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Questões de Concurso Sobre sinônimos | synonyms em inglês

Foram encontradas 1.586 questões

Q3808674 Inglês

Read the following text to answer questions


 Effective communication is central to the clinicianpatient encounter. When the patient’s needs and concerns are well understood through a biopsychosocial formulation, then a comprehensive care plan can be mutually agreed on. Communication skills training (CST) has become one vehicle to build skills that optimally advance the clinical agenda, alongside promoting professionalism and excellence of care. Good communication skills have been linked to higher patient satisfaction, greater patient adherence to treatment, better patient health outcomes, fewer physician malpractice claims, reduced patient anxiety, increased recall, and improved understanding.


Patients with cancer report unmet communication needs for information about the extent of disease, prognosis, and treatment options, intent, and adverse effects. This is consistent with earlier studies on communication in clinical encounters. When the clinician is responsive to patients’ needs, their anxiety levels have been significantly reduced.


In this article, we propose the establishment of a universal CST curriculum for fellows of all cancer specialties that builds their professionalism and sustains effective clinician-patient communication throughout their careers.


(https://pmc.ncbi.nlm.nih.gov/articles/PMC3341141/. 06.08.2025. Adaptado)

In the extract from the first paragraph “skills that optimally advance the clinical agenda, alongside promoting professionalism and excellence of care”, the highlighted word can be substituted, without changes in its original meaning, by
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Q3803578 Inglês
Yesterday
The Beatles

Yesterday
All my troubles seemed so far away
Now it looks as though they're here to stay
Oh, I believe in yesterday

Suddenly
I'm not half the man I used to be
There's a shadow hanging over me
Oh, yesterday came suddenly

Why she had to go? I don't know
She wouldn't say
I said something wrong, now I long
For yesterday

Yesterday
Love was such an easy game to play
Now I need a place to hide away
Oh, I believe in yesterday

Why she had to go? I don't know
She wouldn't say
I said something wrong, now I long
For yesterday

Yesterday
Love was such an easy game to play
Now I need a place to hide away
Oh, I believe in yesterday

In the line “Now I long for yesterday,” which option is the most precise synonym for long as used in the lyric’s emotional context?
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Q3787306 Inglês
The Century-Long Search for the Loch* Ness Monster 


(Available at: www.bbc.com/culture/article/20251002-the-century-long-search-for-the-loch-ness-monster – 
text specially adapted for this test). 
*Loch: in Scotland, a lake or inlet of the sea or ocean. 
(Available at: https://dictionary.cambridge.org/dictionary/english-portuguese/loch)   
*Eel: a snake-like water creature. 
(Available at: https://dictionary.cambridge.org/dictionary/english-portuguese/eel)
In the text, the word ‘hoax’ (l. 07) is closest in meaning to: 
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Ano: 2025 Banca: FUNDATEC Órgão: IGP-RS Prova: FUNDATEC - 2025 - IGP-RS - Perito Criminal |
Q3781819 Inglês

Space power: The dream of beaming solar energy from orbit 



(Available at: www.bbc.com/future/article/20251029-the-beam-dream-should-we-build-solar-farms-in-space– 

text specially adapted for this test). 

Analyse the statements below according to the vocabulary used in the text, and mark T, if true, or F, if false. 

( )The word “feasible” (l. 28) could be replaced by “achievable” without changing the meaning.
( ) The prefix un– in “uncertain” (l. 38) and “unrealistic” (l. 17) indicates reversal of action, similar to the verb “undo”.
( ) The word “viable” (l. 32) refers to something that can function successfully.
(  ) The term “renewable” (l. 14) is formed by the addition of the prefix re- and the suffix -able, which mean, respectively, “not” and “capability/possibility”.

The correct order of filling in the parentheses, from top to bottom, is:
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Q3780405 Inglês
Read the following text and answer the questions.


Artificial Intelligence: The “lethal trifecta”

    LARGE LANGUAGE MODELS (LLMs), a trendy way of building artificial intelligence, have an inherent security problem: they cannot separate code from data. As a result, they are at risk of a type of attack called a prompt injection, in which they are tricked into following commands they should not. Sometimes the result is merely embarrassing, as when a customer-help agent is persuaded to talk like a pirate. On other occasions, it is far more damaging.

