Growing Academic
Vocabulary with a Collaborative On-line Database
Marlise Horst,
Concordia University, Montreal
Tom Cobb,
Université du Québec à Montréal
Paper presented
at IT-MELT '01, Polytechnic University of Hong Kong, June 2001.
Most educators would agree that one of the most
exciting aspects of using computerized resources for second language
acquisition is the potential of these resources for meeting the very diverse
needs of individual learners efficiently and effectively. We would argue that nowhere is the need for individualized
instruction greater than in the area of academic vocabulary for learners
intending to do university work in English. The basis for this claim is the
fact that many university-bound ESL learners already know the core vocabulary
of English; that is, they have progressed beyond the point where an all-purpose
course in the most basic thousand words would be equally beneficial for all. As
proficiency and vocabulary size increase, learners vary hugely in what they
know and what they need to learn (Nation, 1990). Thus, the Chinese speaking
learner arriving in Canada to study computer science may already know - as a
result of study in his home country - many words that will be useful for doing
academic work in English. But he is likely to know a very different set of
items from the student seated next to him in ESL class, for example a
Francophone learner from Quebec intending to study stage design. It is also
clear that the words these two students will want to study to prepare for
courses in their majors will be quite different. The challenge for the course designer
is to build a course that both of these students (and many others) can profit
from. Our proposed answer to the challenge is to put technology tools in the
hands of learners so that they can construct the courses they need for
themselves. In this paper we describe how we tested this idea in an
experimental ESL vocabulary course for academic learners at Concordia
University in Montreal.
The course-design
question the authors set out to answer can be stated as follows: How can we
ensure that a vocabulary course offers academic learners of varying L1
backgrounds, L2 proficiency levels, and academic objectives a significant
opportunity to focus on the words they need to know? Can one course address the
needs of students preparing for study in content domains as varied as computer
science and stage design? In addition to tailoring a course to meet students'
vocabulary needs as effectively as possible, we were interested in
investigating the role of technology in providing individualized instruction,
and we wished to test a number of research claims about instructed vocabulary
learning as well. The following section details the principles that guided the
design of the course and outlines our research agenda.
Designing the course
The guidelines
the designer/researchers arrived at were as follows:
·
Start with reading
as a source of new vocabulary.
·
Provide technology
tools for students to create the course they need.
·
Recognize that
studying domain-specific vocabulary is important.
·
Recognize that
knowing subtechnical academic vocabulary is crucial.
·
Raise awareness
of proven word learning strategies.
·
Challenge
learners to study hundreds of new words.
Each of these
will be discussed in turn.
Start with
reading
There are at
least four good reasons for focusing an academic vocabulary course on reading.
First, although university-bound students need vocabulary knowledge to be able
to speak and write in content courses, it is clear that the ability to read and
understand course content as presented in textbooks is central. People who know
more words understand more of what they read than people who know fewer; indeed
reading comprehension is so closely associated with vocabulary knowledge that
test designers have had difficulty in distinguishing between the two (Read,
1997). Secondly, receptive knowledge represents the starting point of the word
learning process. Generally, L1 and L2 learners alike begin to feel they know a
new word when they can recognize its meaning when they read (or hear) it, while
more active knowledge such as the ability to produce a fully correct definition
of the word or to use it accurately in an original sentence tends to come later
(Wesche & Paribakht, 1996).
Thirdly, analyses
of large corpora of written and spoken language indicate that written texts are
much more likely to contain words that would be unfamiliar to intermediate ESL
learners than spoken texts. Spoken discourse makes heavy use of common words -
words that most intermediate ESL learners would probably already know - and
rarely presents items outside a list of the 2000 most frequent words of English
(West & Stanovich, 1991). It is clear that requiring students to read
widely is a good way of ensuring they have many opportunities to meet new words
beyond this most basic level. Finally, reading passages are natural ready-made
learning materials for vocabulary acquisition because they present unfamiliar
words in authentic sentence and discourse contexts. These contexts can provide
the learner with valuable grammar information, rich associative links to other
words, and importantly, useful clues to meaning.
In implementing
an individualized course with reading at its centre, the course designers felt
it was important to give the students a role in selecting the texts that would
serve as the basis for their vocabulary learning. So instead of prescribing a
core text, we required students to buy (or read on-line) a quality newspaper
and read any two articles of their choice each week. The newspaper that we
chose for this purpose was the Focus section of the weekend issue of the Toronto
Globe and Mail. This weekly supplement presents well written essays on a
variety of topics written in a style that can be termed "academic."
Each week students were required to prepare brief oral or written summaries of
the two articles they had chosen. They were also expected to look up the
meanings of new words they encountered in dictionaries.
