Questões Militares Sobre inglês
Foram encontradas 4.456 questões
Leia os diálogos, para responder à questão.
Text 1: Making a doctor’s appointment
(telephone rings)
Patient: Could I make an appointment to see the doctor, please?
Receptionist: Certainly, who do you usually see?
Patient: Dr Cullen.
Receptionist: I’m sorry but Dr Cullen has got patients all day.
Would Dr Maley do?
Patient: Sure.
Receptionist: OK then. When would you like to come?
Patient: Could I come at four o’clock?
Receptionist: Four o’clock? Fine. Could I have your name, please?
(Nunan and Lockwood 1991)
Text 2: Confirming an appointment with the doctor (telephone rings)
Receptionist: Doctor’s rooms, can you hold the line for a
moment?
Patient: Yes.
Receptionist: (pause) Thanks.
Receptionist: Hello.
Patient: Hello.
Patient: That’s all right … I’m just calling to confirm an appointment with Dr X for the first of October. Receptionist: Oh …
Patient: Because it was so far in advance I was told to.
Receptionist: I see what you mean, to see if she’s going to be
in that day.
Patient: That’s right.
Receptionist: Oh we may not know yet.
Patient: Oh I see.
Receptionist: First of October … Edith … yes.
Patient: Yes.
Receptionist: There she is. OK.. What’s your name?
Patient: At nine fift…
Receptionist: Got it got it.
(Burns, Joyce and Gollin 1996)
(Carter, Ronald et al. Telling tails: grammar, the spoken language and
materials development. In Tomlinson, B. (ed). Material Development in
Language Teaching. Cambridge: CUP. 1998/2011. Adaptado)
Considere a seguinte gravura e seu texto para responder à questão.
The content of the answer provided by the internet could be an integral part of an English reading class to discuss issues directly related to the
Leia o texto para responder à questão.
AI tech products at schools and universities
Every few years, an emerging technology shows up at the doorstep of schools and universities promising to transform education. The most recent? Technologies powered by generative artificial intelligence, also known as GenAI. These technologies are sold on the potential they hold for education. As optimistic as these visions of the future may be, the realities of educational technology over the past few decades have not lived up to their promises, as shown by rigorous investigations of technology after technology – from mechanical machines to computers, from mobile devices to massive open online courses.
Yet, educational technology evangelists forget, remain unaware or simply do not care. Or they may be overly optimistic that the next new technology will be different than before.
Here are four questions I believe should be answered before school officials purchase any technology that relies on AI.
1. Is there evidence that a product works?
Compelling evidence of the effect of GenAI products on educational outcomes does not yet exist. Therefore, and unfortunately, it is the consumer who carries the onus of appraising products. My recommendation is: use multiple means for assessing product effectiveness.
2. [...]
Oftentimes, there is a divide between what entrepreneurs build and educators need. For example, one shortcoming of the One Laptop Per Child program – an ambitious program that sought to put small, cheap but sturdy laptops in the hands of children from families of lesser means – is that the laptops were designed for idealized younger versions of the developers themselves, not so much the children who were actually using them.
Initiatives have been implemented in which entrepreneurs and educators work together to improve educational technology products. Some products are developed with input from students and educators. Questions to ask vendors might be: In what ways were educators and learners included? How did their input influence the final product?
3. What educational beliefs shape this product?
Educational technology is rarely neutral. It is designed by people, and people have beliefs, experiences, ideologies and biases that shape the technologies they develop.
It is important for educational technology products to rely on what educators have experienced as relevant to the students they meet in their real-life classes. Questions to ask include: What pedagogical principles guide this product? What particular learning does it support or discourage?
4. Does the product level the playing field?
Finally, people ought to ask how a product addresses educational inequities. Is this technology going to help reduce the learning gaps between different groups of learners? Or is it one that aids some learners – often those who are already successful or privileged – but not others? Is it adopting an asset-based or a deficit-based approach to addressing inequities?