    The worst effects of this flaw are reserved for those who create what is known as the “lethal trifecta”. If a company, eager to offer a powerful AI assistant to its employees, gives an LLM access to untrusted data, the ability to read valuable secrets and the ability to communicate with the outside world at the same time, then trouble is sure to follow. And avoiding this is not just a matter for AI engineers. Ordinary users, too, need to learn how to use AI safely, because installing the wrong combination of apps can generate the trifecta accidentally. 

   Better AI engineering is, though, the first line of defence. And that means AI engineers need to start thinking like engineers, who build things like bridges and therefore know that shoddy work costs lives.

  The great works of Victorian England were erected by engineers who could not be sure of the properties of the materials they were using. In particular, whether by incompetence or malfeasance, the iron of the period was often not up to snuff. As a consequence, engineers erred on the side of caution, overbuilding to incorporate redundancy into their creations. The result was a series of centuries-spanning masterpieces.

   AI-security providers do not think like this. Conventional coding is a deterministic practice. Security vulnerabilities are seen as errors to be fixed, and when fixed, they go away. AI engineers, inculcated in this way of thinking from their schooldays, therefore often act as if problems can be solved just with more training data and more astute system prompts.

   These do, indeed, reduce risk. The cleverest frontier models are better at spotting and refusing malicious requests than their older or smaller cousins. But they cannot eliminate risk altogether. Unlike most software, LLMs are probabilistic. Their output is driven by random selection from likely responses. A deterministic approach to safety is thus inadequate. A better way forward is to copy engineers in the physical world and learn to work with, rather than against, capricious systems that can never be guaranteed to function as they should. That means becoming happier dealing with unpredictability by introducing safety margins, risk tolerance and error rates.

   Overbuilding in the AI age might, for instance, mean using a more powerful model than is needed for the task at hand, to reduce the risk it will be tricked into doing something inappropriate. It might mean imposing limits on the number of queries LLMs can take from external sources, calibrated to the risk of damage from a malicious query. And mechanical engineering emphasises failing safely. If an AI system must have access to secrets, then avoid handing it the keys to the kingdom.

   In the physical world, bridges have weight limits – even if they are not always stated clearly to drivers. And, importantly, these are well within the actual tolerances that calculations suggest a bridge will bear. The time has now come for the virtual world of AI systems to be similarly equipped.

Adapted from The Economist, September 27th, 2025, p. 10
Introducing in by introducing safety margins (6th paragraph) is similar in meaning to 
Alternativas
Q3780403 Inglês
Read the following text and answer the questions.


Artificial Intelligence: The “lethal trifecta”

    LARGE LANGUAGE MODELS (LLMs), a trendy way of building artificial intelligence, have an inherent security problem: they cannot separate code from data. As a result, they are at risk of a type of attack called a prompt injection, in which they are tricked into following commands they should not. Sometimes the result is merely embarrassing, as when a customer-help agent is persuaded to talk like a pirate. On other occasions, it is far more damaging.

    The worst effects of this flaw are reserved for those who create what is known as the “lethal trifecta”. If a company, eager to offer a powerful AI assistant to its employees, gives an LLM access to untrusted data, the ability to read valuable secrets and the ability to communicate with the outside world at the same time, then trouble is sure to follow. And avoiding this is not just a matter for AI engineers. Ordinary users, too, need to learn how to use AI safely, because installing the wrong combination of apps can generate the trifecta accidentally. 

   Better AI engineering is, though, the first line of defence. And that means AI engineers need to start thinking like engineers, who build things like bridges and therefore know that shoddy work costs lives.

  The great works of Victorian England were erected by engineers who could not be sure of the properties of the materials they were using. In particular, whether by incompetence or malfeasance, the iron of the period was often not up to snuff. As a consequence, engineers erred on the side of caution, overbuilding to incorporate redundancy into their creations. The result was a series of centuries-spanning masterpieces.

   AI-security providers do not think like this. Conventional coding is a deterministic practice. Security vulnerabilities are seen as errors to be fixed, and when fixed, they go away. AI engineers, inculcated in this way of thinking from their schooldays, therefore often act as if problems can be solved just with more training data and more astute system prompts.

