Can we learn English from movies? A text analysis
Graduation ThesisPresented to
the Faculty of the Department ofEnglish Language and LiteratureNotre Dame Seishin University
In Partial Fulfillmentof the Requirement for the Degree
Bachelor of Arts
byMadoka Hioka
2015
1
Contents
Chapter One: Introduction
1.1 Introduction
1.2 Learning English through movies
1.2.1 Listening skills
1.2.2 Speaking skills
1.2.3 Vocabulary
1.2.4 Summary
1.3 Ways to assess whether students can learn English from
movies
1.3.1 Listen and test
1.3.2 Interviews
1.3.3 Text analysis
1.4 Analyzing language texts
1.4.1 What coverage rate is best for language learning from
movies?
1.4.2 How to analyze texts
1.5 Previous research on text analysis of movies
1.6 What is the vocabulary size of Japanese students?
1.7 Research Questions
1.8 Conclusion
Chapter Two: The movie analysis
2.1 Introduction
2.2 The experiments
2.2.1 Introduction to the experiment
2.2.2 Method
2.2.2.1 The texts
2.2.2.2 The analyzing the text
2.3 Results
2.3.1 Coverage
2.3.2 Vocabularies
2.4 Summary
Chapter Three: Discussion
3.1 Introduction
3.2 Summary of the results
3.3 Discussion of the results
3.4 Answering the research questions
3.5 Implications from the data
3.6 Limitations of the Experiment
3.7 Further research
3.8 Conclusion
References
Appendices
ii
Abstract
Many researchers said that movies are good way to learn English
especially to improve speaking skills, listening skills, vocabulary
knowledge. This thesis found out it is true or not in the lexical point of
view. 16 movies’ script were downloaded from the Internet and edited to
analyze texts. Texts were analyzed using AntWord profiler (Anthony,
2013) which determines the frequency of each word. The comparison
wordlist was based on the Extensive Reading Foundation scale to
determine the percentage of words at each headword level.
Previous research said that leaners need 95%-98% coverage of
movies to be able to guess the meaning of an unknown word successfully.
The aim of this study was to find out how many words do learners need to
reach 95% or 98%.
The results of text analysis showed that learners would have only
93.13% coverage of one movie of average of all 16 movies if learners
know all 2,500 words from level 1 to level 16. Looking at all movies one by
one, the only 4 movies could reach 95% coverage. Learners could know
about over 60% of 750 words which are from level 1 to level 6 if they
watch all 16 movies. In terms of all 16 levels, they could be known 38% of
2,500 words on the same condition. The top 25 highest ranking words
used in the 16 movies were shown in this study. Those words are also
frequent in daily life.
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In this study, we found that we can’t say learning English from
movies are useful for everyone because the difficulty is depend on
learners’ knowledge of vocabularies. Learners who have high knowledge
of the words could guess the meaning of the words from the movies’
contexts with pictures.
iv
Chapter 1: Learning English from movies 1.1 Introduction
Japan is the country in which most people only need Japanese and
we don’t need to use other languages like English, French, or Spanish to
live in Japan. Some countries, however, have more than one official
language. For example, the official languages in Canada are English and
French, and in Belgium are French, Dutch, and German. Therefore,
Japanese students find it hard to realize the necessity of learning other
languages even though the Course of Study in Japan has determined that
English is as a compulsory subject from fifth grade elementary school
since the school year of 2011.
Braj Kachru advocated a circle of World Englishes which are shown
in concentric circle (see below). The inner circle represents the countries
where people originally speak English as
mother tongue such as United States of
America, United Kingdom, Australia, and
Canada. The outer circle stands for the
countries where many people learn and speak
English as lingua franca such as India, Nigeria,
and Malaysia. The expanding circle shows the
countries where people have their own language and learn English as a
foreign language such as Japan, Russia, China, and Korea.
1
Nowadays English is learned by many people all over the world as
the universal language. We can communicate with foreigners, collect
information from other countries, have fun through using English if we
learn English and use it. It feels like our world has expanded.
There are many ways to learn English in the world. For example,
reading books, listening to music, watching movies, etc. All these ways to
learn English have good point of something. This thesis is going to focus
on learning English through movies.
Many people say watching movies is a great way to improve the
English skills, especially listening and speaking skills. Movies are made for
native speakers not English learners and also they made these movies it
gives English learners opportunities to hear natural spoken English. This
means it may be possible to learn a lot of new words and expressions
from movies. This thesis will explore this question.
1.2. Learning English through movies
In Japan we often hear people claim that watching movies is a great
way to learn English. Ding (2007, p. 275) found that among the
participants in his study, all eight of the prize winners in national level
speech contents in China regarded watching movies and television series
as one of the most effective ways of improving their English. We often
hear about this on the internet and in classrooms too.
1.2.1 Listening skills
One advantage of movies is that learners can hear natural way to
speak English through movies. They can meet English the natural speed of
speaking by native speakers and help learners get used to hearing it. And
2
also learners can hear informal words or slang they cannot find in books
or dictionaries.