Educational technology vendors and startups may not have answers to all of these questions. But they should still be asked and considered. Answers could lead to improved products.
(George Veletsianos. https://theconversation.com, 15.04.24. Adaptado)
Words ending in –ing may play a variety of roles in the English sentence. The word in bold is an adjective in alternative:
Leia o texto para responder à questão.
AI tech products at schools and universities
Every few years, an emerging technology shows up at the doorstep of schools and universities promising to transform education. The most recent? Technologies powered by generative artificial intelligence, also known as GenAI. These technologies are sold on the potential they hold for education. As optimistic as these visions of the future may be, the realities of educational technology over the past few decades have not lived up to their promises, as shown by rigorous investigations of technology after technology – from mechanical machines to computers, from mobile devices to massive open online courses.
Yet, educational technology evangelists forget, remain unaware or simply do not care. Or they may be overly optimistic that the next new technology will be different than before.
Here are four questions I believe should be answered before school officials purchase any technology that relies on AI.
1. Is there evidence that a product works?
Compelling evidence of the effect of GenAI products on educational outcomes does not yet exist. Therefore, and unfortunately, it is the consumer who carries the onus of appraising products. My recommendation is: use multiple means for assessing product effectiveness.
2. [...]
Oftentimes, there is a divide between what entrepreneurs build and educators need. For example, one shortcoming of the One Laptop Per Child program – an ambitious program that sought to put small, cheap but sturdy laptops in the hands of children from families of lesser means – is that the laptops were designed for idealized younger versions of the developers themselves, not so much the children who were actually using them.
Initiatives have been implemented in which entrepreneurs and educators work together to improve educational technology products. Some products are developed with input from students and educators. Questions to ask vendors might be: In what ways were educators and learners included? How did their input influence the final product?
3. What educational beliefs shape this product?
Educational technology is rarely neutral. It is designed by people, and people have beliefs, experiences, ideologies and biases that shape the technologies they develop.
It is important for educational technology products to rely on what educators have experienced as relevant to the students they meet in their real-life classes. Questions to ask include: What pedagogical principles guide this product? What particular learning does it support or discourage?
4. Does the product level the playing field?
Finally, people ought to ask how a product addresses educational inequities. Is this technology going to help reduce the learning gaps between different groups of learners? Or is it one that aids some learners – often those who are already successful or privileged – but not others? Is it adopting an asset-based or a deficit-based approach to addressing inequities?
Educational technology vendors and startups may not have answers to all of these questions. But they should still be asked and considered. Answers could lead to improved products.
(George Veletsianos. https://theconversation.com, 15.04.24. Adaptado)
Leia as duas perguntas e a afirmação a seguir.
– “In what ways were educators or learners included?” (parágrafo 6)
– “How did their input influence the final product?” (parágrafo 6)
– “It is important for educational technology products to rely on what educators have experienced as relevant to the students they meet in their real-life classes.” (parágrafo 7)
Em seu conjunto, as três citações refletem a preocupação do autor do texto em valorizar o professor no que concerne
Leia o texto para responder à questão.
AI tech products at schools and universities
Every few years, an emerging technology shows up at the doorstep of schools and universities promising to transform education. The most recent? Technologies powered by generative artificial intelligence, also known as GenAI. These technologies are sold on the potential they hold for education. As optimistic as these visions of the future may be, the realities of educational technology over the past few decades have not lived up to their promises, as shown by rigorous investigations of technology after technology – from mechanical machines to computers, from mobile devices to massive open online courses.
Yet, educational technology evangelists forget, remain unaware or simply do not care. Or they may be overly optimistic that the next new technology will be different than before.
Here are four questions I believe should be answered before school officials purchase any technology that relies on AI.
1. Is there evidence that a product works?
Compelling evidence of the effect of GenAI products on educational outcomes does not yet exist. Therefore, and unfortunately, it is the consumer who carries the onus of appraising products. My recommendation is: use multiple means for assessing product effectiveness.
2. [...]