   These do, indeed, reduce risk. The cleverest frontier models are better at spotting and refusing malicious requests than their older or smaller cousins. But they cannot eliminate risk altogether. Unlike most software, LLMs are probabilistic. Their output is driven by random selection from likely responses. A deterministic approach to safety is thus inadequate. A better way forward is to copy engineers in the physical world and learn to work with, rather than against, capricious systems that can never be guaranteed to function as they should. That means becoming happier dealing with unpredictability by introducing safety margins, risk tolerance and error rates.

   Overbuilding in the AI age might, for instance, mean using a more powerful model than is needed for the task at hand, to reduce the risk it will be tricked into doing something inappropriate. It might mean imposing limits on the number of queries LLMs can take from external sources, calibrated to the risk of damage from a malicious query. And mechanical engineering emphasises failing safely. If an AI system must have access to secrets, then avoid handing it the keys to the kingdom.

   In the physical world, bridges have weight limits – even if they are not always stated clearly to drivers. And, importantly, these are well within the actual tolerances that calculations suggest a bridge will bear. The time has now come for the virtual world of AI systems to be similarly equipped.

Adapted from The Economist, September 27th, 2025, p. 10
The word tricked (1st paragraph) means that LLMs can be
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Q3778305 Inglês

Are Some Sugars ‘Less Bad’ Than Others?


        Q: I’m trying to limit sugar, but I love sweets. Are “natural” sweeteners like honey and agave syrup healthier alternatives to table sugar?


         You probably know that the sugars in fruits, vegetables and other plants are far better for you than the added sugars often found in processed foods like sodas, candy bars and many baked goods.


         But in that category of added sugars, there’s an array of sweeteners that are often seen as more “natural” or healthier than others. Honey, maple syrup and agave nectar, for instance, are commonly touted as “better for you” swaps for regular sugar, such as in many health-focused baking recipes and on social media.


        Is that right? We asked three nutrition experts to help us sort it out. 


Source: 

https://www.nytimes.com/2025/10/28/well/eat/health-

effects-honey-maple-syrup-agave.html 

In the sentence “I’m trying to limit sugar, but I love sweets,” the word limit is closest in meaning to:
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Q3773724 Inglês

Read the text below and answer question


Plan to test Liberian schoolchildren for drugs blocked

October 17th, 2025

By Moses Kollie Garzeawu

Monrovia, Liberia, Africa


Liberia's Education Ministry has blocked controversial plans to introduce mandatory drug testing in all of the country's schools.


Speaking to local media, the interim head of the Liberia Drug Enforcement Agency (LDEA), Fitzgerald Biago, said school testing would help address the growing problem of drug abuse.


The announcement sparked a mixed response. Some thought it would help tackle the scourge of drugs, while others saw it as an invasion of privacy, or feared it would cost too much.


Last year, President Joseph Boakai declared drug and substance abuse a national emergency and a recent EU-backed report estimated that one in five young Liberians take drugs.


However, the Education Ministry said it was not aware of any plans to test students and added that such a decision needed to be based on concrete evidence and properly thought through.


Assistant minister in charge of students Sona Toure-Sesay told the BBC that this kind of plan required proper research. "Let's assume we are made aware of the proposed initiatives by the LDEA, it will require us to conduct research and review case studies from other countries where this has been successful," she said.  


Toure-Sesay also noted that testing could affect students. "What happens to students who test positive? What are the social services in place for them? Some of them might be bullied even after returning, and it may affect their overall educational performances."


She added that a multi-sectoral committee on drug and substance abuse had been set up, headed by the Health Ministry. Along with strengthening health clubs in schools, she said that this would help to reduce the prevalence of drugs among students.


President Boakai dismissed the leadership of the LDEA in August this year, and recently appointed Biago, a former senior police officer, as interim head of the agency.



Taken from:

https://www.bbc.com/news/articles/c0mxz3x1lr7o  

In the fragment of paragraph 8 “She added that a multi-sectoral committee on drug and substance abuse had been set up”, the phrasal verb SET UP could be replaced, with no change in meaning, by:  
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Q3773718 Inglês

Read the text below and answer question


Plan to test Liberian schoolchildren for drugs blocked

October 17th, 2025

By Moses Kollie Garzeawu

Monrovia, Liberia, Africa


Liberia's Education Ministry has blocked controversial plans to introduce mandatory drug testing in all of the country's schools.