1.2.2 Speaking skills
Learners can improve their fluency of speaking. It helps learners to
learn how to put the words together and how to pronounce them. English
tends to link the words when they pronounce and so this is a good
opportunity to hear it in practice. Learners hear them and practice
mimicking it many times.
1.2.3 Vocabulary
Japanese English learners tend to learn new vocabularies and their
spelling with vocabulary lists in their school but it’s good to remember the
meaning and spelling but is not good for how to use the words. It should
be assumed that learning from a word list or word cards means that the
words are learned forever, nor does it mean that all knowledge of a word
has been learned (Paul and Rob However, learners can find many new
words or phrases, especially idioms or collocations through watching
movies. Movies are really helpful to understand and remember these
words because of the context. Learners get better understanding how to
use these words like when they are happy, surprised, sad, or angry
through the contexts of watching interesting and engaging movies.
1.2.4 Summary
In this section we have seen many claims for the idea that learning
from movies is very powerful, however there has been little or no research
3
to validate that this is actually the case. Is this true or not? We are going
to find out.
1.3 Ways to assess whether students can learn English from
movies
Above we saw the claims for the power of learning from movies, but
this is not yet verified and needs to be assessed. This section will discuss
the ways to measure uptake from watching movies.
1.3.1 Listen and test
Students watch movies and then take tests which ask the context of
movies, or dictation or even test their vocabulary knowledge. We can
know whether students can listen and understand what the characters
said properly.
1.3.2 Interviews
One way to assess if learners are learning from movies is we can
conduct interviews to ask questions such as “How did you feel learning
English from movies?”, “Did you like the movie or not? and Why?”, and
“Did you think you could learn something from movies?” after watching
movies.
1.3.3 Text analysis
This involves analyzing the script from the movie with software to
find out what words are in the texts. This allows us to generate a profile of
4
the percentage of high and low frequency words. If there are many low
frequency words it means the movie is likely to be difficult. If we also
know the likely acquisition uptake rate (see below) we can then ascertain
the likelihood of whether the movie will be in the right coverage range
which can lead to uptake.
1.4 Analyzing language texts
A different and standard way to find out how difficult a text is, is to
analyze the vocabulary in it. Software programs can count how many
times each word appears in the text to tell us
a) how many words were used in each text and as a total
b) which words were used and how many times
The data from this can be analyzed to find out how difficult a text is. If
there are a lot of high frequency words it is likely that the movie will be
easy, but if there are many low frequency words, it will make the movie
hard to understand.
The text analysis can also tell us how easy it is for a student to learn
new words from the movies. Research shows that students need to
a) meet each words many times before it is learnt
b) know about 98% of the surrounding text for the student to be able
to have a high chance of guessing an unknown word successfully.
1.4.1 What coverage rate is best for language learning from
movies?
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Before we can ascertain whether students can understand a movie,
we need to know how many of the words they need to know to actually
understand it. Is it 80%, 90% or more? Brown, Waring, Donkaewbua
(2008) compared three types of input methods to know which one is good
for learning more English vocabulary, which are reading, reading-while-
listening, and listening. Subjects were tested and they answered by
multiple choice and translation. The result showed that reading-while-
listening was the best way to learn vocabulary. It also showed that only
listening was much harder than reading or reading-while- listening.
This suggests that students listening to movies will need a higher
level of coverage than the 95% or 98% often stated for reading. This level
might be 98% or 99% of the words met in the movies to be known for
fluent understanding. If the subject knows fewer than 98-99% of the
words they meet, then they may not pick up much and thus very little will
be learnt. We are assuming here they are only watching the movie not
also reading the subtitles in English.
However, a difference between listening to a book and watching a
video is that a lot of the contents of a video are visual rather than
auditory. This means that it’s likely a lower percentage than 99% might be
suitable for comprehension. This has not been researched until the
present time but it may be a rate similar to that of reading - possibly 95-
98%.
1.4.2 How to analyze texts
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The texts were put into a software program called AntConc
(Anthony, 2013) which determines the frequency of each word against a
wordlist. The comparison wordlist was based on the 20-level Extensive
Reading Foundation scale (www.erfoundation .org ) to determine what
percentages of words at each headword level were. It can determine the
number of words in each text outside the 95% and 98% coverage rates
needed for fluent comprehension.
1.5 Previous research on text analysis of movies
Webb and Rodgers (2009) analyzed 318 movies which have
2,841,887 running words to find out the vocabulary size that need to
comprehend 95% and 98% of the words in movies. The movies
distinguished between American and British English, and divided into 11
genres; action, animation, comedy, suspense/crime, drama, horror,
romance, science fiction, war, western, and classic.
The result showed that learners were likely to understand 95.76% of
the words in movies if they know the most frequent 3,000 word families
plus proper nouns and marginal words, and they are likely to understand
98.15% of the words in movies if they know the most frequent 6,000 word
families plus proper nouns and marginal words.