Oftentimes, there is a divide between what entrepreneurs build and educators need. For example, one shortcoming of the One Laptop Per Child program – an ambitious program that sought to put small, cheap but sturdy laptops in the hands of children from families of lesser means – is that the laptops were designed for idealized younger versions of the developers themselves, not so much the children who were actually using them.
Initiatives have been implemented in which entrepreneurs and educators work together to improve educational technology products. Some products are developed with input from students and educators. Questions to ask vendors might be: In what ways were educators and learners included? How did their input influence the final product?
3. What educational beliefs shape this product?
Educational technology is rarely neutral. It is designed by people, and people have beliefs, experiences, ideologies and biases that shape the technologies they develop.
It is important for educational technology products to rely on what educators have experienced as relevant to the students they meet in their real-life classes. Questions to ask include: What pedagogical principles guide this product? What particular learning does it support or discourage?
4. Does the product level the playing field?
Finally, people ought to ask how a product addresses educational inequities. Is this technology going to help reduce the learning gaps between different groups of learners? Or is it one that aids some learners – often those who are already successful or privileged – but not others? Is it adopting an asset-based or a deficit-based approach to addressing inequities?
Educational technology vendors and startups may not have answers to all of these questions. But they should still be asked and considered. Answers could lead to improved products.
(George Veletsianos. https://theconversation.com, 15.04.24. Adaptado)
Leia o texto para responder à questão.
AI tech products at schools and universities
Every few years, an emerging technology shows up at the doorstep of schools and universities promising to transform education. The most recent? Technologies powered by generative artificial intelligence, also known as GenAI. These technologies are sold on the potential they hold for education. As optimistic as these visions of the future may be, the realities of educational technology over the past few decades have not lived up to their promises, as shown by rigorous investigations of technology after technology – from mechanical machines to computers, from mobile devices to massive open online courses.
Yet, educational technology evangelists forget, remain unaware or simply do not care. Or they may be overly optimistic that the next new technology will be different than before.
Here are four questions I believe should be answered before school officials purchase any technology that relies on AI.
1. Is there evidence that a product works?
Compelling evidence of the effect of GenAI products on educational outcomes does not yet exist. Therefore, and unfortunately, it is the consumer who carries the onus of appraising products. My recommendation is: use multiple means for assessing product effectiveness.
2. [...]
Oftentimes, there is a divide between what entrepreneurs build and educators need. For example, one shortcoming of the One Laptop Per Child program – an ambitious program that sought to put small, cheap but sturdy laptops in the hands of children from families of lesser means – is that the laptops were designed for idealized younger versions of the developers themselves, not so much the children who were actually using them.
Initiatives have been implemented in which entrepreneurs and educators work together to improve educational technology products. Some products are developed with input from students and educators. Questions to ask vendors might be: In what ways were educators and learners included? How did their input influence the final product?
3. What educational beliefs shape this product?
Educational technology is rarely neutral. It is designed by people, and people have beliefs, experiences, ideologies and biases that shape the technologies they develop.
It is important for educational technology products to rely on what educators have experienced as relevant to the students they meet in their real-life classes. Questions to ask include: What pedagogical principles guide this product? What particular learning does it support or discourage?
4. Does the product level the playing field?
Finally, people ought to ask how a product addresses educational inequities. Is this technology going to help reduce the learning gaps between different groups of learners? Or is it one that aids some learners – often those who are already successful or privileged – but not others? Is it adopting an asset-based or a deficit-based approach to addressing inequities?
Educational technology vendors and startups may not have answers to all of these questions. But they should still be asked and considered. Answers could lead to improved products.
(George Veletsianos. https://theconversation.com, 15.04.24. Adaptado)
Observe a palavra destacada em negrito nas duas frases a seguir:
I. “Yet, educational technologist evangelists forget, remain unaware or simply do not care.” (parágrafo 2)
II. “Compelling evidence of the effect of GenAI products on educational outcomes does not yet exist” (parágrafo 5).
O uso da palavra yet está corretamente explicado na alternativa:
Leia o texto para responder à questão.