Speaking to local media, the interim head of the Liberia Drug Enforcement Agency (LDEA), Fitzgerald Biago, said school testing would help address the growing problem of drug abuse.


The announcement sparked a mixed response. Some thought it would help tackle the scourge of drugs, while others saw it as an invasion of privacy, or feared it would cost too much.


Last year, President Joseph Boakai declared drug and substance abuse a national emergency and a recent EU-backed report estimated that one in five young Liberians take drugs.


However, the Education Ministry said it was not aware of any plans to test students and added that such a decision needed to be based on concrete evidence and properly thought through.


Assistant minister in charge of students Sona Toure-Sesay told the BBC that this kind of plan required proper research. "Let's assume we are made aware of the proposed initiatives by the LDEA, it will require us to conduct research and review case studies from other countries where this has been successful," she said.  


Toure-Sesay also noted that testing could affect students. "What happens to students who test positive? What are the social services in place for them? Some of them might be bullied even after returning, and it may affect their overall educational performances."


She added that a multi-sectoral committee on drug and substance abuse had been set up, headed by the Health Ministry. Along with strengthening health clubs in schools, she said that this would help to reduce the prevalence of drugs among students.


President Boakai dismissed the leadership of the LDEA in August this year, and recently appointed Biago, a former senior police officer, as interim head of the agency.



Taken from:

https://www.bbc.com/news/articles/c0mxz3x1lr7o  

In the fragment of paragraph 1 “Liberia’s Education Ministry has blocked controversial plans to introduce mandatory drug test”, the adjective “mandatory” could be replaced, with no change in meaning, by: 
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Q3764986 Inglês
The use of AI in public safety is transforming how cities approach crime and security.[...] The primary focus in enhancing public safety is prevention. Stopping crime before it happens protects residents, helps cities use resources more wisely, builds trust in public services and creates safer, better-planned communities. AI is making this possible by turning large, scattered data into actionable insight. Law enforcement agencies can analyze years of crime data, community reports, weather patterns and local events to predict where problems are likely to arise. Predictive policing can cut crime by up to 40% while helping cities deploy resources more proactively. These tools need to be implemented with care, as biased data or algorithms can lead to unfair targeting if not properly managed.

SAND TECHNOLOGIES. AI in Public Safety: transforming how cities keep people safe.

In “helps cities use resources more wisely", the word ‘wisely’ is closest in meaning to:
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Q3763486 Inglês
During an advanced English class, a student asks about the difference between these two sentences: (1)“The teacher stopped talking to the students.” and (2)“The teacher stopped to talk to the students.”. The trainee teachers give different interpretations, and you must clarify the semantic aspects involved.

As a senior English teacher, you are guiding trainee teachers to analyze semantic nuances in classroom communication, consider the situation above and judge the following items, according to English semantics. 
Both sentences share the same core meaning, since “stop” always implies a cessation of action.
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Q3760455 Inglês
Which of the alternatives below is a synonym of the word in bold “buffs” in “For bike buffs, it doesn't get any better” (I. 18)?  
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Q3758791 Inglês
Leia o texto abaixo para responder da questão.

New Study: This Regional Accent Is Considered the Most Trustworthy in the U.S.—And the Results Will Really Surprise You!

By Jennifer Geddes

A person’s cadence counts for a lot.

Everyone knows first impressions are important— and we don’t just make them based on sight. Beyond a chic outfit and well-coiffed hair, how a person sounds can also be a big factor when forming an initial opinion. In fact, a recent analysis of more than a dozen American accents conducted by BetUS Casino found that some folks’ speech actually conveys more honesty and reliability than others’.

At this point, you’re probably praying your own voice sounds dependable, not shifty or shady, right? Try to relax, and then read on to learn (nay, hear!) where the most trustworthy accents are located.

How was the study conducted?

As with many studies today, internet data helped determine which parts of the country sound the most steadfast and true. BetUS Casino crafted the report, which is current as of Aug. 15, 2025, by focusing on how people feel about 14 different regional accents.

How did the company determine those feelings?