Provide
technology tools for students to create the course they need
The next question
that the course designers faced was how we might use the valuable information
gleaned in individual word quests to build a student-generated vocabulary
course that all could access easily. While we recognized that not every student
would be interested in each of every other student's dictionary findings, we
reasoned that each student would belong to a number of constituencies within
the class that had common vocabulary needs. That is, a new word encountered by
one Francophone learner in a newspaper text might well be unfamiliar to other
Francophone learners in the group. Similarly, if a student interested in
biology read a piece about Nova Scotia fisheries and was curious about the
meaning of crustacean, then other science majors who opted to read the
same article might well be wondering about it too. If the pool of word findings
was large, the chances that each student would find a useful body of new
material to study would be increased. Thus the technology design challenge was
to offer students a simple format for creating their own course by building up
a large collection of vocabulary findings and to provide them with an easy way
to share the collection with each other. Clearly, computer technology in the
form of a collaborative on-line database offered a solution.
The collaborative
project we opted for was an on-line Word Bank. Figure 1 shows the homepage
which the second author designed for the course. The button for word bank entry
appears at the top of the middle column under Focus Activities. Clicking on
this button brings up a data entry template which presents the student with
spaces for entering a word, followed by an example of the word used in context,
word class information, a dictionary definition, and the contributor's name.
Each week the group of 33 students were required to enter five new words they
had encountered in their newspaper reading in the Focus Word Bank. A sample of
the 165 entries made in Weeks 1 and 2 of the course is shown in Figure 2.
Figure 1
Homepage for
Academic Vocabulary Development, an experimental ESL course
Figure 2
Sample entries to
collaborative on-line database, the Focus Word Bank
So far our
rationale for a collaborative on-line databank has emphasized advantages such
as the efficient dissemination of a large body of material and the potential
for individualizing instruction. But another important benefit is the word
learning that is likely happen when a student creates a Word Bank entry.
Hulstijn, Greidanus and Hollander (1996) have shown that the act of looking up
a word in a dictionary increases the chances that the learner will remember
it; it seems likely that the act of
typing out a definition and example sentence also contributes making the new
word memorable.
In addition to
the on-line Word Bank, an on-line dictionary and concordancer were made
available to support learners' vocabulary learning. These computer tools will
be described in a later section.
Recognize that
studying domain-specific vocabulary is important
In the interest
of living up to the name of the course (Academic Vocabulary Development), we
felt it should offer participants the opportunity to study words specific to
their chosen fields of study. We assumed that the idea of learning new science,
economics, or art history vocabulary would appeal to students and it was clear
that on-line technology could help address a range of individual interests.
That is, the tools used to build a class word bank for general newspaper
reading could also be used to build mini-wordbanks in specialist domains.
To implement this
idea, we divided the students into special interest groups according to the
academic field they intended to study. Five groups were formed around the
following domains: arts, business, computers, science, and education. Each
student was asked to locate a short reading on a topic in their field to share
with other group members. Three times during the 13-week course (that is, once
a month) students read two of these readings, summarized them, and entered five
new words into the Specialist Word Bank, just as they did on a weekly basis
with their newspaper reading. The entry form for this task can be accessed from
the course home page by clicking on the button at the top of the third column
entitled "Specialist Activities" (see Figure 1). The specialist data
base allowed users to group word entries in alphabetical order, by student
contributor, or by specific domain. Figure 3 shows a sample of Specialist Word
Bank entries grouped by domain: here we see items contributed by members of the
Business Group.
Figure 3
Sample entries to
collaborative on-line database, the Specialist Word Bank
Recognize that
knowing subtechnical academic vocabulary is crucial.
Perhaps one of
the most useful research findings to come out of corpus analyses of English texts
is the identification of a core set of about 850 word families that occur
frequently and consistently in academic texts - across disciplines. (A word
family is defined as a root word, e.g. produce, and its derived forms,
e.g. product, production, unproductive, etc.) The importance of being
able to recognize the meanings of word families on what is known as the
University Word List (Xue & Nation, 1984) is made dramatically clear in two
versions of an authentic textbook passage about increasing forest productivity
shown below (from Nation, 1990). In the first version, all items that are not
among the 2000 most common word families of English appear as blanks. Thus,
reading this passage simulates the experience of ESL learners with no more than
a basic knowledge of English when they are confronted with university texts. It
is possible to get some sense of subject and gist in this version but much of
the informational content is simply unavailable.
Version 1
....the increasing wood supplies will _______ a larger _______
force, an improved roading network, and _______ _______ and _______ _______ .
If the trees are to be _______ , then certain _______ must be made. They will
include _______ in: logging machinery and _______ ; logging trucks, and other
_______ _______ for the _______ of _______ products; ....
Version 2
....the increasing wood supplies will require a larger labor
force, an improved roading network, and expanded transport and processing
facilities. If the trees are to be exported, then certain investments must be
made. They will include investments in: logging machinery and equipment;
logging trucks, and other _______ required for the transport of processed
products; ....
