Content uploaded by Peter Yongqi Gu
Author content
All content in this area was uploaded by Peter Yongqi Gu on Feb 20, 2015
Content may be subject to copyright.
Learning Strategies for Vocabulary Development 105
Learning Strategies for
Vocabulary Development
Yongqi Gu
Victoria University of Wellington, New Zealand
ABSTRACT
This paper reports on a study of changes in vocabulary learning strategies and how these
changes are related to vocabulary development. One hundred Chinese EFL students
studying in a six-month pre-university English language enhancement programme
in Singapore answered a vocabulary learning questionnaire at the beginning and end
of the programme. The changes in their vocabulary learning strategies were matched
against the changes in their passive and active vocabulary. Findings suggested that at
the end of the six-month course, these participants used more varieties of vocabulary
learning strategies more frequently than they did six months ago, and that there was
more consistency between beliefs and strategies at the end of the course. It was also
found that many vocabulary learning strategies correlated significantly with passive
vocabulary size (positively) and with the percentage of active vocabulary at the K1
level (negatively). The relationship between VLS and active vocabulary beyond K1,
however, remained more complex.
KEYWORDS:
Second language learning; Learning strategies; Vocabulary
development
Vocabulary learning strategies (VLS) are intuitively appealing to teachers
and learners. It has also become a popular research topic among researchers in
the last two decades. Recent years have seen two books (Gu, 2005; Taka
č
, 2008)
and a number of articles on learner’s deliberate and strategic efforts in learning
vocabulary (e.g., Barcroft, 2009; Tseng & Schmitt, 2008). Most research so far has
demonstrated a meaningful relationship between vocabulary learning strategies
and learning results either through a correlational approach (e.g., Fan, 2003; Gu
& Johnson, 1996; Kojic-Sabo & Lightbown, 1999) or by establishing strategy
similarities and differences among learners with different degrees of success (Gu,
1994, 2003a; Moir & Nation, 2002).
Largely two types of learning outcome measures have been used: language
proficiency and vocabulary. Those who use the general language proficiency
measure tend to find positive and significant correlations between VLS and
language proficiency. For example, Mizumoto and Takeuchi (2008) investigated
the effect of VLS on TOEIC performance among a group of Japanese students
and found that, among a group of variables, “vocabulary learning strategies as
a whole had the greatest influence on TOEIC scores” (p. 17). Gu and Johnson
Reflections on English Language Teaching, Vol. 9, No. 2, pp. 105–118
106 Yongqi Gu
(1996) used both a general proficiency measure and a vocabulary size measure.
However, despite a generally positive correlation between VLS and English
proficiency and vocabulary size, Gu and Johnson reported that some strategies
aimed at vocabulary retention correlated significantly with vocabulary size but
not with general proficiency. This suggests a dynamic and prolonged nature of
vocabulary development from initial linking and storage of form-meaning pairs
(reflected to a certain extent in passive vocabulary size) to a gradual shift of these
words to the active stock and finally to an integration of words into the general
linguistic competence. A wide array of VLS should, therefore, be used at different
stages of learning to commit words to memory and to automate the use of these
words in real language use contexts.
The overwhelming majority of vocabulary measures in VLS studies have
been some type of passive vocabulary size measure, in other words, the number
of words a learner can recognize. A number of active vocabulary measures have
been proposed (Laufer, 1998; Laufer & Nation, 1999; Meara & Bell, 2001; Meara
& Fitzpatrick, 2000). However, none of these has been able to satisfactorily
measure active vocabulary size. One of the most widely used measures of active
vocabulary so far is arguably Laufer and Nation’s (1995) Lexical Frequency Profile
(LFP), which sketches the profile of a learner’s active vocabulary use by providing
the percentage of words used that belong to the first 1,000 most frequently used
words, the percentage of the second 1,000 words, that of the Academic Word List,
and that of words that do not fall into the lists compared (Morris & Cobb, 2004;
Muncie, 2002). Probably due to this lack of a single satisfactory measure of active
vocabulary (Meara & Olmos Alcoy, 2010; Read, 2000), practically no VLS study
has looked at how strategies are related to the growth of active vocabulary.