First, researchers looked at internet search terms like “friendly (accent)” or “professional (accent).” Then, to complete the rankings, they compiled data on the rate of financial crimes per 10,000 people, plus the number of lawyers and primary-care doctors in each area.

Why doctors and lawyers, you may ask? Well, these are professions that rely on trust—after all, you might have to put your life in their hands! The more of these professionals in an area, the more trustworthy the accent. Once the study authors had the information in hand, they weighted the data and ranked the regions on a scale of 1–100.

Which regional accent is considered the most trustworthy?

Now hear this: The regional accent that’s considered to be the most trustworthy hails from Boston!

Yup, the fine citizens of Beantown scored 56.1, which was enough to take top honors for sounding highly dependable. Boston ranks so strongly thanks to more than 23,300 searches related to how kind and upstanding the accent sounds. The Massachusetts capital and largest city in New England also sports a low level of financial crime and is home to tens of thousands of lawyers and doctors.

Boston shines in other ways too, underlining the trust factor essential to its distinctive accent. For example, one recent WalletHub report list Boston as the third most caring city in the nation, while another names Massachusetts as the best U.S. state to live in. And the Bay State has excellent health care, with the highest childhood vaccination rates, lowest infant mortality and fewest premature avoidable deaths.

Want to sound just like a Bostonian? Start by dropping some of your R’s, as in “pahk the cah” and “wicked smaht.” Or listen to Ben Affleck turn on the telltale accent in his Dunkin’ commercials. Other famous Bostonians with perfect inflection include Matt Damon, Mark Wahlberg and Amy Poehler.

In: https://www.rd.com/article/happiest-cities-america-2025/ 
No trecho “a recent analysis of more than a dozen American accents conducted by BetUS Casino found that some folks’ speech actually conveys more honesty and reliability than others’,” qual palavra abaixo poderia substituir corretamente o termo reliability, mantendo o sentido da frase? 
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Q3758066 Inglês
Jadarite, described as ‘Earth's kryptonite twin,’ has potential to replace fossil fuels 

A plain-white mineral found in western Serbia has a name straight out of the comics and a chemical profile that battery makers crave. Called jadarite, also known as sodium-lithium- boron silicate hydroxide, was first pulled from drill cores in 2004 and officially recognized as a new mineral two years later. 

Geologists soon noticed that the formula on the sample label matched the faux “kryptonite” shown in a 2006 Superman film, minus the fluorine and the green glow. That pop-culture twist helped the discovery grab headlines, yet the real excitement lies in what the mineral could do for electric vehicles and renewable power storage.

Jadarite occurs as dull, chalky nodules tucked inside fine-grained shale in the Jadar Valley. The host rocks formed in an ancient lake basin rich in volcanic ash, allowing lithium and boron to build up in the pore waters until the mineral crystallized. Those conditions have been found only in Serbia so far, making the deposit both unique and strategically valuable. 

Michael Page, a process chemist at Australia’s Nuclear Science and Technology Organisation (ANSTO), points out that the valley “is considered one of the largest lithium deposits in the world, making it a potential game-changer for the global green energy transition.” […]

Serbian communities are not unanimous in welcoming the mine. Environmental groups warn that alkali-rich tailings could leak into the Jadar River and harm local agriculture. Independent studies have found elevated boron and lithium downstream of exploratory boreholes, fueling weekly protests in Belgrade.

Supporters counter that rigorous water-management plans and sealed tailings cells can limit impacts, and that the economic gains, including thousands of skilled jobs, are hard to ignore. European automakers also see the project as a chance to shorten supply chains now dominated by South American brines and Chinese refiners.

Whether or not the Jadar project reaches full production, the mineral has already altered the critical-minerals map. Its existence proves that lithium can concentrate outside traditional pegmatites and brines, broadening the hunt to basins once dismissed as uneconomic clay.

Researchers are now experimenting with synthetic pathways, seeding gels of silica, borate, and lithium under lake-like conditions to see if jadarite can be grown on demand. Success could pave the way for engineered deposits that bypass mining altogether. For now, though, nature’s one known batch in western Serbia remains the focus of intense scientific, industrial, and public scrutiny.

