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Learning
and Teaching through Context - A Data-driven Approach
by Ramesh Krishnamurthy
COBUILD
(Collins Dictionaries and the University of Birmingham)
This
article is based on a talk given at the TESOL Spain 24th National
Convention, "A Quest for Teacher Development", Seville,
30th March-April 1st 2001, and was first published in theTESOL
Spain Newsletter, Volume 24, Autumn/Winter 2001, ISSN 1575-8044.
It is reproduced here with their kind permission.
Abstract
A
word may have many potential meanings, but its actual meaning
in any authentic written or spoken text is determined by its
context: its collocations, structural patterns, and pragmatic
functions. Large language corpora offer access to words in
a wide range of natural contexts, which can improve and enrich
both language learning and teaching.
Introduction
The
conference theme is teacher development. So how do teachers
develop? Mainly by experimentation and experience. But teachers
can also develop by adopting more active strategies, acquiring
new knowledge through reading and by conducting their own
research, and acquiring new skills by observing colleagues,
by attending courses, and of course by thinking and reflecting
on their own experiences. Above all, teacher development is
a question of attitude. Good teachers (and good students,
for that matter) need to be constantly open to new ideas and
new opportunities, for example through technological developments.
This paper will focus on one of these technological developments
in particular, and show how teachers can use the newly available
resources and techniques to supplement and enhance their current
teaching practices.
"The
single most important task facing language learners is acquiring
a sufficiently large vocabulary." (Lewis, 2000:8). For
centuries, one major resource for this task has been dictionaries.
Dictionaries depend on a simple linguistic fact: words can
be easily listed in alphabetical order. Meanings arise when
words are used in context, but meanings are too complex to
list, so lexicographers listed words and pretended that meanings
were associated with them, as a form of shorthand. However,
at some point we seem to have forgotten that this is just
a conventionalised pretence, and have come to believe
that meaning actually is contained in individual words.
Some
people talk more accurately about words having potential
meanings. Their actual meaning in any authentic written
or spoken text is determined by their context: their collocations,
structural patterns, and pragmatic functions. If meanings
arise from words in contexts, learners will need contexts
in order to learn the language. Where can we get these contexts
from? We can make them up (as most lexicographers, linguists
and teachers did in the past) but, because our memories and
intuitions are often inaccurate and incomplete, we usually
make up contexts that are inaccurate and incomplete. As John
Sinclair has said:
"language users cannot accurately report language usage,
even their own" (Sinclair, 1987), and "There are
many facts about language that cannot be discovered by just
thinking about it, or even reading and listening very intently"
(Sinclair, 1995).
Language
corpora are collections of authentic written and spoken texts,
created in genuine communicative situations, and provide us
with many real contexts. Normally, students encounter a particular
word, phrase, or grammatical structure on one day, then have
to wait for a long period before they come across it again.
Corpora allow students to see many examples of the word, phrase,
or grammatical structure at the same time. They also notice
patterns of usage and work out rules for themselves, and therefore
remember them better.
Many
language corpora have become available to the public in the
past few years, e.g. for English there are the British National
Corpus, and the COBUILD Bank of English corpus. It is also
fairly easy to collect smaller corpora oneself, from texts
available on the World Wide Web. Students who write their
essays on computer can collect a corpus of their own work.
Teachers can collect their students' work to form a class
corpus. Students can compare their own output with native-speaker
texts in the public corpora, improve their own writing, and
increase their language awareness.
Public
corpora usually provide their own software tools, but a variety
of programs are also available separately for use with user-collected
data. This paper refers only to English, but corpora are now
available for many other languages. Some websites with information
about corpora, software, and corpus analysis techniques can
be found at the end of this paper.
The
data shown below is taken from the Bank of English corpus,
but the main facts and figures for most words will be similar
whichever large corpus you use. Most corpus software will
provide a similar set of standard facilities. Each of these
can be used to focus on different aspects of language learning
and teaching.
Only two such facilities will be covered here: frequency
and concordance, but there are many other facilities
such as various collocation tools, and grammatical part-of-speech
tags.
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