Besides the lack of knowledge on productive vocabulary learning strategies,
very little is known about the change of VLS over time; nor do we know much
about the effect of this change on the development of vocabulary along both
passive and active dimensions. The only study I am aware of is Cortazzi and Jin’s
(1996) cross-sectional description of VLS changes of 212 university students in
China. These students were asked to report on a questionnaire the strategies they
were using, how effective they thought these strategies were, and recall on their
use of the same strategies when they were in secondary schools. Cortazzi and
Jin reported that major changes occurred from secondary school to university in
terms of both VLS and their perceived effectiveness. Strategies used in secondary
schools included mainly reading textbooks, listening to the teacher and taking
notes; whereas a much larger repertoire was reported in university, including more
opportunities for use such as writing essays, listening to radios, and talking to
English teachers and native speakers. Some ways of learning vocabulary remained
remarkably stable. These included classroom based activities such as listening
to the teacher and taking notes. Outside the classroom, memorizing vocabulary
remained the most widely used strategy.
In addition to proficiency growth that demands different strategy use, learning
strategies shift with contexts of learning (Gu, 2003b). In the current study, I am
interested to find whether the dramatic change of learning context from an EFL
environment in China to an ESL context in Singapore would change the VLS
Learning Strategies for Vocabulary Development 107
a group of Chinese students used. I examine if the change of VLS is related to
growth in passive and active vocabulary. In particular, the present study aims to
answer the following two research questions:
1. Are there significant changes in vocabulary learning strategies after a six-
month English enrichment programme in Singapore?
2. How are vocabulary learning strategies related to vocabulary development
(passive vocabulary level and active vocabulary use) at the beginning and
end of the programme?
Method
Subjects
Every year, the Singapore government selects a group of students from universities
in China and supports their study at a university in Singapore. These students
need to complete a six-month English language enrichment programme in order
to be able to cope with English-medium instruction in Singapore. The students
who participated in this study were selected from 14 universities in China
where they had just begun tertiary studies. They filled in a vocabulary learning
strategies questionnaire immediately after a placement test at the beginning of
the proficiency enrichment programme in Singapore. The same questionnaire
was again administered six months later during the last week. One hundred
complete sets of pre- and post-questionnaires were collected at the end of the
programme. Seventy three of these were from male students; and 27, from
females. The participants’ age ranged from 17 to 21, with the majority of them
19 (51%) and 18 (30%). The voluntary nature of the project meant that the data
were not complete for all students. This will be reflected in the varied number of
participants for various calculations.
Instruments and Procedures
The instrument used for the elicitation of VLS was Vocabulary Learning
Questionnaire (Version 5, or VLQ5), a ninety-item update by Gu and Hu (2003)
of Gu and Johnson’s (1996) VLQ. Each of the ninety statements was followed by
a 7-point Likert scale. The Beliefs section ranged from 1, Absolutely disagree, to 7,
Absolutely agree. The Strategies section ranged from 1, Absolutely untrue of me, to
7, Absolutely true of me. Table 1 lists the major dimensions and categories of VLS,
which the VLQ covers (Version 5).