AI tech products at schools and universities
Every few years, an emerging technology shows up at the doorstep of schools and universities promising to transform education. The most recent? Technologies powered by generative artificial intelligence, also known as GenAI. These technologies are sold on the potential they hold for education. As optimistic as these visions of the future may be, the realities of educational technology over the past few decades have not lived up to their promises, as shown by rigorous investigations of technology after technology – from mechanical machines to computers, from mobile devices to massive open online courses.
Yet, educational technology evangelists forget, remain unaware or simply do not care. Or they may be overly optimistic that the next new technology will be different than before.
Here are four questions I believe should be answered before school officials purchase any technology that relies on AI.
1. Is there evidence that a product works?
Compelling evidence of the effect of GenAI products on educational outcomes does not yet exist. Therefore, and unfortunately, it is the consumer who carries the onus of appraising products. My recommendation is: use multiple means for assessing product effectiveness.
2. [...]
Oftentimes, there is a divide between what entrepreneurs build and educators need. For example, one shortcoming of the One Laptop Per Child program – an ambitious program that sought to put small, cheap but sturdy laptops in the hands of children from families of lesser means – is that the laptops were designed for idealized younger versions of the developers themselves, not so much the children who were actually using them.
Initiatives have been implemented in which entrepreneurs and educators work together to improve educational technology products. Some products are developed with input from students and educators. Questions to ask vendors might be: In what ways were educators and learners included? How did their input influence the final product?
3. What educational beliefs shape this product?
Educational technology is rarely neutral. It is designed by people, and people have beliefs, experiences, ideologies and biases that shape the technologies they develop.
It is important for educational technology products to rely on what educators have experienced as relevant to the students they meet in their real-life classes. Questions to ask include: What pedagogical principles guide this product? What particular learning does it support or discourage?
4. Does the product level the playing field?
Finally, people ought to ask how a product addresses educational inequities. Is this technology going to help reduce the learning gaps between different groups of learners? Or is it one that aids some learners – often those who are already successful or privileged – but not others? Is it adopting an asset-based or a deficit-based approach to addressing inequities?
Educational technology vendors and startups may not have answers to all of these questions. But they should still be asked and considered. Answers could lead to improved products.
(George Veletsianos. https://theconversation.com, 15.04.24. Adaptado)
Leia o texto para responder à questão.
AI tech products at schools and universities
Every few years, an emerging technology shows up at the doorstep of schools and universities promising to transform education. The most recent? Technologies powered by generative artificial intelligence, also known as GenAI. These technologies are sold on the potential they hold for education. As optimistic as these visions of the future may be, the realities of educational technology over the past few decades have not lived up to their promises, as shown by rigorous investigations of technology after technology – from mechanical machines to computers, from mobile devices to massive open online courses.
Yet, educational technology evangelists forget, remain unaware or simply do not care. Or they may be overly optimistic that the next new technology will be different than before.
Here are four questions I believe should be answered before school officials purchase any technology that relies on AI.
1. Is there evidence that a product works?
Compelling evidence of the effect of GenAI products on educational outcomes does not yet exist. Therefore, and unfortunately, it is the consumer who carries the onus of appraising products. My recommendation is: use multiple means for assessing product effectiveness.
2. [...]
Oftentimes, there is a divide between what entrepreneurs build and educators need. For example, one shortcoming of the One Laptop Per Child program – an ambitious program that sought to put small, cheap but sturdy laptops in the hands of children from families of lesser means – is that the laptops were designed for idealized younger versions of the developers themselves, not so much the children who were actually using them.
Initiatives have been implemented in which entrepreneurs and educators work together to improve educational technology products. Some products are developed with input from students and educators. Questions to ask vendors might be: In what ways were educators and learners included? How did their input influence the final product?
3. What educational beliefs shape this product?
Educational technology is rarely neutral. It is designed by people, and people have beliefs, experiences, ideologies and biases that shape the technologies they develop.