The results of 95% coverage of American and British movies were
the same as above, but the results of that of 98% have the gap of 1,000
words.
Looking at the genres, the results have a wide range. Learners need to
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understand 95% of the words in movies, which provide 3,000 to 4,000
word families plus proper nouns and marginal words, and 98% of the
words in movies, which provide 5,000 to 10,000 word families plus proper
nouns and marginal words.
1.6 What is the vocabulary size of Japanese students?
Research shows that the average Japanese college student knows
about 2,000 words by the time they graduate from high school. The
question is whether this is enough words to be able to cover 95% or 98%
of the words in movies?
1.7 Research Questions
In the next chapter, we will find out the answers to the following
three research questions by analyzing the texts.
1. How many words do learners need when the coverage of movies
reach 95% or 98%?
2. Are there any differences from age or ability?
3. What words were used in the movies at each level?
1.8 Conclusion
In this chapter, we looked at the advantage of learning English
through movies, word coverage of movies, and analyzing text. In the next
chapter, we will look at the experiment to find out watching movies are
8
good for learning English by analyzing text.
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Chapter 2: The Movie Analysis
2.1 Introduction
In Chapter One, we looked at learning English from movies from
various points of view. In this chapter, we are going to look at how to
analyze the texts more detail, and the results of analyzing texts to see if
indeed typical college age English majors can learn much new language
from watching movies without subtitles.
2.2 The experiment
2.2.1 Introduction to the experiment
16 movie scripts were edited and analyzed to find out what words
were used at each level in each movie and what vocabulary size learners
would need to reach 95% or 98% coverage of movies to understand the
whole movie.
2.2.2 Method
This section explains the method of the text analysis.
2.2.2.1 The texts
The 16 texts were downloaded from some sites on the Internet. All
of movies were English language movies which were produced by Walt
Disney Animation Studios and Pixar Animation Studios;
Snow White and the Seven Dwarfs (1937),
Pinocchio (1940),
Cinderella (1950),
10
Alice in Wonderland (1951),
Peter Pan (1953),
Sleeping Beauty (1954),
The Little Mermaid (1989),
Beauty and the Beast (1991),
Aladdin (1992),
The Lion King (1994),
Toy Story (1995),
Finding Nemo (2003),
Cars (2006),
Enchanted (2007),
Tangled (2010),
Frozen (2013).
2.2.2.2 The analyzing the text
Words which were not spoken in the movies such as stage
commands, story line, and speaker’s names were removed from the
scripts. Only the spoken words in the movies were analyzed.
The number of times each word was used was counted using AntWord
Profiler (Anthony, 2013) and put against several wordlists from 200
headwords going up to 2500 headwords. The aim was to see what
percentage of the words in the movies come from various frequency
bands. If most of the words are high frequency ones then it means the
movies should be easy to understand. Alternatively, if there are many low
frequency words it means the movies are difficult. In Chapter One we
11
showed that students need to know about 95-98% of the surrounding
words to be able to guess the meaning of an unknown word successfully.
However, the raw texts were not clean in the sense that they had
names, narration excerpts and so on (in pink below) which needed to be
removed before analysis. Only the spoken words from the movies were
analyzed. Contractions and connected speech were changed to the form.
For example, wanna, gotta, and somethin’ were changed want to, have to,
and something.
Below is an example edit from Aladdin. The items in pink were removed.
ALADDIN: THE COMPLETE SCRIPT COMPILED BY BEN SCRIPPS
<[email protected]> (Portions Copyright (c) 1992
The Walt Disney Company)
PEDDLER: Oh I come from a land From a faraway place Where the
caravan camels roam Where they cut off your ear /Where it's flat
and immense If they don't like your face /And the heat is intense It's
barbaric, but hey--it's home! When the wind's at your back And the
sun's from the west And the sand in the glass is right Come on
down, Stop on by Hop a carpet and fly To another Arabian night!
Arabian nights Like Arabian days More often than not Are hotter
than hot In a lot of good ways
12
Arabian nights 'Neath Arabian moons A fool off his guard Could fall
and fall hard Out there on the dunes.
Ah, Salaam and good evening to you worthy friend. Please, please,
come closer--(Camera zooms in hitting peddler in face) Too close, a
little too close. (Camera zooms back out to CU)There.Welcome to
Agrabah. City of mystery, of enchantment, and the finest
merchandise this side of the river Jordan, on sale today, come on
down! Heh, heh. Look at this! Yes! Combination hookah and coffee
maker--also makes Julienne fries. Will not break (taps it on table),
will not--(it falls apart)--it broke. Ooohhh! Look at this! (Pulls out
Tupperware) I have never seen one of these intact before. This is
the famous Dead Sea Tupperware. Listen. (Pries it open, makes
raspberry sound.) Ah, still good. (Camera begins to pan to right.