The first administration of VLQ5 at the beginning of the programme required
the participants to recall how they had been learning vocabulary the previous two
years before they moved to Singapore. The second administration at the end of
the programme required the respondents to answer according to how they were
learning vocabulary during the six-month intensive English language training in
Singapore. To avoid misunderstanding, the Chinese version of VLQ5 was used
for both occasions. Table 2 reports the Cronbach’s alpha (α) reliability (internal
consistency) for the two administrations of VLQ5. The reliability of the first
108 Yongqi Gu
Table 1
VLQ5: Dimensions, Categories, and Items (Gu & Hu, 2003)
Number of Number of
Dimensions Categories variables items
Beliefs 2 12
Metacognitive Selective attention 2 10
strategies Self-initiation
Cognitive Initial handling Guessing 2 10
strategies Dictionary use 3 14
Note-taking 2 8
Reinforcement Rehearsal 3 11
Encoding 6 20
Activation 1 5
Total 21 90
Table 2
VLQ5 Item Distribution and Reliability Statistics
Number of
Categories Strategies items α1 α2
Beliefs about Words should be memorized. 6 .7116 .7744
vocabulary Words should be learned through use. 6 .5940 .6069
learning
Metacognitive Selective attention 5 .6829 .7631
strategies Self-initiation 5 .7062 .6515
Contextal Wider context 5 .7224 .7282
guessing Immediate context 5 .6716 .7245
Dictionary Dictionary strategies for comprehension 4 .7157 .6902
strategies Extended dictionary strategies 5 .7894 .7329
Looking-up strategies 5 .7236 .6272
Note-taking Meaning-oriented note-taking 4 .6488 .6527
Usage-oriented note-taking 4 .7151 .6335
Rehearsal Use of word lists 5 .6913 .6504
strategies Oral repetition 3 .5516 .4931
Visual repetition 3 .5421 .5590
Encoding Association/elaboration 4 .4973 .6706
strategies Visual encoding 4 .6992 .7177
Auditory encoding 3 .7318 .7168
Use of word structure 3 .7756 .6773
Semantic encoding 3 .6544 .5100
Contextual encoding 3 .6725 .6880
Active use Activation strategies 5 .7557 .7442
Learning Strategies for Vocabulary Development 109
administration is labelled α1, and that of the second administration is labelled
α2.
As a quick passive vocabulary measure administered together with the
questionnaires, the 3000-word level of Nation’s (2001)Vocabulary Levels Test
was combined with Goulden, Nation, and Read (1990). Crude as it was, the
combined measure was thought to be indicative of the participants’ learning
background1 as well as their passive vocabulary level at the time.
Active vocabulary was measured by the Lexical Frequency Profile (LFP).
This was based on two of the participants’ in-class argumentative compositions
collected from their writing class at the beginning and end of the programme.
Their first composition focused on the brain-drain phenomenon in developing
countries, while the last composition was about their arguments for or against
cloning. Each composition was typed and an LFP was obtained by submitting it
to Tom Cobb’s Vocabulary Profiler at http://www.lextutor.ca/vp/. For the purpose
of this project, the LFP included the number of types, tokens, and word families
contained in each composition. It also included the percentages of words that
fall into the first 1000 most frequent words (K1), the second 1000 most frequent
words (K2), words that belong to the Academic Word List (AWL) (Coxhead,
2000), and off-list words.
Analysis
Changes in passive and active vocabulary and changes in VLS over the six-month
period were captured by paired t-tests comparing the respondents’ pre- and post
vocabulary measures as well as their answers to the pre- and post questionnaires.
To examine the effect of strategy use on vocabulary development over the six-
month programme, Pearson correlations were obtained between VLS on the
second questionnaire and the passive and active vocabulary measures.
Findings
Changes in Vocabulary
Significant improvement in both passive and active vocabulary was found across
the board (Table 3). The passive vocabulary at the end was significantly larger
than that at the beginning of the programme. The one-hour in-class composition
students wrote in their last week contained significantly more tokens, more types,
and more word families than the composition they wrote in the first week of
the programme. An average of 89% of the first composition was made up of the
first 1000 most frequent words. This percentage was reduced to 83% by the end
of the six- month programme. In the meantime, the average percentage of K2
1 Most Chinese students place a great emphasis on expanding their vocabulary size, often indiscriminately
(Cortazzi & Jin, 1996). For example, many spend years memorising vocabulary lists or even dictionary
entries from A to Z. This results in some very low frequency words being remembered. It was therefore
decided to use Goulden, Nation, and Read (1990) to capture these words that another level in the VLT,
e.g., 5,000-word level, would not be able to capture.
110 Yongqi Gu
words increased from 3% to 5%; the average percentage of AWL words increased
from 2% to 5%, and off-list words increased from 6% to 7.45%. These changes
indicate in general a significant increase in active vocabulary use. Type/token ratio
dropped significantly as well, indicating that the increase in different words used
in compositions did not catch up with the increase of the number of words used.
Overall, these figures show a very healthy profile of vocabulary development for
this group of learners over a six-month period.