In the second
version of the same text, the words that are shown are both high frequency
words from the 2000 list and UWL words. Reading this version simulates the
experience of an ESL learner who comes to the task of academic reading armed
with knowledge of all items on both lists. Now only one blank remains: the text
suddenly becomes comprehensible and the missing item (vehicle) can be readily
guessed from context. Interestingly, the UWL items that make the difference are
not technical words specific to the domain of forestry but rather all-purpose
or "subtechnical" words like require, labor, process and equipment.
It is clear that university-bound learners stand to profit a great deal from
studying this key set of items.
The
"covering" power of the UWL is further detailed in Table X which is
based on analyses by Nation and Waring (1997) and Sutarsyah, Nation and Kennedy
(1994). The fourth line suggests that an ESL student who knows both the 2000
most frequent words of English and the items on the UWL will understand 90% of
the running words in a typical academic text, regardless of its subject matter.
Since a receptive vocabulary size of about 3000 words (2000 + UWL = 2800) has
also been identified as the watershed between comprehension and
noncomprehension in studies of academic reading by Laufer (refs), we felt there
were compelling reasons to prioritize the study of the UWL in our experimental
course.
Table 1
Frequent English
words and coverage of academic texts
No. of word
families |
Percent
coverage |
Ratio
unknown:known |
70 |
50 |
1:2 |
1000 |
75 |
1:4 |
2000 |
80 |
1:5 |
2000 + UWL |
90 |
1:10 |
2000 + UWL +
Specialist |
95 |
1:20 |
128,000 |
100 |
-- |
The fifth line of
Table 1 reflects findings by Sutarsyah, Nation and Kennedy (1994). Their work
indicates that knowledge of several hundred words that recur frequently in the
texts of a particular subject domain can offer additional coverage such that a
reader who knew these would know as many as 95% of the running words. This
suggested to us that the plan to devote some attention to domain specific words
was justified. Unfortunately, however, lists of high frequency core vocabulary
for specific domains have not (yet) been compiled. So it was not possible to
specify exactly which business, arts or science words were important for our
learners to study. Nonetheless, we assumed the scheme outlined above for reading
in subject domains and contributing new vocabulary to the Specialist Word Bank
would represent a useful step in preparing the learners for study in their
chosen fields.
To understand
where the 35 students registered for the experimental course stood in relation
to the word frequency zones identified as important for academic reading
success, we administered an updated version of the Vocabulary Levels Test
(Nation, 1990; Schmitt, 2000). This instrument uses a multiple-choice cluster
format to test receptive knowledge of items sampled from each of five zones:
the 2000 most frequent words, words on the 3000, 5000, 10,000 most frequent
lists, and the Academic Word List (a recent update of the UWL; Coxhead, 2000).
The test requires testees to match items to simply worded definitions. An
example of a question cluster from the section that tests the Academic Word
List is shown in Table 2.
Table 2
Sample question
from the AWL section of the Vocabulary Levels Test: Version 1 (Schmitt, 2000)
1. benefit 2. labor 3. percent 4. principle 5. source 6. survey |
____ work ____ part of
100 ____ generated
idea used to guide one's actions |
Test results
confirmed the expectation that in terms of vocabulary knowledge, the learners
were indeed a very diverse group. Although the group means in Table 3 suggest
that students could recognize the meanings of 80% of the tested words at the
2000, 3000 and Academic levels, the standard deviations reveal that individuals
varied considerably. Some of the French speaking students scored high on the
Academic list (which contains many words of Latin origin) but low on the 2000
list (which contains many words of Germanic origin). Many of the Asian students
(mostly Chinese speakers) scored high on the test of the 2000 list but fared less
well on other lists.
Table 3
Pretest means on
the Vocabulary Levels Test by section; maximum score = 30
|
Pretest/30 (n=28) |
2000 M SD |
25.27 4.46 |
3000 M SD |
24.61 3.96 |
5000 M SD |
20.86 4.84 |
10,000 M SD |
9.68 5.21 |
Academic M SD |
24.77 3.94 |
These outcomes
confirmed our intuitions about the need for an individualized course designed
to meet highly diverse needs. Furthermore, it was clear that the students had
plenty of work to do in the Academic/University Word List zone. Few students
had full mastery of words at this level, and given its importance for academic
reading success, it seemed likely that all would benefit from intensive study
of these words. To implement this goal, we divided the 800 words of the UWL
into twelve 65-word lists for week-by-week studying and testing. So in addition
to reading and summarizing two readings each week and submitting Word Bank
entries, students prepared for a UWL quiz. About 30 minutes of each of the
twice-weekly 90-minute class periods were spent either on UWL learning
activities or testing. An example of a weekly quiz appears in Appendix 1.