PEDDLER hurries to catch it.) Wait, don't go! (Stop pan.) I can see
that you're only interested in the exceptionally rare. I think then,
you would be most rewarded to consider...this. (PEDDLER pulls the
MAGIC LAMP out from his sleeve.) Do not be fooled by its
commonplace appearance. Like so many things, it is not what is
outside, but what is inside that counts. (Another pan, this one
slower to left. Again, PEDDLER rushes to catch up.) This is no
ordinary lamp! It once changed the course of a young man's life. A
young man who liked this lamp was more than what he seemed. A
diamond in the rough. Perhaps you would like to hear the tale?
(PEDDLER pours shiny sand from the lamp into his hand.) It begins
on a dark night (PEDDLER throws sand into the sky, where it forms a
13
starry nightscape.) , where a dark man waits, with a dark purpose.
(Camera tilts down to find JAFAR sitting on his horse and IAGO on his
shoulder. GAZEEM comes riding up to the pair.)
JAFAR: You...are late. GAZEEM:A thousand apologies, O patient one.
JAFAR: You have it, then? GAZEEM:I had to slit a few throats to get
it. (Pulls out half of the medallion. JAFAR reaches out for it, but
GAZEEM yanks it back.) Ah, ah, ahhh! The treasure! (IAGO
squawks as he flies by and grabs the medallion.) Ouch! JAFAR:
Trust me, my pungent friend. You'll get what's coming to you. IAGO:
What's coming to you! Awk!
(JAFAR pulls out the second half of the medallion. He connects
them, and the insect medallion begins to glow. Finally, it flies out of
JAFAR's hand, scaring the horses, and is off towards the dunes.)
JAFAR: Quickly, follow the trail!
After edit
Oh I come from a land From a faraway place Where the caravan
camels roam Where they cut off your ear /Where it's flat and
immense If they don't like your face /And the heat is intense It's
barbaric, but hey--it's home! When the wind's at your back And the
sun's from the west And the sand in the glass is right Come on
14
down, Stop on by Hop a carpet and fly To another Arabian night!
Arabian nights Like Arabian days More often than not Are hotter
than hot In a lot of good ways
Arabian nights 'Neath Arabian moons A fool off his guard Could fall
and fall hard Out there on the dunes.
Ah, Salaam and good evening to you worthy friend. Please, please,
come closer--Too close, a little too close. There. Welcome to
Agrabah. City of mystery, of enchantment, and the finest
merchandise this side of the river Jordan, on sale today, come on
down! Heh, heh. Look at this! Yes! Combination hookah and coffee
maker--also makes Julienne fries. Will not break, will not--it broke.
Ooohhh! Look at this! I have never seen one of these intact before.
This is the famous Dead Sea Tupperware. Listen. Ah, still good.
Wait, don't go! I can see that you're only interested in the
exceptionally rare. I think then, you would be most rewarded to
consider...this. Do not be fooled by its commonplace appearance.
Like so many things, it is not what is outside, but what is inside that
counts. This is no ordinary lamp! It once changed the course of a
young man's life. A young man who liked this lamp was more than
what he seemed. A diamond in the rough. Perhaps you would like
to hear the tale? It begins on a dark night, where a dark man waits,
with a dark purpose.
You...are late.
15
A thousand apologies, O patient one.
You have it, then?
I had to slit a few throats to get it.
Ah, ah, ahhh! The treasure!
Ouch!
Trust me, my pungent friend. You'll get what's coming to you.
What's coming to you! Awk!
Quickly, follow the trail!
2.3 Results
2.3.1 Coverage
This section will show the number of running words of the texts at each of
the 16 levels.
16
Table 1: The total number of words in the 16 movie scripts by level
Level Number of headwords
(cumulative)
Totals
1 100 (100) 54,7362 100 (200) 12,4523 200 (400) 15,8794 100 (400) 8,1205 100 (600) 3,4786 150 (750) 3,2507 150 (900) 2,4318 150 (1,050) 1,4929 150 (1,200) 1,43310 150 (1,350) 98711 200 (1,550) 1,16512 200 (1,750) 1,11313 150 (1,900) 60314 200 (2,100) 80315 200 (2,300) 75516 200 (2,500) 605
Out of level 8,065Total 117,367
Table 1 shows that the total number of words in the 16 movies’
scripts by level. It didn’t included proper names in movies because people
can know that it’s name of the character while they listen to it many
times. Neither does the above include words outside these 2,500
headwords.
17
Table 2 shows the percentage of words from that level which
appeared in the movies.