Adapted from https://www.earth.com/news/jadarite-described-as-earthskryptonite-twin-has-potential-to-replace-fossil-fuels/


In the fragment “a chemical profile that battery makers crave” (1st paragraph), the verb is close in meaning to
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Q3757720 Inglês
READ TEXT I AND ANSWER THE  QUESTION:

TEXT I

Products and dynamics of lava-snow explosions: The 16 March 2017 explosion at Mount Etna, Italy

Abstract

Volcanic hazards associated with lava flows advancing on snow cover are often underrated, although sudden explosions related to different processes of lava-snow/ice contact can occur rapidly and are only preceded by small, easily underrated precursors. On 16 March 2017, during a mildly effusive and explosive eruption at Mount Etna, Italy, a slowly advancing lava lobe interacted with the snow cover to produce a sudden, brief sequence of explosions. White vapor, brown ash, and coarse material were suddenly ejected, and the products struck a group of people, injuring some of them. The proximal deposit formed a continuous mantle of ash, lapilli, and decimeter-sized bombs, while the ballistic material travelled up to 200 m from the lava edge. The deposit was estimated to have a mass of 7.1 ± 0.8 × 104 kg, which corresponds to a volume of 32.0 ± 3.6 m3 of lava being removed by the explosion. Data related to the texture and morphology of the ejected clasts were used to constrain a model of lava-snow interaction. The results suggest that the mechanism causing the explosions was the progressive build-up of pressure due to vapor accumulation under the lava flow, while no evidence was found for the occurrence of fuel-coolant interaction processes. Although these low-intensity explosions are not particularly frequent, the data set collected provides, for the first time, quantitative information about the processes involved and the associated hazard and suggests that mitigation measures should be established to prevent potentially dramatic accidents at worldwide volcanoes frequented by tourists and with fairly easy access, such as Etna.

Source: GSA Bulletin (2024) 136 (5-6): 2325–2342. Available at https://pubs.geoscienceworld.org/gsa/gsabulletin/article/136/5- 6/2325/628546/Products-and-dynamics-of-lava-snow-explosions-The
In the fragment “a mildly effusive and explosive eruption”, the adverb is comparable in meaning to
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Q3748901 Inglês
        Since the 1950s, researchers, inventors and entrepreneurs have been fascinated by the idea of Artificial Intelligence (AI) to replicate human behaviour and thinking into technology. Over time AI has evolved to mimic human behaviour in information technology (IT) with key milestones like machine learning, natural language processing and understanding, generative AI and orchestrating decision making and now the latest advancement: agentic AI.

        Today, AI is not just a technology but a critical part of modern IT strategies. AI in the IT industry has been a transformative force, automating tasks, analysing vast amounts of data and improving operational processes. By using AI for ITSM, organisations can adapt to a changing technology landscape and complex digital environments and keep their IT infrastructure future proof.

        AI has come a long way from theory to software to recent innovations like machine learning (ML). ML is about developing AI algorithms and models that help systems learn and make decisions based on patterns and relationships in data. Instead of programming each decision manually, systems can make decisions on their own based on large amounts of data. Continuous learning on data allows systems to get better over time. At the next level is natural language processing (NLP), a branch of machine learning that’s about interpreting human language and generating intelligent and contextual responses. By using ML algorithms on language, machines can do things like response generation, speech recognition, language translation and more. NLP is the foundation for modern day chatbots that can understand user intent and generate responses to user requests.

         AI is revolutionizing ITSM by introducing innovative solutions such as an AI service desk that enhances IT operations. With automated ticket triaging, routing, deflection, and process automation, organizations can streamline tasks that IT agents encounter daily.

        By providing agents with agent assist capabilities and an AI Copilot, organizations can reduce redundant and repetitive service tasks and improve productivity, thereby minimizing the need for human intervention in these repetitive tasks. With AIOps, organizations can also stay ahead of potential incidents and outages with proactive detection and remediation, as well as automated incident management.

        AI also plays a big role in software development and testing. It helps quality assurance teams by generating test cases and predicting defects. This means they can catch and fix bugs much earlier which prevents bigger issues down the line. When it comes to data center security, computer vision is a powerful tool. It allows systems to analyze images and videos to monitor infrastructure and spot anything unusual. Additionally, machine learning models can analyze network traffic in real time to detect cyber threats and fraud and allow teams to respond quickly and protect their systems.

