Session 2
• Vocabulary size and vocabulary profiles of
students
• Often used in proficiency or entrance tests; as
an indicator of proficiency level
• Word frequencies
• Which words are more frequently used in the
English language?
• What kind of words should learners focus on?
• Some well-known word lists
• Computer applications for assessing
vocabulary size and profile
Warming Up
Number of words in the English
language:
Number of words a universityeducated native English speaker
knows:
Number of words that you know:
Vocabulary size needed for basic
communication (i.e., to express what
one wants to express, however
simply):
Vocabulary size needed for reading
(understanding any written text):
Can you think of a good way to measure people’s
vocab sizes?
New curriculum proposed by
EDB
Key Stage (KS)
Stage target
(no. of word
families)
Cumulative target
(no. of word
families)
KS1 (Pri 3)
KS2 (Pri 6)
KS3 (Sec 3)
KS4 (Sec 6)
3
Number of words in the English
language:
•1 to 2 million words (Schmitt, 2000)
Goulden, Nation & Read (1990) estimated
that Webster’s Third International Dictionary
(published in 1961) contained around 267,000
entries and 54,000 word families.
Number of words a universityeducated native English speaker
knows:
20,000 word families
2,000 most frequent words
Vocabulary size needed for basic
West’s (1953) General Service List:
communication (i.e., to express what
one wants to express, however simply): 95% coverage of informal spoken English
(but only 80% coverage of written English)
Vocabulary size needed for reading
(understanding any written text):
Students need to know 95%-98% of the
words in a text in order to understand the
text
(5,000 words – about 90% coverage,
depending on the kind of text being read)
New curriculum proposed by
EMB
Key Stage (KS)
Stage target
Cumulative target
KS1 (Pri 3)
1000
1000
KS2 (Pri 6)
1000
2000
KS3 (Sec 3)
1500
3500
KS4 (Sec 6)
1500
5000
5
Vocabulary size and text coverage
Source: Francis and Kucera, 1982 (as cited in Nation & Waring, 1997, presession 2 reading)
How many words do you know?
(Measuring vocab size)



take a dictionary and count the number of words that
you know on 10 pages chosen at random. Divide the
total by 10 and multiply by the number of pages in the
dictionary.
Method by Goulden, Nation & Read (1990); more
sophisticated version in Schmitt (2000)
Paul Nation’s Vocabulary Levels Test
 measures number of words that are known at
various levels of frequency
8
Recommended sequence for learners

First 2,000 words


First 2,000 words + AWL


90% of text coverage of a text that a student would
typically read
First 2,000 words + AWL + Technical vocab


80% of text coverage
95% of text coverage of a text that a student would
typically read
First 2,000 words + AWL + Technical vocab +
most frequently used prefixes, roots and suffixes
9
Strategies for learning words of
different frequency levels
5,000 Word Level (general vocabulary)
•Training at guessing words in context
•Wide general reading : novels, newspapers and magazines
•Intensive reading of a variety of texts
•Advanced English Vocabulary workbooks
University Word Level (specialised academic vocabulary)
•Learn the words on the University Word List (Nation 1990) and Academic Word List
(Coxhead, 2000)
•Intensive reading of university texts
10,000 Word Level (a wide, general vocabulary)
•Activities similar to the 5,000 word level,
•combined with learning prefixes and roots
Receptive Knowledge vs.
Productive Knowledge


Tang (2007) found that primary five students in
Hong Kong knew about 40% of the most
frequent 5,000 words
However, their limited use of vocabulary in
writing suggested that more effort is needed to
convert the receptive knowledge into productive
knowledge
Tang, E. (2007). An exploratory study of the English vocabulary
size of Hong Kong primary and junior secondary school students.
The Journal of Asia TEFL. 4 (1), 125-144.
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What do you think are the ten most
frequently used words in English?
10 most frequently used words
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
West (1953)’s GSL (2000 words)




Based on a 5 million word written corpus
% given for different meanings and parts of speech
How to make reading texts more comprehensible for learners
Replacing difficult vocabulary with the GSL words, selected
according to:





Frequency
Universality (words used in different countries)
Range (words used to talk about a range of topics)
Usefulness (words used to define other words)
Despite its age, validated by later studies to be providing an
average of 82% text coverage (Hirsh & Nation, 1992; Sutarsyah,
nation & Kennedy, 1994)
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Frequency Lists

Nation and Waring (1997) (pre-session 2
reading) suggests that a list of high frequency
words used in a course should provide:
Core meaning of the word
 Different word forms and parts of speech (word
family)
 Variations of meaning (for polysemous words)
 Frequency information of the different meanings &
uses
 Collocations
 Restrictions on use of the word
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
Local Situation:
Sources of input for the EDB wordlists

Words taken from:




General Service List (GSL)
Most frequent words in British National Corpus (BNC)
Academic Word List (AWL)
Teacher representatives then further selected words
based on their judgment according to:



themes recommended in the Government’s Curriculum
Guides
vocabulary content of approved textbooks
other guidelines set by the research team (e.g. whether words
are used in Hong Kong, ease for learning, etc.)
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Sources for vocabulary lists
GSL
Classic list of
most frequent 2000 words
GENERAL words
BNC
100 million word collection
from written and spoken texts
(you can get BNC lists from http://www.lextutor.ca/list_learn/)
AWL
ACADEMIC words
570 words that occur frequently
in academic texts across disciplines
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Tom Cobb’s Compleat Lexical
Tutor (http://www.lextutor.ca/)



Test (to get receptive and productive tests of various word levels)
List_Learn (to learn words at various levels with an online concordancer and
dictionary; to get lists of words from 1k to 20k level and AWL and UWL)
Vocab Profiler (to see the vocab profile of one’s writing / to predict
“readability” of a text for learners)