Table 2: The average coverage rate for the 16 movie scripts
Level Number of headwords
(cumulative)
Rate Cumulative rate
1 100 (100) 46.64% 46.64%2 100 (200) 10.61% 57.25%3 200 (400) 13.53% 70.78%4 100 (400) 6.92% 77.69%5 100 (600) 2.96% 80.66%6 150 (750) 2.77% 83.43%7 150 (900) 2.07% 85.50%8 150 (1,050) 1.27% 86.77%9 150 (1,200) 1.22% 87.99%10 150 (1,350) 0.84% 88.83%11 200 (1,550) 0.99% 89.82%12 200 (1,750) 0.95% 90.77%13 150 (1,900) 0.51% 91.29%14 200 (2,100) 0.68% 91.97%15 200 (2,300) 0.64% 92.61%16 200 (2,500) 0.52% 93.13%
Out of level
6.87% 100.00%
Table 2 shows that the average coverage rate for the 16 movie
scripts. 46.64% of the running words of 16 movies could be understood if
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learners know the words of the level 1. 57.25% of that could be
understood if learners know the words of the level 1 and 2. Level 16
provides 93.13% coverage of 16 movies. That is if the subjects have a
listening vocabulary of 2,500 words, they would know 93.13% of the
words in these movies not including proper nouns.
19
Table 3: The coverage cumulative rate for the 16 movie scripts
leve
l
Alad
din
Alice
in
Won
derl
and
Beau
ty
and
the
Beas
t
Cars
Cind
erel
la En
chan
ted Fr
ozen
Find
ing
Nem
o
Pete
r Pa
n
Pino
cchi
o Slee
ping
Be
auty
Snow
W
hite
Tang
led
The
Lion
king
The
Little
m
erm
aid
Toy
Stor
y
145.81
%44.34
%47.63
%47.60
%44.05
%50.47
%45.82
%49.86
%43.02
%48.29
%41.91
%43.84
%44.14
%48.27
%40.99
%45.98
%
255.09
%56.04
%58.00
%58.06
%54.84
%61.81
%58.21
%60.42
%52.69
%58.34
%53.04
%53.23
%55.30
%58.82
%50.20
%56.96
%
368.20
%70.31
%72.11
%70.64
%68.58
%75.10
%72.27
%73.99
%66.61
%72.90
%67.80
%67.88
%68.33
%70.05
%63.47
%70.79
%
475.22
%76.71
%79.50
%77.34
%75.82
%82.17
%79.30
%79.89
%73.24
%80.28
%74.84
%75.75
%76.46
%77.49
%69.79
%76.61
%
578.28
%79.95
%82.11
%80.02
%79.32
%85.80
%82.22
%81.79
%76.14
%83.48
%78.32
%78.61
%80.48
%80.14
%72.55
%79.39
%
681.21
%82.52
%84.94
%82.26
%81.49
%88.51
%85.81
%84.35
%79.54
%86.04
%81.04
%81.02
%84.08
%82.89
%75.79
%81.96
%
783.24
%84.72
%87.13
%84.20
%83.99
%90.65
%88.15
%85.87
%81.65
%87.65
%84.36
%82.71
%86.45
%84.84
%77.80
%83.95
%
884.45
%85.93
%88.81
%85.41
%84.87
%91.79
%89.78
%86.75
%82.88
%89.10
%85.87
%84.28
%87.68
%85.81
%78.97
%85.37
%
985.65
%87.41
%89.97
%86.73
%85.92
%92.66
%90.91
%87.63
%83.59
%90.46
%87.52
%84.95
%88.56
%87.58
%79.65
%87.67
%
1086.61
%88.39
%90.94
%87.72
%86.66
%93.24
%91.61
%88.29
%84.80
%91.71
%87.96
%85.50
%89.42
%88.52
%80.81
%88.47
%
1187.82
%89.58
%92.06
%88.31
%87.40
%94.11
%92.67
%88.96
%86.02
%92.54
%89.82
%87.95
%90.47
%89.09
%81.96
%89.29
%
1289.73
%91.23
%92.69
%89.03
%88.74
%94.90
%93.44
%89.59
%86.71
%93.09
%91.61
%88.83
%91.40
%89.77
%82.62
%90.02
%
1390.40
%91.62
%93.12
%89.71
%89.23
%95.05
%94.00
%90.07
%87.96
%93.34
%91.98
%89.46
%91.81
%90.21
%83.81
%90.56
%
1490.87
%92.42
%94.04
%90.26
%89.60
%95.54
%94.44
%90.81
%89.98
%93.92
%92.36
%90.24
%92.44
%90.95
%85.74
%91.11
%15 91.61 92.75 94.75 91.00 90.38 95.98 95.03 91.52 90.37 94.58 93.24 90.68 93.28 91.54 86.11 92.06
20
% % % % % % % % % % % % % % % %
1692.03
%93.11
%95.08
%91.73
%90.86
%96.27
%95.49
%92.19
%91.07
%95.56
%93.73
%90.94
%93.67
%92.00
%86.77
%92.80
%
21
Table 3 shows that the cumulative coverage of each movie at each
level. It showed that any movies don’t reach 98% coverage and only
Enchanted are reached 95% at level 13, Frozen reached it at level 15, and
Beauty and the Beast and Pinocchio are reached it at level 16.
