1 . Catherine Garland, a physics professor, started seeing “the problem” in 2019. She’d laid out the assignment clearly during an engineering course, but student after student was calling her over for help. They were all getting the same error message: The program couldn’t find their files.
Garland thought it would be an easy fix. She asked each student where they had saved their project. “Could they be on the desktop? Perhaps in the Documents folder?” But over and over, she was met with confusion. “What are you talking about?” multiple students inquired. Gradually, Garland came to the realization: the concept of file folders and directories, essential to previous generations, understanding of computers, is gibberish to many modern students.
Garland’s mental model is commonly known as “directory structure”, the hierarchical system (层级体系) of folders used to arrange files. What have caused the mental model to change? It is possible that many students spent their high school years storing documents in the cloud storage like OneDrive and Dropbox rather than in physical spaces. It could also have to do with the other apps they’re accustomed to. “When I want to scroll (滚屏) over to Snapchat, Twitter, they’re not in any particular order, but I know exactly where they are,” says Vogel, who is a devoted iPhone user. Some of it boils down to muscle memory.
It may also be that in an age where every user interface includes a search function, young people have never needed folders or directories. The first internet search engines were used around 1990, but features like Windows Search are products of the early 2000s. While many of today’s professors grew up without search functions, today’s students increasingly don’t remember a world without them.
Some may blame the generational incompetence. An international study claimed that only 2 percent of Generation Z (born from 1997 onwards) had achieved the “digital native” level of computer literacy. But the issue is likely not that modern students are learning fewer digital skills, but rather that they’re learning different ones. Garland, for all her knowledge of directory structure, doesn’t understand Instagram nearly as well as her students do. “They use computers one way, and we use computers another way,” Garland emphasizes. “That’s where the problem lies.”
1. The word “gibberish” in paragraph 2 is closest in meaning to________.A.common | B.accessible | C.nonsense | D.fundamental |
A.There is no search function in the directory structure. |
B.College professors have weaker muscles than students do. |
C.Modern students like to store documents in physical drives. |
D.The change in mental models reflects the progress in technology. |
A.highlights the different mindsets of two generations |
B.criticizes modern students’ overuse of online apps |
C.shows the difficulty of teaching today’s students |
D.calls on a change in the education of physics |
A.Teaching students directory structure. |
B.Improving generational understanding. |
C.Enhancing Generation Z’s digital skills. |
D.Urging teachers to learn search functions. |
“Li Na’s perseverance and pioneering courage will be recognized with the highest honor in her profession: induction (入门) into the International Tennis Hall of Fame (名人堂).”
“Ne Zha and Monkey King share a lot in common. They are brave fighters, refusing to resign themselves to destiny.”
成功的人物总有一些可贵的品质,读了以上材料,谈谈你的想法。内容包括:
1. 简述李娜(网球运动员)或者哪吒(神话人物)等身上的可贵品质;
2. 结合生活实际谈谈其中某一可贵品质的重要性。
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7 . Page, my younger brother by four years, has been braindamaged from birth. He does not speak, cannot hear and see poorly through his remaining eye. He stays home, staring at the television happily. But it wasn’t always this way.
On a lot summer morning, Mum had penciled “VISIT GRANDMA” for Page in large letters on a napkin before we left for the nursing home. No one expected to understand that this might be our last visit.
We arrived there and stepped into her room. The strokes had left grandma trembling and unresponsive. Her mouth hung open, and her wide eyes shut and opened quickly and stared but appeared not to see.
We stood round the bed, smiling uncomfortably, and saying that everything would be all right. For the first time, I was free to talk all I wanted.
Page was standing quietly next to the window with his face brilliant red, tears following from his eyes. Just then, he pushed through the group and made his way to the bed. He leaned over Grandma’s withered body and took her cheeks gently in his hands.
Those of us with healthy ears were deaf to the volumes being spoken in that wonderful, wordless exchange.
We kissed Grandma, and slowly walked out of the room one by one. I was the last to leave. “Bye, Grandma,” I said. As I turned to look at her one last time, I noticed her lips come together, as if she was trying to speak. Somehow, if for a moment, she gathered the strength to say goodbye.
That afternoon by Grandma’s deathbed, when none of us knew what to say, my speechless brother had said it all.
