classrooms. Therefore, the platform is both a chance and a responsibility. For top middle school students, the deeper lesson is about learning strategy. The future may not reward those who remember the most facts, because facts are easier to find than before. It may reward those who can judge information, connect ideas and ask meaningful questions. In this sense, AI education is not mainly about machines. It is about whether human learners can become more active, fair-minded and independent. 121. What is the main purpose of the global AI education service platform? A. To replace all teachers with AI. B. To support sharing of quality educational resources. C. To stop students from learning foreign languages. D. To make exams disappear from schools. 122. Why does the writer say “sharing resources is not the same as learning”? A. Because students may access materials without understanding them. B. Because online lessons are always worse than printed books. C. Because AI cannot explain any grammar points. D. Because teachers no longer need resources. 123. Which group is NOT mentioned as having a role in digital education? A. Teachers. B. Students. C. Parents. D. Tour guides. 124. What risk may appear if rich schools benefit first? A. Students will stop using notebooks. B. The digital gap may become wider. C. Teachers will have too much free time. D. All schools will become the same. 125. What ability may be more important in the future according to the passage? A. Copying information quickly. B. Avoiding all digital tools. C. Judging information and asking meaningful questions. D. Remembering every answer from AI. B. AI Literacy: A New Basic Skill China’s plan to build an AI literacy system across different stages of education shows that AI is no longer treated only as a subject for computer scientists. It is becoming a basic skill f