It is important for educational technology products to rely on what educators have experienced as relevant to the students they meet in their real-life classes. Questions to ask include: What pedagogical principles guide this product? What particular learning does it support or discourage?
4. Does the product level the playing field?
Finally, people ought to ask how a product addresses educational inequities. Is this technology going to help reduce the learning gaps between different groups of learners? Or is it one that aids some learners – often those who are already successful or privileged – but not others? Is it adopting an asset-based or a deficit-based approach to addressing inequities?
Educational technology vendors and startups may not have answers to all of these questions. But they should still be asked and considered. Answers could lead to improved products.
(George Veletsianos. https://theconversation.com, 15.04.24. Adaptado)
Another very relevant reading ability to be developed in students is that of recognizing the gist of a text, or of a self-contained part of a text. A teacher’s instruction to help develop this ability would include asking the students to reread subitem 2 and provide a subtitle that both shows their understanding of the excerpt and corresponds to the way the text has been structured.
One correct subtitle would be:
Leia o texto para responder à questão.
AI tech products at schools and universities
Every few years, an emerging technology shows up at the doorstep of schools and universities promising to transform education. The most recent? Technologies powered by generative artificial intelligence, also known as GenAI. These technologies are sold on the potential they hold for education. As optimistic as these visions of the future may be, the realities of educational technology over the past few decades have not lived up to their promises, as shown by rigorous investigations of technology after technology – from mechanical machines to computers, from mobile devices to massive open online courses.
Yet, educational technology evangelists forget, remain unaware or simply do not care. Or they may be overly optimistic that the next new technology will be different than before.
Here are four questions I believe should be answered before school officials purchase any technology that relies on AI.
1. Is there evidence that a product works?
Compelling evidence of the effect of GenAI products on educational outcomes does not yet exist. Therefore, and unfortunately, it is the consumer who carries the onus of appraising products. My recommendation is: use multiple means for assessing product effectiveness.
2. [...]
Oftentimes, there is a divide between what entrepreneurs build and educators need. For example, one shortcoming of the One Laptop Per Child program – an ambitious program that sought to put small, cheap but sturdy laptops in the hands of children from families of lesser means – is that the laptops were designed for idealized younger versions of the developers themselves, not so much the children who were actually using them.
Initiatives have been implemented in which entrepreneurs and educators work together to improve educational technology products. Some products are developed with input from students and educators. Questions to ask vendors might be: In what ways were educators and learners included? How did their input influence the final product?
3. What educational beliefs shape this product?
Educational technology is rarely neutral. It is designed by people, and people have beliefs, experiences, ideologies and biases that shape the technologies they develop.
It is important for educational technology products to rely on what educators have experienced as relevant to the students they meet in their real-life classes. Questions to ask include: What pedagogical principles guide this product? What particular learning does it support or discourage?
4. Does the product level the playing field?
Finally, people ought to ask how a product addresses educational inequities. Is this technology going to help reduce the learning gaps between different groups of learners? Or is it one that aids some learners – often those who are already successful or privileged – but not others? Is it adopting an asset-based or a deficit-based approach to addressing inequities?
Educational technology vendors and startups may not have answers to all of these questions. But they should still be asked and considered. Answers could lead to improved products.
(George Veletsianos. https://theconversation.com, 15.04.24. Adaptado)
Leia o texto e o gráfico para responder à questão.
The 2020s have brought a degree of chaos not seen in decades. A pandemic was followed by a full-scale war in Europe; both sent food and fuel prices surging. Extreme weather events have shown that climate change is beginning to bite. The phrase “unprecedented times” soon sounded too common.
This all affected the global standards of living. One measure of this, the United Nations’ Human Development Index (HDI), fell in 2020 for the first time since its launch. It fell again in 2021. The HDI is one of the most widely used measures of countries’ development, after the Gross Domestic Product (GDP). It is not complete, though. It does not account for economic inequality, for example, or disparities between ethnicities and genders.
The latest figures show that the global HDI is rising again, but progress has been slow and uneven. It seems the long-term trend appears to have suffered a permanent setback since the pandemic. This setback will deeply affect the world’s poorest.