% of words at 2000 word level
% of academic words
% of words from beyond the most frequent 2000
type-token ratio
Corpus-based Range checks whether a word is used more frequently in
spoken or written English in the Brown Corpus. It also checks the range of
a word in any of the 15 sub-corpora of the Brown Corpus, i.e. in which and
how many of the 15 sub-corpora a word can be found. The sub-corpora cover
a wide range of domains such as press, academic, and fiction.
Text-based Range allows you to upload up to 25 texts of your own and
check the range and frequency of a word in these 25 texts.
Type and Token


How many types are there in the following
sentence?
How many tokens (running words) are there in the
following sentence?
We need a vocabulary to talk about vocabulary.
Type-Token Ratio (also called “Lexical
Richness” or “Lexical Density”)

How many types and tokens do you see here?
Watch out! I said watch out!
4 types
 6 tokens / running words
 Type-token ratio: 4/6 (0.67)

20
Text written by a local HK 12-year



I have a rubber, an old, small rubber. Although it is so small
that I can not use it anymore, I still keep it carefully in my
drawer as it is so important for me.
That is a long, long time that I have my rubber. Four years ago,
when I was still an eight-years-old child, my parents bought me a
rubber as my birthday present. I put it into my pencil-box and
brought it to school everyday.
We had an interesting game in the past. We used our rubber to
play with in the game. We pushed our rubber one by one and
tried not to be pushed out at the desk by another rubber. We
pushed and pulled our rubbers, soon our rubbers became older
and smaller one day than one day.
Source: Arthur McNeill’s (2004)
“VocabProfile” of a student’s text
First
1000
words
88%

Second
1000
words
12%
Academic
words
(AWL)
0%
75 types /137 tokens : 0.55
Off-list words
(Less frequent
words)
0%
Examples from Hong Kong sample


Repetition of key words (need for lexical
substitution – synonyms, superordinates /
hyponyms, and pronoun substitution)
The need for lexical enrichment (adjectives and
adverbs)
Substitutes for “rubber”





It (pronoun)
One (pronoun)
Eraser (synonym)
Item of stationery (superordinate)
Tool? (superordinate)



I have a rubber, an old, small one. Although it is so
small that I can not use it anymore, I still keep it
carefully in my drawer as it is so important for me.
That is a long, long time that I have my favourite
chosen possession. Four years ago, when I was still an
eight-years-old child, my parents bought it for me as
my birthday present. I put it into my pencil-box and
brought it to school everyday.
We had an interesting game in the past. We used our
eraser to play with in the game. We pushed our
stationery one by one and tried not to be pushed out at
the desk by another opponent. We pushed and pulled
our weapons, soon our rubbers became older and
smaller one day than one day.
Text written by a local HK 16-year
old under exam conditions
Many students strive for academic excellency, but what is the
motivation behind their hardwork? In this essay, I am going
to explore the different aspects of learning, and analyse the
pros and cons of each motivating factor.
The hunger for knowledge and wisdom can motivate
students to learn. They hope to widen their horizons
through reading, watching educational programs, travelling
and other ways. To them, the world is a fascinating place,
full of wonders and mysteries to unravel. Their love of
learning motivates them to seek knowledge in all areas,
from science and mathematics to arts.
Source: McNeill’s (2004)
“VocabProfile” of a student’s text
First
1000
words
73%

Second
1000
words
6%
Academic
words
(AWL)
10.5%
69 types / 96 tokens = 0.72
Off-list words
(Less frequent
words)
10.5%
Pedagogical Implications


Process Writing may be used to improve
students’ lexical richess
Peer revision of writing drafts
insertion of adjectives and adverbs
 activation of recently learnt vocabulary

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Lexical enrichment
I was sweating. Ms Ip neared my table and put the
exam paper in front of me. I closed my eyes
and opened them a fraction of an inch. There,
on top of the paper, was a 33. My heart sank.
Then my teacher took away the paper and put
another one in front of me. I took it and saw an
88 in the mark box. The first paper belonged to
my neighbor, Sally.
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Lexical enrichment
I was sweating [adv]. Ms Ip neared my table [adv]
and put the [adj] exam paper in front of me. I
[adv] closed my eyes and [adv] opened them a
fraction of an inch. There, on top of the paper,
was a 33. My heart sank. Then my teacher [adv]
took away the paper and put another one in
front of me. I took it [adv] and saw an 88 in the
mark box. [Adv] the first paper belonged to my
neighbor, Sally.
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Lexical enrichment
I was sweating [heavily]. Ms Ip neared my table
[unexpectedly] and put the [horrible] exam
paper in front of me. I [immediately] closed
my eyes and [slowly] opened them a fraction of
an inch. There, on top of the paper, was a 33.
My heart sank. Then my teacher [swiftly] took
away the paper and put another one in front of
me. I took it [without thinking] and saw an 88
in the mark box. [Fortunately] the first paper
belonged to my neighbor, Sally.
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Discussion

What are the benefits of using word lists (such
as GSL, AWL)?
To design a vocabulary curriculum
 To decide which texts to use with students
 To decide which words in a text would cause
difficulty to students

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Local research on vocabulary size
and vocabulary knowledge

Cobb & Horst (2000) – post session reading




CityU students knew the most basic 2000 words; also performed well at 3000word level
But low scores on UWL level
Vocabulary growth over a period of 6 months: No
Fan (2001) – post session reading


Vocabulary scores positively correlate with language proficiency
Students from Chinese-medium schools and those with E in HKAL need help
with vocabulary
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