22
Table 4: The coverage rate for the 16 movie scripts at each level
Alad
din
Alice
in
Won
der
land
Beau
ty
and
the
Beas
t
Cars
Cind
ere
lla
Ench
ante
d
Froz
en
Find
ing
Nem
o
Pete
r Pa
n
Pino
cch
ioSl
eepi
ng
Beau
ty
Snow
W
hite
Tang
led
The
Lion
king The
Little
m
erm
ai
Toy
Stor
y
145.8
%44.3
%47.6
%47.6
%44.1
%50.5
%45.8
%49.9
%43.0
%48.3
%41.9
%43.8
%44.1
%48.3
%47.5
%46.9
%
2 9.3%11.7
%10.4
%10.5
%10.8
%11.3
%12.4
%10.6
% 9.7%10.1
%11.1
% 9.4%11.2
%10.5
%10.6
%10.1
%
313.1
%14.3
%14.1
%12.6
%13.7
%13.3
%14.1
%13.6
%13.9
%14.6
%14.8
%14.7
%13.0
%11.2
%13.4
%13.8
%4 7.0% 6.4% 7.4% 6.7% 7.2% 7.1% 7.0% 5.9% 6.6% 7.4% 7.0% 7.9% 8.1% 7.4% 7.2% 5.8%5 3.1% 3.2% 2.6% 2.7% 3.5% 3.6% 2.9% 1.9% 2.9% 3.2% 3.5% 2.9% 4.0% 2.6% 3.0% 2.8%6 2.9% 2.6% 2.8% 2.2% 2.2% 2.7% 3.6% 2.6% 3.4% 2.6% 2.7% 2.4% 3.6% 2.7% 2.9% 2.6%7 2.0% 2.2% 2.2% 1.9% 2.5% 2.1% 2.3% 1.5% 2.1% 1.6% 3.3% 1.7% 2.4% 2.0% 2.0% 2.0%8 1.2% 1.2% 1.7% 1.2% 0.9% 1.1% 1.6% 0.9% 1.2% 1.4% 1.5% 1.6% 1.2% 1.0% 1.6% 1.4%9 1.2% 1.5% 1.2% 1.3% 1.0% 0.9% 1.1% 0.9% 0.7% 1.4% 1.6% 0.7% 0.9% 1.8% 1.0% 2.3%
10 1.0% 1.0% 1.0% 1.0% 0.7% 0.6% 0.7% 0.7% 1.2% 1.2% 0.4% 0.6% 0.9% 0.9% 0.7% 0.8%11 1.2% 1.2% 1.1% 0.6% 0.7% 0.9% 1.1% 0.7% 1.2% 0.8% 1.9% 2.5% 1.1% 0.6% 0.9% 0.8%12 1.9% 1.6% 0.6% 0.7% 1.3% 0.8% 0.8% 0.6% 0.7% 0.5% 1.8% 0.9% 0.9% 0.7% 1.0% 0.7%13 0.7% 0.4% 0.4% 0.7% 0.5% 0.2% 0.6% 0.5% 1.2% 0.2% 0.4% 0.6% 0.4% 0.4% 0.4% 0.5%14 0.5% 0.8% 0.9% 0.5% 0.4% 0.5% 0.4% 0.7% 2.0% 0.6% 0.4% 0.8% 0.6% 0.7% 0.5% 0.6%15 0.7% 0.3% 0.7% 0.7% 0.8% 0.4% 0.6% 0.7% 0.4% 0.7% 0.9% 0.4% 0.8% 0.6% 0.5% 1.0%16 0.4% 0.4% 0.3% 0.7% 0.5% 0.3% 0.5% 0.7% 0.7% 1.0% 0.5% 0.3% 0.4% 0.5% 0.3% 0.7%Not in 8.0% 6.9% 4.9% 8.3% 9.1% 3.7% 4.5% 7.8% 8.9% 4.4% 6.3% 9.1% 6.3% 8.0% 6.5% 7.2%
Total 100.0
%100.0
%100.0
%100.0
%100.0
%100.0
%100.0
%100.0
%100.0
%100.0
%100.0
%100.0
%100.0
%100.0
%100.0
%100.0
%
23
Figure 1: The coverage rate for the 16 movie scripts at each level
24
Table 4 and Figure 1 showed the coverage of each script at each level. Enchanted which reached 95% coverage at level 13 and used fewer words from out of level and more words from the upper level than other movies.
Table 5: The average coverage of the 16 levels for one movie
Level Number of headwords (cumulative)
Rate
1 100 (100) 67%2 100 (200) 56%3 200 (400) 59%4 100 (400) 66%5 100 (600) 56%6 150 (750) 45%7 150 (900) 31%8 150 (1,050) 29%9 150 (1,200) 21%10 150 (1,350) 20%11 200 (1,550) 18%12 200 (1,750) 15%13 150 (1,900) 11%14 200 (2,100) 11%15 200 (2,300) 13%16 200 (2,500) 10%
total average
2,500 33%
Table 5 shows the average percentage of the words at each level that
25
have been used in one movie of the 16 movies. One movie used 67% of the first 100 words at level 1, and 56% of the 100 words at level 2. Bottom of level 11, one movie used under 20% of the words. On the whole, learners will meet only 33% of the words at these 16 levels.