Yet there are reasons for hope. The chaos of the 2020s has also shown that governments can collaborate on some big issues. During the pandemic, vaccines were developed, produced and distributed at remarkable speed, saving an estimated 20 million lives in their first year alone. At the 28th United Nations Climate Change Conference (COP28) in 2023 the world proved that it could agree on a deal to tackle climate change (even if fulfilling it is another matter). More of that will be needed to overcome the setbacks from the start of the decade.
Leia o texto e o gráfico para responder à questão.
The 2020s have brought a degree of chaos not seen in decades. A pandemic was followed by a full-scale war in Europe; both sent food and fuel prices surging. Extreme weather events have shown that climate change is beginning to bite. The phrase “unprecedented times” soon sounded too common.
This all affected the global standards of living. One measure of this, the United Nations’ Human Development Index (HDI), fell in 2020 for the first time since its launch. It fell again in 2021. The HDI is one of the most widely used measures of countries’ development, after the Gross Domestic Product (GDP). It is not complete, though. It does not account for economic inequality, for example, or disparities between ethnicities and genders.
The latest figures show that the global HDI is rising again, but progress has been slow and uneven. It seems the long-term trend appears to have suffered a permanent setback since the pandemic. This setback will deeply affect the world’s poorest.
Yet there are reasons for hope. The chaos of the 2020s has also shown that governments can collaborate on some big issues. During the pandemic, vaccines were developed, produced and distributed at remarkable speed, saving an estimated 20 million lives in their first year alone. At the 28th United Nations Climate Change Conference (COP28) in 2023 the world proved that it could agree on a deal to tackle climate change (even if fulfilling it is another matter). More of that will be needed to overcome the setbacks from the start of the decade.
Leia o texto e o gráfico para responder à questão.
The 2020s have brought a degree of chaos not seen in decades. A pandemic was followed by a full-scale war in Europe; both sent food and fuel prices surging. Extreme weather events have shown that climate change is beginning to bite. The phrase “unprecedented times” soon sounded too common.
This all affected the global standards of living. One measure of this, the United Nations’ Human Development Index (HDI), fell in 2020 for the first time since its launch. It fell again in 2021. The HDI is one of the most widely used measures of countries’ development, after the Gross Domestic Product (GDP). It is not complete, though. It does not account for economic inequality, for example, or disparities between ethnicities and genders.
The latest figures show that the global HDI is rising again, but progress has been slow and uneven. It seems the long-term trend appears to have suffered a permanent setback since the pandemic. This setback will deeply affect the world’s poorest.
Yet there are reasons for hope. The chaos of the 2020s has also shown that governments can collaborate on some big issues. During the pandemic, vaccines were developed, produced and distributed at remarkable speed, saving an estimated 20 million lives in their first year alone. At the 28th United Nations Climate Change Conference (COP28) in 2023 the world proved that it could agree on a deal to tackle climate change (even if fulfilling it is another matter). More of that will be needed to overcome the setbacks from the start of the decade.
Leia o texto e o gráfico para responder à questão.
The 2020s have brought a degree of chaos not seen in decades. A pandemic was followed by a full-scale war in Europe; both sent food and fuel prices surging. Extreme weather events have shown that climate change is beginning to bite. The phrase “unprecedented times” soon sounded too common.
This all affected the global standards of living. One measure of this, the United Nations’ Human Development Index (HDI), fell in 2020 for the first time since its launch. It fell again in 2021. The HDI is one of the most widely used measures of countries’ development, after the Gross Domestic Product (GDP). It is not complete, though. It does not account for economic inequality, for example, or disparities between ethnicities and genders.
The latest figures show that the global HDI is rising again, but progress has been slow and uneven. It seems the long-term trend appears to have suffered a permanent setback since the pandemic. This setback will deeply affect the world’s poorest.