Changes in VLS
Table 4 reveals that the participants were active vocabulary learners before they
started the Singapore programme. For eight out of the 21 variables, the mean score
was above 4.50; and the mean for Self initiation was 4.82. The participants did
not believe in the memorization of words (M = 2.95) and believed that words
should be learned through use (M = 5.44). Their most often used strategies
were dictionary use (for comprehension = 5.40, for usage = 5.50, and look-up
strategies = 5.12) and contextual guessing (using global context = 5.22, using
local context = 4.85). Their least used strategies included visual repetition (M =
3.47) and remembering semantically related words together (Semantic encoding
= 3.28). At the end of the six-month programme, the strategies often used at the
beginning were still often used. The difference was: all but visual repetition (M =
3.54) and memorization (M = 3.25) were above the mid-point of 4.00. Thirteen
Table 3
Changes in Passive and Active Vocabulary
M n SD t p
Passive Vocabulary size Pre 12.66 85 4.60 -18.33 .000
Vocabulary Post 20.72 85 5.50
Active Tokens Pre 392.86 83 73.66 -7.47 .000
Vocabulary Post 454.02 83 70.57
Types Pre 166.95 83 28.35 -4.55 .000
Post 180.61 83 30.16
Type/Token ratio Pre .43 83 .050 5.27 .000
Post .40 83 .052
Families Pre 129.14 83 21.46 -5.10 .000
Post 140.28 83 22.57
K1 Pre 89.16 83 3.36 12.88 .000
Post 83.04 83 3.62
K2 Pre 2.98 83 1.47 -8.03 .000
Post 4.96 83 1.68
AWL Pre 1.96 83 1.51 -11.36 .000
Post 4.57 83 1.77
Off-list Pre 6.00 84 2.31 -4.40 .000
Post 7.45 84 2.47
Learning Strategies for Vocabulary Development 111
Table 4
Vocabulary Learning Strategies Before and After the 6-month Programme
VLS M n SD t p
Beliefs Memorize words Pre 2.95 95 1.03 -2.65 .009
about Memorize words Post 3.25 95 1.05
vocabulary Acquire and use Pre 5.44 94 .69 -1.22 .227
learning Acquire and use Post 5.53 94 .56
Meta- Selective attention Pre 4.19 96 1.04 -5.51 .000
cognitive Selective attention Post 4.72 96 .92
strategies Self-initiation Pre 4.82 97 1.04 -1.53 .130
Self-initiation Post 4.97 97 .86
Cognitive Contextual Wider context Pre 5.22 97 .81 -.61 .543
strategies guessing Wider context Post 5.26 97 .74
Immediate context Pre 4.85 96 .82 -5.15 .000
Immediate context Post 5.21 96 .76
Dictionary Dictionary for
strategies comprehension Pre 5.40 95 1.09 -.37 .713
Dictionary for
comprehension Post 5.45 95 .89
Extended dictionary use Pre 5.50 92 .97 .85 .400
Extended dictionary use Post 5.42 92 .81
Look-up strategies Pre 5.12 92 1.04 -2.28 .025
Look-up strategies Post 5.32 92 .75
Note-taking Note taking meaning Pre 4.62 98 1.16 -4.71 .000
strategies Note taking meaning Post 5.17 98 .86
Note taking use Pre 4.61 99 1.12 -1.40 .164
Note taking use Post 4.74 99 .92
Rehearsal Use of word lists Pre 3.82 93 1.11 -4.59 .000
strategies Use of word lists Post 4.36 93 .91
Oral repetition Pre 4.05 100 1.17 -.82 .415
Oral repetition Post 4.16 100 .99
Visual repetition Pre 3.47 97 1.30 -.46 .650
Visual repetition Post 3.54 97 1.19
Encoding Association/elaboration Pre 3.88 95 1.00 -4.01 .000
strategies Association/elaboration Post 4.31 95 1.00
Visual encoding Pre 3.74 99 1.19 -2.93 .004
Visual encoding Post 4.08 99 1.05
Auditory encoding Pre 3.93 100 1.25 -3.98 .000
Auditory encoding Post 4.42 100 1.10
Word structure Pre 4.11 97 1.34 -5.88 .000
Word structure Post 4.80 97 1.10
Semantic encoding Pre 3.28 98 1.12 -8.27 .000
Semantic encoding Post 4.20 98 1.00
Contextual encoding Pre 4.16 98 1.19 -3.71 .000
Contextual encoding Post 4.57 98 1.03
Active Use Activation Pre 4.17 96 1.13 -3.98 .000
Activation Post 4.58 96 .94
112 Yongqi Gu
out of the 21 variables had a mean score above 4.50. In other words, more varieties
of strategies were used and each strategy was used more frequently than at the
beginning of the programme.