Raise awareness
of proven word learning strategies
So far we have
discussed the vocabulary learning materials on offer (the Word Bank entries and
the UWL), ways of delivering it (class and website activities) and an
evaluation component (the UWL quizzes). But as O'Dell (1997) and others point
out, training students how they can learn most effectively is a key aspect of
any language course. Our examination of the vocabulary learning research
identified five main strategies for successful retention of form-meaning
associations. These are: keyword mnemonics (Brown & Perry, 199?), word-part
analysis (Sokmen, 1997), elaborative sentences (Brown & Perry, 1991; Ellis
1997), dictionary use (Hulstijn, Greidanus & Hollander, 1996) and
concordancing (Cobb 1997). We set the goal of familiarizing students with each
of these in class activities and, where possible, on the website.
In practice, it
turned out that some of the strategies were limited in their applicability. For
instance, the much acclaimed keyword imaging technique can only be applied if
an English word to be learned sounds like an L1 word and represents a concept
that can be pictured. Thus, one student was able to draw a picture of a
disgusted teacher throwing failed papers into the air to remember the English
word flunk. Since flunk sounds like the French word flanquer
(throw, fling) the vivid papers-in-the-air image creates a strong link to the
new word and its meaning. But it is clear that many words, especially abstract
ones, do not lend themselves to this treatment.
Two strategies
that could be applied to any new word were consistently supported in class
activities throughout the course. These were dictionary use and concordancing.
Support activities for dictionary use included exercises in identifying correct
definitions of words that have different senses in different contexts, and
comparing dictionaries designed for native speakers to those designed for
learners. Students were also shown how to access an on-line dictionary via the
Lexical Tutor button in the first column of the home page (see Figure 1).
The Lexical Tutor
button also offered learners an easy-to-use on-line concordancing tool
(developed by Chris Greaves of Hong Kong Polytechnic University). A
concordancer searches a large body of text to find every occurrence of a
particular word or phrase and displays these in a format that allows the user
to see the many different instances of the word in use. A concordance for the
word abandon consisting of 13 instances of the word in use is shown in
Figure 4. In principle, a concordance should be a powerful resource for
learning. Because the learner can examine a number of sentences containing the
new word, chances are that he or she will meet at least one that is easy to
understand. If the learner engages in solving the puzzle (i.e. guessing the
word's meaning), the concordance offers the opportunity to test a solution in
other sentences. Research by Cobb (1997; 1999) has confirmed the usefulness of
learning by concordancing. He found that learners who examined concordances
were more able to transfer new word knowledge to novel contexts than learners
who studied definitions. In the experimental course described in this paper,
students were shown on the first day how to use the concordancing tool and then
again at several later points. In addition, classroom concordancing activities
on paper were designed to raise student awareness of this strategy.
Figure 4
Concordance lines
for the word abandon
Challenge
learners to study hundreds of new words
Researchers
differ on the number of words language learners need to know to readily
comprehend textbooks used in university content courses. Research by Laufer
(1989, 1992) points to a minimum receptive vocabulary size of 3000 high
frequency word families. Work by Hazenbrug and Hulstijn (1996) suggests that
the figure may in fact be higher than this but the main message of these
studies is clear: the university-bound learner needs to know thousands of
words. For many learners, this means acquiring hundreds if not thousands on
fairly short order - in a semester or two of ESL study, if possible. Thus there
are compelling reasons to make acquiring knowledge of hundreds of new words an
explicit course goal, even if it means encouraging learners to resort to
studying lists. Rote memorization tasks
are out of fashion in language teaching, but Nation (1982) suggests that
currently popular methodologies may be neglecting a powerful learning
technique. He points to memory experiments where participants have been found
able to learn (and retain) as many as 50 new word and translation-equivalent
pairs an hour. Admittedly , this kind of memory work cannot be expected to
result in full knowledge such that a learner understands all the senses of new
words or is able to use them correctly in elegant original sentences. But we
reasoned that some initial engagement - however incomplete - with over a
hundred words each week was potentially more useful to university-bound
learners than intensive study of the dozen or so items that is more typical of
ESL courses.
Unlike the simple
word/translation pairs of used in the memory experiments, the on-line lists
available for study in our experimental course were richly informative. In
addition to offering the definition of a word and its part of speech, each Word
Bank entry provided an example of the word in use. Since these sentence
contexts generally came from material students had read, we assumed that many
entries would also provide memory links to class discussions of newspaper
articles, summary writing, and other activities. The on-line concordancing tool
meant that students could also study UWL items in a wide variety of sentence
contexts. To motivate students to study large numbers of words, we included two
exams in the plan for the course, a midterm and a final. For each of these,
students were expected to study 400 UWL items, 200 items from the newspaper
Word Bank, and 50 Specialist Word Bank items in their particular subject area.
These class tests focused narrowly on receptive word knowledge by presenting
students with context sentences taken directly from the Word Bank and requiring
them to identify the missing target items.