Yet there are reasons for hope. The chaos of the 2020s has also shown that governments can collaborate on some big issues. During the pandemic, vaccines were developed, produced and distributed at remarkable speed, saving an estimated 20 million lives in their first year alone. At the 28th United Nations Climate Change Conference (COP28) in 2023 the world proved that it could agree on a deal to tackle climate change (even if fulfilling it is another matter). More of that will be needed to overcome the setbacks from the start of the decade.
Leia o texto e o gráfico para responder à questão.
The 2020s have brought a degree of chaos not seen in decades. A pandemic was followed by a full-scale war in Europe; both sent food and fuel prices surging. Extreme weather events have shown that climate change is beginning to bite. The phrase “unprecedented times” soon sounded too common.
This all affected the global standards of living. One measure of this, the United Nations’ Human Development Index (HDI), fell in 2020 for the first time since its launch. It fell again in 2021. The HDI is one of the most widely used measures of countries’ development, after the Gross Domestic Product (GDP). It is not complete, though. It does not account for economic inequality, for example, or disparities between ethnicities and genders.
The latest figures show that the global HDI is rising again, but progress has been slow and uneven. It seems the long-term trend appears to have suffered a permanent setback since the pandemic. This setback will deeply affect the world’s poorest.
Yet there are reasons for hope. The chaos of the 2020s has also shown that governments can collaborate on some big issues. During the pandemic, vaccines were developed, produced and distributed at remarkable speed, saving an estimated 20 million lives in their first year alone. At the 28th United Nations Climate Change Conference (COP28) in 2023 the world proved that it could agree on a deal to tackle climate change (even if fulfilling it is another matter). More of that will be needed to overcome the setbacks from the start of the decade.
Leia o texto e o gráfico para responder à questão.
The 2020s have brought a degree of chaos not seen in decades. A pandemic was followed by a full-scale war in Europe; both sent food and fuel prices surging. Extreme weather events have shown that climate change is beginning to bite. The phrase “unprecedented times” soon sounded too common.
This all affected the global standards of living. One measure of this, the United Nations’ Human Development Index (HDI), fell in 2020 for the first time since its launch. It fell again in 2021. The HDI is one of the most widely used measures of countries’ development, after the Gross Domestic Product (GDP). It is not complete, though. It does not account for economic inequality, for example, or disparities between ethnicities and genders.
The latest figures show that the global HDI is rising again, but progress has been slow and uneven. It seems the long-term trend appears to have suffered a permanent setback since the pandemic. This setback will deeply affect the world’s poorest.
Yet there are reasons for hope. The chaos of the 2020s has also shown that governments can collaborate on some big issues. During the pandemic, vaccines were developed, produced and distributed at remarkable speed, saving an estimated 20 million lives in their first year alone. At the 28th United Nations Climate Change Conference (COP28) in 2023 the world proved that it could agree on a deal to tackle climate change (even if fulfilling it is another matter). More of that will be needed to overcome the setbacks from the start of the decade.
Since the first ascent in 1953, many climbers have left trash behind. The Nepal government-funded team removed 11 tons of garbage, four dead bodies, and a skeleton during this year's climbing season. Ang Babu Sherpa, the team leader, estimates there might be 40-50 tons of garbage still at South Col, the last camp before the summit. The trash includes old tents, food packaging, gas cartridges, oxygen bottles, and ropes. The garbage is layered and frozen at 8,000 meters altitude. Although recent rules and awareness have reduced new garbage, most of the trash is from older expeditions.
Cleaning is difficult due to harsh weather, low oxygen levels, and the garbage frozen in ice. Of the 11 tons removed, three were decomposable and taken to nearby villages, while eight were transported to Kathmandu for recycling. The oldest item found was a battery from 1957.
Disponível em: https://www.newsinlevels.com/.
Textual interpretation, in general, refers to the process of understanding, analyzing, and deriving meaning from written texts. It is a key skill and requires careful reading, critical thinking, and an appreciation for the nuance and complexity of the text and the context. In this sense, according to the text, choose the correct alternative.
Conheça nossos planos