Table 4 also suggests that post scores were consistently higher than pre-
scores for all but one variable (extended dictionary use). Except for believing
in memorization and association/elaboration, all pre- standard deviations were
larger than post standard deviations. The former means that the participants
used more VLS more often at the end of the programme; the latter indicates
that the beliefs and strategic learning behaviours of these learners became more
consistent at the end of six months of intensive English language training. In all,
13 out of 21 variables showed statistically significant differences before and after
the programme. Understandably, the most often used and the least often used
strategies did not reveal significant differences.
VLS and Vocabulary Development
Answers to Research Question 2 can be found in Table 5. For most strategies,
more frequent use of VLS was positively and significantly correlated with passive
vocabulary size. The only strategy that was negatively and significantly correlated
with passive vocabulary was visual repetition (r = -.359, p < .01). This was
consistent with previous research (e.g., Gu & Johnson, 1996).
The relationship between VLS and active vocabulary, however, was more
complex than anticipated. VLS were closely related to active vocabulary use
of the first 1000 most frequent words. The two belief variables did not reveal
significant correlations with the use of K1 words. But six of the 19 strategy variables
showed significant and negative correlations with the percentage of K1 words
in the final composition. In other words, the more often VLS were used, the less
likely students would stick to K1 words in their active use. Beyond the K1 level,
however, the picture was less clear. Believing in memory (r = 312, p = .004) and
using word lists (r = .248, p = .025) were found to be significantly correlated to
the percentage of K2 words. The use of off-list words correlated with Selective
attention (r = .331, p = .002), using word lists (r = .263, p = .016), visual encoding
(r = .363, p = .001), auditory encoding (r = .284, p = .008), semantic encoding
(r = .240, p = .027), contextual encoding (r =.247, p = .022), and activation
(r = .252, p = .019). These findings suggest that for these students who were still
developing a basic competence in language use, those who deliberately tried to
memorise more words would venture more into the use of words beyond the K1
level. Likewise, self-initiation was the only variable that significantly correlated
with type/token ratio, suggesting that for students at this level, venturing into the
use of unfamiliar words is a motivation as well as a strategy issue. In sum, VLS
were found to be more related to passive vocabulary and more to K1 words than
to less frequent words beyond K1. This phenomenon confirms Laufer’s (2005)
contention that lexical knowledge and lexical use develop along different paths,
and that small increases in vocabulary size are not necessarily reflected in active
use.