Research questions
Our investigation
of the experimental course focuses on two key issues: the usefulness of the
on-line resources, and the amount of new vocabulary knowledge gained by the
learners who used them. One way of examining the usefulness of the learning materials
is to consider their quality. Indeed the claim that learning vocabulary with a
collaborative on-line database is effective rests on showing that students were
indeed generating accurate and useful materials for their own learning. We were
also interested to see whether the quality of the entries changed as students
gained experience in working with dictionaries and selecting examples during
the 13-week course. Thus the first research questions we consider are as
follows:
1. What was the quality of student-produced on-line course
material (the Word Bank entries), and did entries improve over time?
We have argued
that an important advantage of a collaborative on-line project is its potential
to offer instruction tailored to individual needs. Since the pretesting had
shown that needs were indeed highly diverse, we were interested in seeing
whether different kinds of learners were using the resource in different ways.
Two very distinct constituencies in the group were learners of Asian and Romance language backgrounds. Romance
language speakers are able to exploit cognate knowledge for clues to the
meanings of the many English words of Latin and Greek origin, a strategy that
is not available to Asian language speakers. Thus, as Laufer (1997) points out,
words of Latin origin like perspective or anticipate may look
opaque to one learner but totally transparent to another. Exploring how these
two groups of learners used the on-line database seemed likely to be a useful
initial indicator of how well the on-line resources served the needs of different types of learners. This prompted
the following research question:
2. Did students of Asian and Romance language background enter
different types of words?
The remaining
questions address the important issues of amounts of new word knowledge gained
in the experimental course and factors that might explain growth results
3. Did learners increase their vocabulary knowledge?
4. Which strategies (e.g. dictionary use) were associated with
learning gains?
Participants
The 33 students
who registered for the experimental vocabulary course at Concordia University
(Montreal) represented a variety of first language backgrounds. About two
thirds of the group were speakers of Asian languages (Chinese and Vietnamese) and about one third had Romance language
background (Quebec French, Spanish or Portuguese). There was also an Arabic
speaker and a Farsi speaker in the group. All had been assessed as having
minimal or inadequate proficiency for university studies on a placement test
administered by the institution. There was a range of abilities in the group
but they can be generally termed intermediate-level learners. Most had been
admitted to the university on condition that they take courses to improve their
English.
Results
Word Bank entries
- the quality question
We used a ratings
procedure to investigate the quality of Word Bank entries (research question
1). To evaluate students' example
sentences, we began by selecting at random 40 sentences entered during the second
week of the course. Forty more sentences entered during the eleventh week were
also selected so that early and late entries could be compared. Next, following
a method devised by Beck, McKeown and McCaslin (1983), we deleted the target
words and asked a native speaker of English to draw on information in the
sentences to supply the missing items. The sentences were then evaluated using
the following scheme. If the rater's guess matched or nearly matched the word
in the original sentence, the sentence was awarded a score of 4. If a guess
showed general similarity to the missing word, the context was considered to be
supportive and was awarded a 3. An example of such a sentence appears in Table
4 where we see that the rater supplied anticipating instead of the original term yearning in the example sentence
"I was ___ this trip". Sentences prompting guesses that bore little
resemblance to the target words were considered neutral and were awarded a
score of 2. Misleading contexts scored 1 point. See Table 4 for examples.
Table 4
Rating scheme for
assessing quality of context entries
Student data
base entry |
Informant's
guess |
Rating |
The theater has
a seating capacity of 800. |
The theater has
a seating capacity of 800. |
4 exact |
Preminger cropped
Jean's hair. |
Preminger cut
Jean's hair |
4 near exact |
I was yearning
this trip. |
I was anticipating
this trip. |
3 supportive |
He commit
himself in writing this book |
He excelled
himself in writing this book |
2 neutral |
Her religions-minded
parents had met at a science convention. |
Her religions-shunning
parents had met at a science convention. |
1 misleading |
To rate the
quality of definitions entered in the Word Bank, we selected 40 definitions at
random from weeks 2 and 11 of the course. Again, we used a 4-point rating
scheme. Definitions that were simply and clearly worded and matched the sense
intended in example sentences were awarded the full mark of 4. Definitions that
were accurate but contained difficult language were awarded a 3. The wording
problem is evident in the case of chutney, where the definition
"pungent condiment made of vinegar and fruits" is clearly accurate
but of doubtful usefulness because of the potential difficulty of the words pungent
and condiment. Uninformative definitions such as the circular one for mythical
shown in Table 5 were rated 2 points while definitions that did not match the
sense of the example were awarded 1 point.