Table 6: The proportion of the words using more than 10 times at each level
Level Number of headwords
(cumulative)
Rate
1 100 (100) 79%2 100 (200) 67%3 200 (400) 74%4 100 (400) 83%5 100 (600) 75%6 150 (750) 59%7 150 (900) 36%8 150 (1,050) 34%9 150 (1,200) 20%10 150 (1,350) 19%11 200 (1,550) 16%12 200 (1,750) 13%13 150 (1,900) 7%14 200 (2,100) 10%15 200 (2,300) 13%16 200 (2,500) 6%
total average
2,500 38%
26
Table 6 showed that the percentage of the words which learners are
likely to be known after watching all 16 movies if we assume that they need
to meet the words at least 10 times for them to be ‘known’. 38% of the
words in the 16 movies are likely to be known after watching all 16 movies.
27
2.3.2 Vocabulary
Table 7: The top 25 words at levels 1 to 8
Level 1 Level 2 Level 3 Level 4 Level 5 Level 6 Level 7 Level 81 I we a will dream would dear might2 be but can so ever still should fix3 see for they if guy fly once scare4 the all now little world swim poor land5 to come well find heart even save song6 this here one could move through sweet rise7 it get some life hurry hold lady stick8 not know right true child funny crazy deal9 and just let wish last marry forever perhaps10 do with think course real wonder actually present11 no look time place may kill hang shoot12 he why way stay forget around certainly trust13 oh about wait than free kiss upon human14 what love never happen close whole fairly guest15 of back as leave own enough pass blow16 have every take turn left matter promise ahead17 go any tell bring wonderful wake perfect freeze18 in down from sing soon star return wood
28
19 she really thing believe surprise ride cool taste20 you help then fine fall road death search21 on very mean most while bit point shut22 yes only day light chance order space warn23 there stop too follow stand power beat escape24 out sorry need ready another yet prepare attention25 hello dad or guess mind alive exact roll
Table 8: Top 25 words at levels 9 to 16 and those ‘out of list’.
Level 9 Level 10 Level 11 Level 12 Level 13 Level 14 Level 15 Level 16Out of list
1 king string queen prince pan captain waged race heighho2 kid ocean magic princess lightning hook whale excuse majesty3 shall loose dig roses monster beast grace party pretty4
toy brave castle slippercommand hi rust
conscience sire
5 master chase fool soul pig scar rat bubble ooh6
baby fit shinegentleman shark merry royal pirate ain
7 cause spot fault crew thunder palace bolt fairy heh8 nose awake glad interpret float whistle brute lead eh9 speed beg pardon harm faith crown heal elastic kingdom10 smoke chief bite tune adapt mate sting chop mm1 impress race bell grab colony sand polar blink aye
29
112 wing steady honor nonsense dumb tank bump ring idea13 entire count gift treasure standard alphabet demon fossil ohh14 gas drama darling tower sweep tub peculiar
sympathize hah
15 indeed economy dust trap carpet
assignment claw charge gonna
16 force pleasure sail charm combine bless crust deceive sharkbait17 gate practical spell honey dive mask gram fuss dude18 honest define celebrate joy forbid pal hail laser hoo19 lip guard cough quit formal process utilize moisture ahem20 mirror hunt bet tale inspire curse wax someday ahh21 ought diamond block bow row glory bounce chew papa22 rough chip cute butter tick lantern immune heap piston23 case feed dare ideal victim sew lord hybrid blah24 propose focus evil planet bride turtle upper mark ee25 direction
fortunately forgive assess constant battle
collaborate moist ugh
30
Table 7 and 8 show the top 25 highest ranking words used in the 16
movies. We can what words we could learn from movies when we watch all
16 movies. These also would be high frequency words in the real world,
especially words from level 1 to level 3. Words out of list had a lot of
onomatopoeia such as eh, ahem, and ugh.
2.4 Summary
In Chapter Two, we have looked at many tables that showed the
numbers and percentages. These data showed that the average of the 16
movies doesn’t equal the 95% or 98% word coverage needed for
comprehension and thus were unlikely to lead to much learning. In the next
chapter, we will discuss this in more detail.
31
Chapter 3: The Discussion 3.1 Introduction
In Chapter One and Two, we looked at the analysis the text for learning
English from movies, and the results of analyzing the text. In this last
chapter, we are going to look at the discussion of the results, and answer the
research questions.
3.2 Summary of the results
All 16 movies totaled 117,367 running words. Table 2 showed that
learners would have only 93.13% coverage of one movie of all 16 movies
even if learners know all 2,500 words from level 1 to level 16. Table 3
showed that the only 4 movies could reach 95% coverage. Table 6 showed
that learners could know about over 60% of 750 words which are from level
1 to level 6 if they watch all 16 movies. In terms of all 16 levels, they could
be known 38% of 2,500 words on the same condition. Table 7 and 8 showed
that the words we can learn if we watch all 16 movies.