Learning Strategies for Vocabulary Development 113
Table 5
VLS and the Passive and Active Use of Vocabulary
Post-
receptive Post-productive vocabulary
vocabulary
Type/
Vocabulary Off Token
size K1 K2 AWL list ratio
Beliefs Words should be r -.144 -.084 .312** -.036 -.061 -.019
about memorised n 89 82 82 82 85 82
vocabulary Words should be r .273(*) .074 -.144 .001 -.002 .003
learning learned thru use n 85 79 79 79 82 79
Meta- Selective attention r .096 -.319** .188 .020 .331** .011
cognitive n 89 82 82 82 85 82
strategies Self initiation r .246(*) .037 -.085 .075 -.057 .285**
n 90 83 83 83 86 83
Contextual Wider context r .171 -.181 -.003 .071 .211 .040
guessing n 90 83 83 83 86 83
Immediate context r .290(**) -.071 -.050 .090 .089 -.071
n 90 82 82 82 85 82
Dictionary Dictionary for r .340(**) .069 -.121 .034 -.029 .185
use comprehension n 89 82 82 82 85 82
Extended dictionary r .430(**) .001 -.101 .107 .011 .214
use n 88 81 81 81 84 81
Look up strategies r .225(*) -.097 .117 .129 -.011 .060
n 86 81 81 81 83 81
Note- Note taking meaning r .208(*) -.254* .043 .205 .205 .113
taking n 90 83 83 83 86 83
Note taking use r .210(*) -.102 .095 .125 -.005 .174
n 90 83 83 83 86 83
Rehearsal Word list r .170 -.265* .248* -.063 .263* .067
n 88 81 81 81 83 81
Oral repetition r .054 -.226* .099 .093 .206 .031
n 90 83 83 83 86 83
Visual repetition r -.359(**) -.014 -.003 -.141 .129 -.130
n 89 82 82 82 85 82
Encoding Association r .093 -.132 .081 -.062 .205 -.013
n 89 83 83 83 86 83
Visual encoding r .209(*) -.194 .060 -.150 .363** .051
n 89 82 82 82 85 82
Auditory encoding r -.040 -.258* .100 .047 .284** .056
n 90 83 83 83 86 83
Word structure r .345(**) -.122 .087 -.013 .141 .113
n 89 83 83 83 85 83
Semantic encoding r .338(**) -.196 .113 -.010 .240* .147
n 89 83 83 83 85 83
Contextual encoding r .203 -.176 .046 -.036 .247* .004
n 90 83 83 83 86 83
Active use Activation r .124 -.255* .150 -.012 .252* .148
n 90 83 83 83 86 83
Post-Questionnaire
** p < 0.01 (2-tailed) * p < 0.05 (2-tailed)
114 Yongqi Gu
Discussion
VLS Changes and Vocabulary Growth
This study discovered the following main patterns of VLS use before and after
the 6-month programme: (a) The most often used and the least often used
strategies remained the same, (b) more varieties of strategies were used and
each strategy was used more frequently at the end of the six-month programme,
and (c) the beliefs and strategic learning behaviours of these learners became
more consistent at the end of the programme. These findings clearly show that
significant strategy changes had occurred during these six months. Differences in
the learning environment may well be one of the main factors that led to these
changes in strategy use. Before the participants’ arrival in Singapore, their main
learning experiences were in their secondary schools in China, where English
was only a subject of study in class; and teachers and textbooks were the main
sources of input. The few months they had in various Chinese universities were
largely similar in terms of the rarity of English language exposure. In contrast,
the six-month intensive English enhancement was a total immersion experience,
in which English was not only the major focus of study, but also used all the
time for all courses. English was suddenly a live language that could be used to
get things done even in the streets. These environmental changes together with
the high stakes nature of the programme demanded different ways of learning,
including vocabulary learning.
Laufer (1991) singled out two factors that could explain the L2 learner’s
lexical development, features of the learning situation and features of the learner.
Both of these, I argue, are mediated through the learner’s self-initiated efforts
and strategic learning. With the change of learning situations, different VLS will
need to be deployed. Contextual influence upon the ways vocabulary is learned
has been found elsewhere. Laufer and Paribakht (1998), for example, found that
vocabulary knowledge differed between foreign and second language contexts,
and that the length of stay beyond two years in the target language community
had an impact on the gap between passive and active vocabulary.
Likewise, as learner proficiency improves dramatically, learning strategies
more suitable for a higher level of language learning and use will need to be
applied. This phenomenon is explained in Laufer’s (1991) “active vocabulary
threshold hypothesis”:
Even though our passive vocabulary develops throughout our lifetime, long
after the grammar of a language has been acquired, our productive lexicon
will grow only until it reaches the average level of the group in which we are
required to function (p. 445).
In other words, when learners reach a point where they do not perceive the need to
enrich their active vocabulary any more, their efforts and strategies in developing
a richer productive vocabulary will stop.
Learning Strategies for Vocabulary Development 115
VLS and Vocabulary Learning Tasks
One of the foci of this study has been the distinction between the learning of
active and passive vocabulary. Probably due to technical difficulties in studying
active vocabulary, the lion’s share of attention on L2 vocabulary acquisition has
been focused on the development of passive vocabulary. Research so far has shown
that these two aspects of vocabulary follow different routes of development,
and that VLS for the development of active vocabulary has largely remained
unknown. Fan (2000) is probably the only study that explicitly tries to discover
strategies for active vocabulary. However, none of the seven strategy items in her
VLS questionnaire that were significantly correlated to her “active vocabulary
test” scores (controlled recall) belonged to strategies that aim for the deliberate
and active use of vocabulary.
