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2018雅思阅读素材:科技和教育引领学习

2018年04月08日 11:14:56来源:雅思考试网
导读:备考雅思考试的过程中,在掌握了考试技巧的基础上再多做一些阅读练习对于提成绩是非常有效的。下面小编给大家推荐几篇阅读练习,以帮助大家可以节省找复习资料的时间,能更高效的把时间放在复习题上。

>>雅思阅读精选练习:2018雅思阅读素材:科技和教育引领学习

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It is easy to say that people need to keep learning throughout their careers. The practicalities are daunting

WHEN education fails to keep pace with technology, the result is inequality. Without the skills to stay useful as innovations arrive, workers suffer—and if enough of them fall behind, society starts to fall apart. That fundamental insight seized reformers in the Industrial revolution, heralding state-funded universal schooling. Later, automation in factories and offices called forth a surge in college graduates. The combination of education and innovation, spread over decades, led to a remarkable flowering of prosperity.

当教育跟不上技术进步时,就会造成不平等。在创新到来之际,工人如果没有技能使自己对雇主仍然“有用”,他们就会遭殃。而如果落后的工人太多,社会就开始崩塌。这一根本性的洞见极大影响了工业革命时期的改革者,推动了国家资助全民教育的普及。后来,工厂和办公室自动化又引发了大学生人数猛增。教育和创新相辅相成,历经数十年,令繁荣之花耀眼绽放。

雅思阅读高频词汇:

keep pace with 跟上

innovations 创新

fall behind 落后

Industrial Revolution 工业革命

surge 飙升

prosperity 繁荣

Today robotics and artificial intelligence call for another education revolution. This time, however, working lives are so lengthy and so fast-changing that simply cramming more schooling in at the start is not enough. People must also be able to acquire new skills throughout their careers.

Unfortunately, as our special report in this issue sets out, the lifelong learning that exists today mainly benefits high achievers—and is therefore more likely to exacerbate inequality than diminish it. If 21st-century economies are not to create a massive underclass, policymakers urgently need to work out how to help all their citizens learn while they earn. So far, their ambition has fallen pitifully short.

今天,机器人和人工智能呼唤又一场教育革命。而这一次,工作生涯如此漫长而又变化迅速,只在人生初期强加更多教育已经不足以应付。人们还必须能在整个职业生涯中获取新技能。

不幸的是,正如我们本期特别报道所述,目前的终身学习主要是令成功人士受益,因此更可能加剧而非减轻不平等。如果21世纪的经济体不想要产生一个庞大的底层阶级,政策制定者亟需制定措施,帮助国民在谋生的同时学习。而迄今为止,他们的抱负还小得可怜。

雅思阅读高频词汇:

artificial intelligence 人工智能

underclass 下层阶级

policymaker 政策制定者

Machines or learning 机器或学习

The classic model of education—a burst at the start and top-ups through company training—is breaking down. One reason is the need for new, and constantly updated, skills. Manufacturing increasingly calls for brain work rather than metal-bashing. The share of the American workforce employed in routine office jobs declined from 25.5% to 21% between 1996 and 2015. The single, stable career has gone the way of the Rolodex.

Pushing people into ever-higher levels of formal education at the start of their lives is not the way to cope. Just 16% of Americans think that a four-year college degree prepares students very well for a good job. Although a vocational education promises that vital first hire, those with specialised training tend to withdraw from the labor force earlier than those with general education—perhaps because they are less adaptable.

机器还是学习

在青少年时强化学习,之后通过公司培训加以补充,这种传统的教育模式正在失效。原因之一是需要新的技能,而且还要不断更新。制造业越来越多地需要脑力而非蛮力。从1996年到2015年,常规办公职位在美国劳动力中所占的比例从25.5%下降到21%。单一稳定的职业生涯已经像旋转式名片夹一样一去不返了。

在人生初期让人们接受更高程度的正规教育并非解决之道。仅有16%的美国人认为四年的大学教育足以让学生找到一份好工作。尽管职业教育能确保找到至关重要的第 一份工作,但接受专门培训的人往往比接受普通教育的人更早退出劳动大军,可能是因为前者适应性较弱。

雅思阅读高频词汇:

top-ups 充值

brain work 大脑的工作

withdraw 撤回

general education 通识教育

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