READ TEXT II AND ANSWER QUESTIONS 16 TO 20:
TEXT II
The backlash against big data
[…]
Big data refers to the idea that society can do things with a large
body of data that weren't possible when working with smaller
amounts. The term was originally applied a decade ago to
massive datasets from astrophysics, genomics and internet
search engines, and to machine-learning systems (for voicerecognition
and translation, for example) that work
well only when given lots of data to chew on. Now it refers to the
application of data-analysis and statistics in new areas, from
retailing to human resources. The backlash began in mid-March,
prompted by an article in Science by David Lazer and others at
Harvard and Northeastern University. It showed that a big-data
poster-child—Google Flu Trends, a 2009 project which identified
flu outbreaks from search queries alone—had overestimated the
number of cases for four years running, compared with reported
data from the Centres for Disease Control (CDC). This led to a
wider attack on the idea of big data.
The criticisms fall into three areas that are not intrinsic to big
data per se, but endemic to data analysis, and have some merit.
First, there are biases inherent to data that must not be ignored.
That is undeniably the case. Second, some proponents of big data
have claimed that theory (ie, generalisable models about how the
world works) is obsolete. In fact, subject-area knowledge remains
necessary even when dealing with large data sets. Third, the risk
of spurious correlations—associations that are statistically robust
but happen only by chance—increases with more data. Although
there are new statistical techniques to identify and banish
spurious correlations, such as running many tests against subsets
of the data, this will always be a problem.
There is some merit to the naysayers' case, in other words. But
these criticisms do not mean that big-data analysis has no merit
whatsoever. Even the Harvard researchers who decried big data
"hubris" admitted in Science that melding Google Flu Trends
analysis with CDC's data improved the overall forecast—showing
that big data can in fact be a useful tool. And research published
in PLOS Computational Biology on April 17th shows it is possible
to estimate the prevalence of the flu based on visits to Wikipedia
articles related to the illness. Behind the big data backlash is the
classic hype cycle, in which a technology's early proponents make
overly grandiose claims, people sling arrows when those
promises fall flat, but the technology eventually transforms the
world, though not necessarily in ways the pundits expected. It
happened with the web, and television, radio, motion pictures
and the telegraph before it. Now it is simply big data's turn to
face the grumblers.
(From http://www.economist.com/blogs/economist explains/201
4/04/economist-explains-10)
When Text II mentions “grumblers” in “to face the grumblers”, it refers to:
The word “so” in “perhaps more so than the words and signals” is used to refer to something already stated in Text I. In this context, it refers to:
The use of the phrase “the backlash” in the title of Text II means the:
Based on the summary provided for Text I, mark the statements
below as TRUE (T ) or FALSE (F ).
( ) Contextual clues are still not accounted for by computers.
( ) Computers are unreliable because they focus on language
patterns.
( ) A game has been invented based on the words people use.
The statements are, respectively:
The three main arguments against big data raised by Text II in the second paragraph are:
For questions 25 and 26, choose the verb tense that is used CORRECTLY
Choose the option where the phrasal verb is used INCORRECTLY.
Choose the option where the verb tense is used INCORRECTLY.
What is NOT TRUE about English for Specific Purposes (ESP)?
According to Duboc (2016, p. 62), critical literacy differs from critical reading as the former holds that:
According to Jordão (2013), critical pedagogy differs from structuralist pedagogies because, among other reasons, it
Critical literacy emphasizes the need to use language as a vehicle for social change. One of the strategies a teacher may use for this purpose is
In a classroom situation in which the student asks the teacher if British or American pronunciation should be preferred, the most adequate answer the teacher should give, from a postcolonial orientation, is:
Duboc (2016, p. 65) mentions three generations of evaluation
practices.
Match the frameworks and the focus of their methods:
1- Behaviorism
2- Constructivism
3- Sociocultural theories
( ) Learner-centered methods
( ) Language-centered methods
( ) Learning-centered methods
Indicate the option that shows the correct matching, from top to
bottom.