Table 5
Rating scheme for
assessing quality of definition entries
Word |
Student data
base entry |
Rating |
She mourned
for her dead son. |
to have or show
great sorrow, usually for a person who has died |
4 accurate, easy to
understand |
I enjoy chutney
with my turkey. |
pungent
condiment made of vinegar and fruits |
3 accurate, hard to
understand |
I was yearning
this trip. |
I was anticipating
this trip. |
3 supportive |
Arthur and
Mordred are mythical persons |
of or existing
in myth |
2 circular or too
long |
You'd think
Alberta would be bristling with warnings to Ottawa. |
thick strong
animal hair used to make brushes. |
1 inappropriate
sense |
Mean scores
indicated that the overall quality of context sentences was fairly high (Table
x). The mean rating for early contexts amounted to 2.7 while the mean for later
contexts was 3.0. That is, late entries earned the score assigned to
"supportive" sentences, and the early entries closely approached this
level. Thus we can conclude that in general, the student-generated material
offered useful context information about new words. These ratings results are
higher than the 2.5 mean ratings other studies using this methodology have
found for natural texts (Horst, 2000; Zahar, Cobb & Spada, in press), so it
is possible to conclude that the student entries succeeded in being more
informative than ordinary sentences would be. The higher mean rating for the
later data suggests that students improved the quality of their entries as the
course progressed. Although, a t-test for independent samples showed that the
gain was not statistically significant, it seems reasonable to assume that the
rising profile would continue with more time and practice.
Table 6
Quality-of-context
ratings (n = 40)
|
Week 1 |
Week 11 |
M |
2.70 |
3.00 |
SD |
1.02 |
1.04 |
Definitions also
appeared to be of a mainly high quality (Table 7); in fact, the definition
results are similar to the sentence findings. The mean ratings of around 3 (the
score awarded to accurate definitions with wording difficulties) at the both
the beginning and end of the course suggest that the definitions were generally
accurate throughout. Again, the data suggest that the quality of definitions
improved during the course. Though the difference was not found to be
statistically significant, it seems likely that definitions would continue to
improve over the longer term.
Table 7
Quality-of-definition ratings
|
Week 1 |
Week 11 |
M |
2.95 |
3.15 |
SD |
.93 |
1.08 |
In general, we
can conclude that both the example sentences and the definitions students
supplied for each other in the Word Bank project were of very satisfactory quality.
Interestingly, a few students complained about occasional spelling or grammar
errors they spotted in the entries, but none complained about the word
information on offer. Our analysis confirms that the information provided in
the entries tended to be useful and accurate.
However, some qualifications are in order: The standard deviations
suggest that quality was rather inconsistent, and the high but not perfect
average scores suggest that students may benefit from training in how to
produce clear definitions and supportive example sentences.
Word Bank entries
- the individual differences question
To investigate
whether students of different L1 backgrounds were using the on-line resources
to meet varying vocabulary needs (research question 2), we took a close look at
words entered by students in two distinct groups: Asian and Romance language
speakers. To compare the words that learners in the two groups looked up, we
prepared two corpora of 300 words each. The Asian corpus consisted of the 300 items
entered in the Focus Word Bank during the first three weeks of the course by
learners whose first language was Chinese or Vietnamese. The Romance corpus consisted of the 300
items entered by French, Spanish and Portuguese speakers. Each corpus was analyzed
using HyperVocabProfile (Cobb, 1998;
based on Nation, 1998), a computer program that groups English words
into frequency bands. That is, the program allowed us to see the extent to
which students in the two groups looked up common and less common words. Of
special interest were the number of look ups in the UWL band (which contains
many words of Greco-Latin origin). We hypothesized that the proportion of
lookups in this zone would be larger in the Asian group than in Romance group.
Figure 5
Distributions of
300 looked-up words in two L1-based groups (figures in percentages)
The results shown
in Figure 5 are striking. If we consider the high frequency categories (the 0
-1000 and 1000-2000 most frequent bands), we see that 12% (7 + 5) of Asian
look-ups were common English words. But this category accounts for a far
greater proportion of the Romance look ups; in fact, over a quarter (18 + 9 =
27%) of all the words looked up by Romance speakers were in this zone. A
possible explanation is the fact that the 0 -1000 and 1000-2000 bands contain a
high proportion of words of Anglo-Saxon origin, words which have no cognate
equivalents in Romance languages and are therefore more likely to be unfamiliar
to Romance speakers than Latin-based English words. The occurrence of common
words of Germanic origin like flew, storm and height on the
Romance list suggest that this was the case. The notion that learners in the
Romance group directed their attention to non-cognates is also confirmed by the
third column of data where we see that these learners looked up fewer of the
Greek and Latin based UWL items than the Asian learners, for whom these words
appear to be difficult. In summary, it
is clear that the two groups were looking up different types of words, and
there is reason to think that both groups were well served by a course designed
to address individual vocabulary needs.
Vocabulary
learning - The growth question
To determine how
much students had learned as a result of taking the course and participating in
the collaborative Word Bank project (research question 3), we measured
students' receptive vocabulary sizes at the beginning and end of the course by
administering updated versions of the Vocabulary Levels Test (Schmitt, 2000;
Schmitt & Schmitt, forthcoming). As discussed earlier, this instrument is
designed to assess receptive knowledge of words sampled from lists of the 2000,
3000, 5000 and 10,000 most common words of English and the Academic Word List
(a list similar to the UWL). Vocabulary learning gains were determined by
calculating the differences between learners' pre- and posttest scores.