A.Head bowed, he stood there, his cheeks wet with tears. |
B.That is when I knew Page had reached her. |
C.I tried to express my love to her. |
D.I felt a rush of warmth deep inside me. |
E.Nobody thought he would appeared and burst out crying. |
F.But I could think of nothing to say to her. |
8 . Can artificial intelligence uncover a liar? It sounds like science fiction, but such an AI system is possible. The question is: How accurate can it be? Rada Mihalcea, a professor of computer science and engineering at the University of Michigan, has worked on deception detection for about a decade. This is how they constructed one AI deception detector, and how it works.
The first thing that researchers working on artificial intelligence and machine learning need is data. In the case of the work that Mlhalcea did, they began with videos from actual court cases. For example, a defendant speaking in a trial in which they were found guilty could provide an example of deceit; they also used testimony from witnesses as either example of truthful or deceitful statements. Altogether, they used 121 video clips and the corresponding transcripts of what they said—about half represented deceptive statements, and half truthful. It was this data that they used to build machine learning classifiers that ultimately had between a 60 to 75 percent accuracy rate.
One thing the system noticed is the use of pronouns—people who are lying would tend to less often use the word ‘I’ or ‘we’, Mihalcea explains. “Instead, people who are lying would more often use ‘you,’ ‘yours,’ ‘he,’ ‘they,’ and ‘she.’” That’s not the only linguistic signal: someone telling a lie would use “stronger words” that “reflect certainty,” she says. Examples of those types of words are “absolutely,” and “very,” while interestingly, people telling the truth were more likely to use words such as “maybe” or “probably.” “I think people who are deceptive would try to make up for the lie they are putting forward,” she says, “and so they try to seem more certain of themselves.” As for gestures, she points out that someone being deceitful would more likely look directly into the eyes of the person questioning them. They also tended to use both hands when gesturing. Instead of just one—also, she suspects, as part of trying to be convincing.
However, Mlhalcea’s work is “far from perfection,” she concedes. “As a researcher, we are excited we were able to get to 75 percent accuracy.” But looked at another way, that’s an error rate of one in four. Ultimately, she sees technology like this as being assistive for people—it could, for example, indicate that it noticed something “unusual” in a speaker’s statement, and then perhaps have a person “investigate more.”
1. What researchers need first to predict whether a defendant is lying is ______.A.statements | B.data | C.pronouns | D.gestures |
A.They used a classifier to build the system. |
B.They involved AI system in a real-life trial. |
C.They fed the system with both truthful and deceptive statements. |
D.They used defendant’s statements as deceptive examples and witnesses’ as truthful examples. |
A.Using pronouns frequently. |
B.Looking straight in your eyes. |
C.Gesturing with both two hands. |
D.Using strong words to make it sound more certain. |
A.Her work fails to live up to her expectation. |
B.AI technology can be used as an aid for human beings. |
C.AI can replace human beings in deception detection now. |
D.AI is so far from perfection that it can’t be used to assist people to uncover a liar. |
9 . Arthur C Clarke (1917-2008) is a science-fiction writer. His fictional HAL 9000 computer in 2001: A Space Odyssey, which he co-wrote,
Till now, the book is
Being wrong is just one problem I have with Clarke’s book. Like most future-gazing, it sees tomorrow
I love what technology is doing for the developing world, where electric lighting, washing machines and the Internet have
Mare Demarest, an Oregon-based digital thinker and author, believes technology tells us truths regardless of our nasty tendency to get distracted, to miss the moment, and to
We’re not progressing humanity or changing the world. That’s what ideas do, and machines don’t have ideas. Technology is only the
A.experiences | B.causes | C.eliminates | D.foresees |
A.coining | B.breaking | C.emphasizing | D.parroting |
A.wrong | B.technical | C.readable | D.informative |
A.use | B.sense | C.mention | D.doubt |
A.launched | B.predicted | C.discovered | D.inspected |
A.entirely | B.attentively | C.seriously | D.positively |
A.constructive | B.supervisory | C.minor | D.leading |
A.economy | B.industry | C.reason | D.reflection |
A.achieved | B.assessed | C.traced | D.aided |
A.active | B.essential | C.revolutionary | D.passive |
A.bend | B.store | C.download | D.transfer |
A.create | B.educate | C.understand | D.improve |
A.besides | B.however | C.therefore | D.otherwise |
A.multitask | B.identification | C.judgment | D.flexibility |
A.agent | B.spokesperson | C.signboard | D.illustration |
A.encouraged | B. excuse | C. featured | D. favor | E. approaches | F. defended |
G. access | H. serve | I. regional | J. celebrated | K. lengths |
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Something similar is happening with A Bite of China, a
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Innovation is generally