Internet:<aisera.com>  (adapted).
In the period “Over time AI has evolved to mimic human behaviour in information technology (IT) with key milestones like machine learning,” the word “milestones” could be replaced, without affecting meaning, by
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Q3747543 Inglês







The Design Thinking Classroom: Using Design Thinking to Reimagine the Role and Practice of Educators (English Edition)


By David Jakes (Author) | ☆☆☆☆☆


A Design-Oriented Approach That Can Best Serve Today's Students and Educators Alike

How can we make schools more relevant, engaging, and capable of supporting the development of skills and dispositions that will help students themselves design a life worth living?

Drawing from his ample experience in the classroom, as a school administrator, and as a designer, author David Jakes makes the case that design thinking offers an approach to education that is responsive, collaborative, and well-suited to the opportunities of the twenty-first century. Full of exercises and suggestions for how design thinking can change educators’ approach to classroom layout, virtual learning, assessment, and more, this book shows how we can make today's classrooms better places to teach and learn.

The Design Thinking Classroom helps create the conditions for K–12 teachers and school leaders to innovate and improve a new kind of educational experience. It’s a book for readers who are invested in rising to the challenges faced by modern institutions and a powerful argument for the ways design thinking can transform education.


Excerpt extracted and adapted from: https://www.amazon.com.br/Design-Thinking-Classroom-ReimagineEducators-ebook/dp/B0BR8MPY76?ref_=ast_author_mpb
Considering the following excerpt extracted from Text 1, where it says “A Design-Oriented Approach That Can Best Serve Today's Students and Educators Alike”, the underlined word (“Alike”) can be correctly replaced (preserving its original meaning and use in its original context) by:
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Q3743509 Inglês

Texto: Challenges in Global Education Systems



    Education is a fundamental pillar of societal development, but many global education systems face significant challenges that hinder their ability to provide equal and quality learning opportunities. These challenges vary from country to country but share common themes such as inequality, lack of resources, outdated curricula, and the rapid pace of technological change.

    One of the most pressing challenges in global education systems is inequality. In many parts of the world, access to quality education is not universal, and disparities in educational opportunities persist along socioeconomic, geographic, and gender lines. In low-income countries, educational infrastructure may be underdeveloped, with inadequate classrooms, outdated textbooks, and insufficient access to digital technologies. Rural areas often face more severe challenges, with limited access to schools or well-trained teachers. Similarly, marginalized communities — such as girls in some parts of Africa or indigenous populations — face cultural and societal barriers that prevent them from accessing education. In wealthier countries, while access to education may not be an issue, disparities remain within local communities, particularly in urban areas. Students from lowerincome backgrounds may face challenges in accessing tutoring, extracurricular activities, and the technology required for modern learning. Addressing these inequities is crucial to ensuring that all students have the opportunity to succeed.

    Another significant challenge in global education systems is the outdated nature of curricula and teaching methods. In many cases, education systems are still based on models from the 19th or 20th centuries, designed to meet the needs of an industrialized economy rather than a knowledge-based, technology-driven society. Traditional curricula often emphasize rote learning and memorization rather than critical thinking, creativity, and problem-solving — skills that are essential in today’s globalized world. Moreover, teaching methods may be rigid, focusing on passive learning rather than active student engagement. This makes it difficult for students to develop the skills necessary to thrive in modern workplaces, where adaptability, innovation, and collaboration are highly valued.

    In many parts of the world, education systems have been slow to adapt to the integration of digital technologies and 21st-century learning strategies. Without updating curricula to reflect the demands of the modern world, students may leave school without the skills needed to succeed in higher education or the workforce. A lack of effective teacher training is another challenge that impacts global education systems. Teachers are the heart of any educational system, and their ability to deliver quality instruction directly affects student outcomes.

    In recent years, technology has become a critical part of the education system. However, the digital divide remains a significant barrier to achieving global educational equity. While students in wealthier countries have easy access to digital tools, high-speed internet, and online resources, students in low-income or rural areas often lack access to the necessary technology. The COVID19 pandemic highlighted these disparities, as many students in underserved communities struggled with remote learning due to limited access to devices or reliable internet connections. The digital divide not only limits access to education but also prevents students from gaining essential digital skills that are crucial in today’s job market.