Pre-post results
and gains are shown in Table 8. The maximum score possible in each section of
the test was 30. While the general picture is largely one of growth, it is also
evident that some of the changes are very small. Statistical analysis
(ANOVA and post hoc t-test) showed that
mean scores on the Academic Word List section differed significantly (t = 2.62;
p < .05). Although the gain of about two new words in this category may
appear rather minor, if we extrapolate this result to the entire word list, we
see that learners achieved a substantial amount of growth. The gain of 1.73
words in 30 represents a growth rate of 5.8%; when this figure is applied to
all 800 words on the UWL, we arrive at a gain figure of about 46 new words
(.058 x 800 = 46.13).
Table 8
Pre-and posttest
means: Vocabulary Levels Test (n = 28)
|
Pretest/30 |
Posttest/30 |
Gain |
3000 |
|
|
|
M |
24.61 |
24.86 |
.25 |
SD |
3.96 |
3.37 |
3.53 |
5000 |
|
|
|
M |
20.86 |
20.77 |
-.07 |
SD |
4.84 |
5.57 |
4.36 |
10,000 |
|
|
|
M |
9.68 |
9.77 |
.11 |
SD |
5.21 |
6.52 |
5.08 |
Academic |
|
|
|
M |
24.77 |
26.50 |
1.73 |
SD |
3.94 |
3.63 |
3.09 |
Clearly, the
learners acquired new receptive vocabulary knowledge as a result of studying in
the experimental course. As we have seen, increases in knowledge of items on
the Academic/University Word List accounted for most of the growth. Since these
subtechnical terms are important for university ESL learners to know, we can
conclude that the course achieved an important objective. But increased
knowledge of UWL items is hardly surprising given the amount of attention given
to the UWL in class. Every week students participated in activities to support
UWL word learning and studied for a weekly quiz; students studied these items
again for midterm and final tests.
This leaves
unanswered the question of why evidence of growth was so slight in non-UWL
zones - zones that the Word Bank activities were designed to address. One
probable explanation is that the Vocabulary Levels Test was not sensitive
enough to capture the incomplete but real knowledge that a learner might retain
from the experience of reading an on-line definition of a word and a single
illustrating example. Work by Horst (2000) has shown that the learning impact
of one or two encounters with a new word can be captured but that very
sensitive measures are required. Also, the sampling technique used to construct
the Vocabulary Levels Test is problematic for the assessment of low-frequency words.
For instance, a learner who acquired new knowledge of a word in the 5000-10,000
most frequent band through studying the Word Bank is highly unlikely to
encounter that word on a test that samples only 30 items of the 5000 words in
the band. Thus there is no reason to conclude that students did not profit from
the on-line collaborative activities;
it is highly probable that they did. Rather, the results point to the
importance of using sensitive measures to assess vocabulary learning.
Another explanation
for slight growth outside the UWL is that the vocabularies of specific academic
disciplines remain as yet undefined, so that it is not possible to target the
characterizing terms of economics, stage design, or any other discipline for
purposes of either teaching or testing. Our students may well have covered much
of the lexical territory of their chosen domains in their Specialist Groups
activities, but we have no way of measuring this other than to use the 10,000
word zone of the Levels Test.
Keys to success -
The strategies question
Although we
familiarized students with a variety of proven strategies for learning
vocabulary in the course, we limited our investigation to those that met two
criteria: 1) strategies that could be applied to any word (see the discussion
of keyword above for an instance of a limited strategy), and 2) strategies that students were
familiar with from the first day of the course onwards (i.e. there was ample
opportunity to use the strategy). Two traditional strategies (using a
monolingual or a bilingual dictionary), and two computerized strategies (using
an on-line dictionary and using a concordance) met these criteria.
We used a
questionnaire attached to the Vocabulary Levels posttest administered in the
final week of the course to explore the extent to which students made use of
the various strategies. The questionnaire asked students to rate their use of
each according to the following five-point scale:
1 = never
2 = once or twice
3 = fairly often
4 = very often
5 = almost always
Then, to
determine which strategy was most closely associated with learning gains, we
entered student ratings of the four strategies into a multiple-regression
analysis with pre-post Academic Word List gain scores as the dependent
variable.
Traditional
dictionary use was clearly more widespread in the group than use of the
computer dictionary and concordancing tools. Figure 6 shows the mean ratings of
about 3.5 for using bilingual dictionaries (e.g. English-Chinese) and
monolingual dictionaries (English-English); in other words, these resources
were both used often. Ratings for the non-traditional tools are lower; students
appeared to prefer using the on-line dictionary to concordancing.