It was a little surprising that no significant correlations were found between
the percentage of the AWL and VLS. A closer analysis reveals that the importance
of the AWL as a learning focus had not been communicated to the learners. The
Singapore intensive English programme did not single out the AWL as a type of
vocabulary that needed special attention. Learning strategies matter most for those
words learners pay special attention to. This may explain the lack of meaningful
correlations between the AWL and VLS.
The significant negative correlations between VLS and K1 words do suggest
the importance of VLS in the development of active vocabulary. However, at
least for this group of learners, this was probably constrained to the first 1000
most frequent words only. A combined K1+K2 did not reveal many meaningful
correlations with VLS, suggesting that K1 and K2 words are probably developed
along different lines. Beyond K2 has been used as a free active vocabulary measure
(Laufer, 1998; Laufer & Paribakht, 1998). In view of the findings from this study,
I suggest that K1 and Beyond K1 be used as more sensitive measures of active
vocabulary for future research of similar learners.
Another insight from this study is that existing VLS measures mostly focus
on strategies for passive vocabulary learning tasks, and that VLS for the active use
of vocabulary in a second language has not received enough attention. Despite
the explicit “Activation” category of strategies that focused on the active use of
known or new words, the VLS taxonomy used in this study shares with all major
taxonomies the same lack of attention to strategies that aim for the development
of active vocabulary. Schmitt’s (1997) taxonomy includes discovery strategies and
consolidation strategies. No items can be found that relate to the development
of active vocabulary. Stoffer’s (1995) “strategies involving authentic language
use”, Nation’s (2001) “generating” and Fan’s (2003) “known words” seem to be
the most relevant, but these systems cover even less of an emphasis than Gu and
Johnson’s (1996) “activation strategies”. It may well be true that teachers and
learners do not pay as much attention to active vocabulary as they do to passive
vocabulary. However, for learners beyond a threshold level of proficiency, VLS
aiming at the development of active vocabulary may become a make-or-break
lever. Further research is definitely needed on the nature of such strategies and
the effect they may have on learning results.
116 Yongqi Gu
Conclusion
VLS are an indispensable tool in describing and explaining the vocabulary
development of a foreign language. VLS are also a tool in empowering learners
to make wise decisions in terms of what to learn and how to learn. This study
focused on the change of VLS when a group of EFL learners moved from China
to Singapore to begin their tertiary education. As they progressed in a six-month
intensive English proficiency enhancement programme, their passive and active
vocabulary improved significantly. Some of these changes could be attributed to
the changes in their VLS which in turn underwent significant shifts. VLS were
found to be related to the growth of passive vocabulary and the participants’ free
use of active vocabulary at the K1 level. Beyond the first 1000 most frequent words,
however, the pattern was not so straightforward. This is thought to have provided
evidence to support Laufer’s (1991) “active vocabulary threshold hypothesis”, in
that the development of active vocabulary follows a different pattern from that
of passive vocabulary, and that beyond a threshold level of active vocabulary,
growth is dependent on the learner’s perceived need for use.
ACKNOWLEDGEMENT
I am indebted to Guangwei Hu for his commitment to earlier phases of the
project.
THE AUTHOR
Yongqi Gu is a Senior Lecturer at Victoria University of Wellington, New Zealand.
He is also an adjunct research fellow at the National Research Centre for Foreign
Language Education in China. He has extensive teaching and teacher training
experiences in mainland China, Hong Kong, Singapore, and New Zealand. His
main research interests include learner strategies, vocabulary acquisition, and
language assessment.
Correspondence concerning this article should be directed to Yongqi Gu, School
of Linguistics and Applied Language Studies, Victoria University of Wellington,
PO Box 600, Wellington 6140, New Zealand; e-mail: peter.gu@vuw.ac.nz.
Learning Strategies for Vocabulary Development 117
118
Yongqi Gu