    The pressures of academic performance, social media, and external expectations can take a toll on students’ mental well-being. In highpressure educational systems, students may experience stress, anxiety, and burnout, which can hinder their ability to focus, learn, and succeed. Additionally, a lack of access to mental health resources or support services further exacerbates these issues. Teachers, too, face significant mental health challenges. The demands of managing large classrooms, addressing diverse learning needs, and meeting educational standards can lead to burnout and job dissatisfaction. Addressing mental health and well-being for both students and educators is essential for creating a healthy and effective learning environment.

    In conclusion, the challenges faced by global education systems are multifaceted and complex, ranging from inequality and outdated curricula to teacher training and the digital divide. These challenges impact not only the quality of education but also the future success and wellbeing of students. To overcome these issues, it is crucial for governments, educational institutions, and communities to collaborate on innovative solutions that address the root causes of these challenges. By investing in equitable access to education, updating curricula, enhancing teacher training, and integrating technology, we can create a more inclusive and effective global education system that equips students for success in an increasingly interconnected world.



Taken and adapted from:

https://portaleducoas.org/challenges-in-globaleducation-systems/

In paragraph 6, the word “hinder” most nearly means:  
Alternativas
Q3740345 Inglês

Read the text to answer the question.



     A recent Executive Order by President Biden emphasized the link between racial equity, education, and artificial intelligence (AI). It stated that the Federal Government must both pursue educational equity and eliminate bias in the design and use of new technologies, such as AI.


     The U.S. Department of Education’s report Advancing Digital Equity for All defines digital equity as the condition in which individuals and technological communities capacity needed have the for full participation in society and the economy.  


     Concerns about racial equity and bias are central to the debate on AI in education. AI systems rely on datasets, and when these datasets are non-representative or contain biased patterns, the resulting models may behave unfairly. Such systematic unfairness in automated decisions is known as algorithmic bias, which can lead to discrimination and undermine equity at scale.


     Bias is intrinsic to how AI algorithms are trained on historical data. When these biases sustain unjust or discriminatory practices in education, they must be identified and addressed. For instance, algorithms used for admissions, early intervention, or exam monitoring should be regularly evaluated for evidence of unfair bias, not only during design but also as they are deployed in real educational contexts. 


U.S. Department of Education, Office of Educational

Technology. (2023). Artificial Intelligence and the Future of

Teaching and Learning: Insights and Recommendations.

Washington, DC: U.S.

In the expression “Such systematic unfairness in automated decisions is known as algorithmic bias”, the word ‘unfairness’ could be replaced without altering the idea by: 
Alternativas
Q3740341 Inglês

Read the text to answer the question.



     A recent Executive Order by President Biden emphasized the link between racial equity, education, and artificial intelligence (AI). It stated that the Federal Government must both pursue educational equity and eliminate bias in the design and use of new technologies, such as AI.


     The U.S. Department of Education’s report Advancing Digital Equity for All defines digital equity as the condition in which individuals and technological communities capacity needed have the for full participation in society and the economy.  


     Concerns about racial equity and bias are central to the debate on AI in education. AI systems rely on datasets, and when these datasets are non-representative or contain biased patterns, the resulting models may behave unfairly. Such systematic unfairness in automated decisions is known as algorithmic bias, which can lead to discrimination and undermine equity at scale.


     Bias is intrinsic to how AI algorithms are trained on historical data. When these biases sustain unjust or discriminatory practices in education, they must be identified and addressed. For instance, algorithms used for admissions, early intervention, or exam monitoring should be regularly evaluated for evidence of unfair bias, not only during design but also as they are deployed in real educational contexts. 


U.S. Department of Education, Office of Educational

Technology. (2023). Artificial Intelligence and the Future of

Teaching and Learning: Insights and Recommendations.

Washington, DC: U.S.

In the phrase “AI systems rely on datasets”, the word rely could be replaced without changing the meaning by:
Alternativas
Respostas
101: C
102: A
103: D
104: B
105: C
106: D
107: A
108: B
109: C
110: E
111: E
112: E
113: B
114: B
115: B
116: D
117: A
118: B
119: A
120: C