Figure 6
Strategy use (n =
22)
The regression
analysis revealed that the strongest predictor of vocabulary learning outcomes
was monolingual dictionary use. However, the use of this strategy is negatively
associated with learning gains. The most reasonable interpretation of this
finding is that good learners who already knew many words on the UWL (and
therefore had little opportunity to register gains on the test) were consistent
users of English-English dictionaries. A more interesting finding appears in
the second line of Table X where we see that of the remaining predictors
concordances use is most strongly associated with vocabulary learning gains (r
= .38) albeit with a probability level that suggests some role for chance
effects. This finding suggests that even though average concordance use ranged
between the "never" and "almost" ratings in the group as a
whole, students who did use this feature were likely to experience vocabulary
gains.
Table 9
Summary of
regression analysis for variables predicting academic vocabulary gains (n = 22)
Strategy |
Correlation |
Probability |
Monolingual |
-.46 |
.03 |
Concordance |
.38 |
.08 |
Bilingual |
.14 |
.55 |
On-line |
.05 |
.82 |
Conclusion
We are convinced
that the collaborative database is a valuable tool for vocabulary acquisition
for learners who have moved beyond the elementary level. The technology is
clearly able to absorb the variety of lexical needs that characterize learning
at this level. Our students have shown they are willing to use the tools we
have developed, that they use these tools reasonably well, and that they learn
some words by using them. How many words, we can not say as yet, for reasons
mainly related to insensitive or non-existant vocabulary measures. Perhaps the
lack of suitable tests for an experiment such as ours is not surprising. Few
instructional designs in the past have attempted to instruct words in the
numbers we have targeted, so it is reasonable there might be few suitable ways
of measuring our results. The 5,000 and 10,000 level of the Leves Test is
clearly a blunt instrument - and yet that is where many of our students
acquisition needs lay. Tests that can measure fine degrees of knowedge simply,
and that target the vocabularies of specific domains, are urgently needed.
We are presently
feeding the findings of this experiemnt into a revamped course with an on-line
component, which we expect to run again soon. At the same time we want to
provide a fully independent Internet version of the course to cater to a
virtual clientele worldwide. In fact, our vocabulary learning tools were
inadvertently left on the Web when the course was over, and learners from
various corners of the world have already started using them and adapting them
to their own purposes.
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Appendix 1
UWL Quiz 8:
linguistics-outcome
Name:
..........................................
A. Write the number of the word next to its
definition (12 points):
1. magic
2. magnetic __ strange
3. moist __ wet, damp
4. odd __old, out of date, useless
5. obsolete
6. mature
1. margin
2. orbit __ reason to do
something
3. null __ circular movement
4. navy __ empty space at the
edge
5. motive
6. momentum
1. mobile
2. maternal __ choosing neither side
3. nuclear __ showing clear thinking
4. neutral __ able to move
5. normal
6. logical
1. litigation
2. location __ movement, travel
3. migration __ duty, responsibility
4. notation __ way of writing
5. orientation
6. obligation
B. Cloze. Choose from the words below to complete the
passage (8 points):
outcome occur magnitude
monarch nutrients occupy
maintain luxuries obvious
The Man Who Broke
the Bank
Barings Bank used to be one of the
oldest and most respected British investment banks. It had branches all over the world and many famous customers
including the British (1)........................ , Queen Elizabeth. But
in February 1996 there was bad
news at the Singapore branch. In fact,
it looked like Barings was in serious trouble.
At first the (2)...................................... of the problem
was not clear. Nobody knew for sure how
many bad investments had been made or how much money was involved, but it soon
became (3)...................... that the losses were over $1.3 billion
dollars, and so large that the 232-year-old bank was forced to close with great
losses to its customers.
How could such a disaster
(4)...................? How was it
possible for such a respected and trusted institution to have made such
mistakes? The top management of Barings
promised a thorough investigation and they soon found out who was responsible:
a young trader called Nick Leeson.
Here is his story: Leeson had done very well at Barings and had
received huge bonuses and rapid promotions for his excellent performance. He came from a very ordinary working-class
English family, and he and his wife enjoyed their new life and the
(5)...................................... that came with wealth and success in
Singapore. They ate at the finest
restaurants and played tennis at the best club. Leeson was determined to
(6)...................................... his record of success at the bank.
His method was simple. He made very large, very risky investments
for Barings in the hopes that there would be enormous profits. If there were losses, he entered them in a
secret account, and hoped to pay off the growing debt with profits from the
next investment success. But the debts
increased so fast that Leeson lost control.
By the time the fraud was discovered, it was too late to save the bank.
Barings Bank was forced to close,
but what was the (7)..................................... for Nick Leeson? He was given a prison sentence of just six
and a half years for his crime, and he did not seem to be very sorry about what
he did. How did he
(8...................................... his time in prison? He spent most of his time writing. Recently, he published a book called Rogue
Trader--How I Brought Down Barings Bank and Shook the Financial World. Buy it and read it if you like, but
remember: Your purchase is helping to
pay the legal bills of a thief.
--from the Toronto Globe & Mail,
March 1996
Appendix 2
Tests were placed
online for students to check immediately after completion, using an authoring
script developed by Chris Greaves.