3.3 Discussion of the results
Table 2 showed that level 16 provided 93.13% of coverage of 16
movies. Table 3 showed that not one of the movies had 98% coverage movie
looking at each movie and only 4 of 16 movies, which were Beauty and the
Beast, Enchanted, Frozen, and Pinocchio, which reached 95% coverage.
32
Enchanted has 95.05% coverage if learners know 1,900 words at level 13,
Frozen has 95.03% coverage if learners know 2,300 words at level 15, and
Beauty and the Beast and Pinocchio have 95.08% and 95.56 % coverage if
learners know 2,500 words at level 16. That means Enchanted is the easiest
movie but looking at the average, it is difficult for learners who have small
knowledge of the words to learn English from movies so learning English
depends on learners’ age or competence.
Table 7 and 8 showed that almost all of the words from the movies
looked very frequent but some words are not frequent as the level is getting
high because it depends on the movie we analyzed in this study. Combined
with Tables 3, 4, 7, 8, and figure 1, Words of level 1 to 3 take up about 70-80
% of all, which are the most frequent words.
3.4 Research questions
1. How many words do learners need when the coverage of movies
reach 95% or 98%?
This study showed that learners need more than 2,500 words when the
coverage of movies reaches 95% or 98%. Unfortunately, the specific
numbers of the words they actually know wasn’t a research question in this
study. However, we can say that as a learner’s listening vocabulary is about
40-50% of their reading vocabulary and so as we saw in Chapter One a
typical college student may have 2,000-2,500 knowledge of written words,
not spoken words and thus may know about 1,000-1,300 words only which
33
will mean that none of the movies come close to meeting the 95% minimum
requirement to be able to guess unknown words from context. This means
learning English from movies is likely to be all but impossible for learners
with a listening vocabulary of less than 3,000 words.
2. Are there any differences from age or ability?
Learning English from movies requires high level of knowledge of the
words that learners can understand by listening, as well as reading. The data
suggest that a no learners were at vastly different ages or levels, we could
not assess this.
3. What words were used in the movies at each level?
Table 6 and 7 answered this question. The words used in movies can
often be seen or heard in daily life.
3.5 Implications
We looked at the results of this study and we found out learning
English from movies is difficult for us because we need 95-98% coverage of
the movies to understand them. If learners have the enough knowledge of
the vocabulary, using movies for learning would be very helpful. The words
at level 1 to 3 in movies and its percentage are 70-80% which means
learners can learn frequent vocabularies by watching movies many times.
However, if the learners watch the movies many times eventually they will
34
understand them.
3.6 Limitations of the Experiments
There are two limitations of the experiments in this study.
(1) the number of the movies and genres
(2) focused on only literal words
First, the movies we use in this study were chosen randomly so we might get
the different results we got if the movies we use were changed, or more
variety.
Secondly, we focused on only the words literal word not the sounds or the
words or the visual images in this study. The percentage this study may be
lower if we also focus on including sound of the words. This means learners
don’t have the same knowledge of the words that learners can understand
both looking and listening. Learners should have the words that they can
understand if they see them but they can’t understand if they only listen to
it.
3.7 Further researchThis study focused on vocabulary, so it will get much better
information if we looked at listening point, and grammar point.
35
In terms of listening, we can discuss the particularity of learning
through movies. Listening with pictures gives us better understanding than
listening only. We can also discuss the effect of the subtitles and its
difference between watching movies in English with English/Japanese
subtitles or without subtitles, and in Japanese with English/Japanese subtitles
or without subtitles.
From the point of view from grammar, we will analyze what grammar
the characters use in their discourse. Learning grammar through discourse in
movies could provide aural input of natural ways to speak and then we can
know about what types of grammar are used most frequently according to
the situations.
3.8 Conclusion
In this study, we looked at the coverage of the movies and it showed
the difficulty of learning English from movies. It is a good way for learners
who have high knowledge of the words to learn with movies. The
vocabularies used in movies are useful. This study showed different results
from the results we expected. Many researchers said that learning English
through movies are good way but it depends on the learners.
36
References
Anthony, L. 2013. AntWord Profiler. Waseda Computer Science Labs.
Brown, R. & Waring, R. & Donkaewbua, S. 2008. Incidental vocabulary acquisition from reading, reading-while-listening, and listening stories, Reading in a Foreign Language, 20 (2): 136-163
Nation, P. & Waring, R. Vocabulary size, text coverage and word lists. www.fltr.ucl.ac.be/fltr/germ/etan/bibs/vocab/cup.html Accessed October 12, 2014
Webb, S. & Rodgers, M. P. H. 2009. The lexical coverage of movies. Applied Linguistics, 30 (3): 407-427
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