Post on 30-Apr-2020
Why teach general academic vocabulary?
A presentation of research
and classroom practices
Plan
09.15 – 10.00 – What does the research say?
10.00 – 10.15 – Break
10.15 – 11.00 – Practicing what I preach
Aims for the session
• Present the use of Corpus Lingistics for
research and classroom practices
• Present a discussion of the term general
academic vocabulary
• Provide some theoretical insight into the
process of learning words
• Provide classroom examples of explicit
vocabulary teaching / vocabulary assessment
using computer programs
Corpus Linguistics (CL)
• Use of large corpora to assess vocabulary use
and patterns
• “Corpus linguistics …[has] a large role to play in
identifying the linguistic constructions of most
relevance to particular learners”
(N. C. Ellis, 2012b, p. 204).
• Computer technology and internet access have
taken the study of corpus linguistics to a new
level (McCarthy, 2012).
• Help to set vocabulary learning goals (Nation, 2013)
Corpora – BNC/COCA
• The British National Corpus (BNC) and the
Corpus of Contemporary American English
(COCA), are a collection of oral and written
texts found in different authentic sources.
• COCA - 450 million words that are “equally divided
among spoken, fiction, popular magazines,
newspapers, and academic texts” (Davies, 2012).
• The BNC “is a 100 million word collection of samples
of written and spoken language … a wide cross-
section of British English, …from the late twentieth
century” (Consortium, 2007).
What is a word?
• Tokens refer to every word form found in a written or oral
text. If the same word form, i.e. economy occurs several
times within a text each form is counted as a separate
entity.
• The term types refers to a gathering of tokens so that if
one word is written several times in a text these are
counted in one group and referred to as one word type.
(Nation, 2013). If the word economy is used seven times
within one text then this will form the word type economy
(7). Likewise, if the word economies (5) appears five
times in the same text, this will be counted as one word
type group as well.
Word Families
• Word families represent “a headword, its
inflected forms, and …closely related derived
forms” (Nation, 2013, p. 11).
• Nation argues that affixes, such as, -ly, -ness,
and un- “greatly reduce the learning burden of
derived forms containing known base forms, but
he also acknowledges that not all learners will
necessarily know all of the derived forms in a
word family.
• The learning burden of derivatives can be
discussed.
Academic Word List (AWL) - Examples
Headwords sublist
acknowledge 6
acquire 2
adequate 4
adjacent 10
compensate 3
compile 10
complement 8
complex 2
economy 1
edit 6
element 2
Word Familyeconomy
economic
economical
economically
economics
economies
economist
economists
uneconomical
Source:
http://www.victoria.ac.nz/lals/resources/
academicwordlist
Defining general academic vocabulary
• academic vs technical
• academic vocabulary “common in different kinds of
academic texts” (Nation, 2013, p. 19).
• general vs discipline-specific (Heibert & Lubliner, 2008; Nagy & Townsend, 2012)
• in relation to each subject it applies to
(Hyland, 2011; Hyland & Tse, 2007)
Coxhead’s Academic Word List (AWL)
• She compared written academic texts used in universities, from
a wide range of subjects, and then compiled a corpus of 3.5
million words from 414 texts, covering the four subject
disciplines: arts, commerce, law and science.
• Each subject discipline was divided into seven subject areas,
such as education, accounting, and biology.
• Word families included on the list had to appear at least 100
times in the corpus, in at least 15 of the subject areas and over
10 times in each of the subject disciplines (Coxhead, 2000).
• Between 8% – 10% of any given text use for university studies
are found on the AWL. AWL use authentic English newspaper
articles is around 5% (Nation, 2013).
Discussion Questions
• How is vocabulary acquired?
• How do pupils acquire vocabulary in a
classroom situation?
• What do you suggest as a means for your
students to widen their vocabulary?
• What vocabulary goals should teachers have
for their students?
Vocabulary Acquisition
• Implicit learning
• “learning that takes place without either intentionality
or awareness” (R. Ellis, 2008, p. 7)
• Explicit learning
• learning as “a conscious process and is likely to be
intentional” (R. Ellis, 2008, p. 7)
• Productive vs receptive word knowledge
• Vocabulary acquisition through reading
• Form-meaning word knowledge
Reading Comprehension
• After extensive research, there is a general consensus
among vocabulary researchers that for unassisted
reading L2 learners should understand 98% of the
words used in a text.
• A more conservative estimate of 95% word coverage
should be seen as an absolute minimum (Laufer, 2010;
Nation, 2013; Schmitt and Grabe, 2011).
• Expressed in more practical terms this means that
learners should not be exposed to more than one
unfamiliar word per 2-5 lines of written text, if they are to
comprehend what they have read (Nation, 2013).
Reading Comprehension
Native American communities and individuals have been
working their way into economic … for quite some time now.
While some of this has been due to the … of government
programs set up to … native businesspeople, most of it has
been an … of native … and …. Native Americans are in
charge of some of the largest resource development
companies, some of the largest restaurant chains, some of the
largest casinos, and some very popular …. and financing
companies all over the country. While these natives represent a
wide … of economic interests, one thing they share is the way
their … has influenced the way they handle their business
operations.
Reading Comprehension
Native American communities and individuals have been
working their way into economic prosperity for quite some
time now. While some of this has been due to the impacts of
government programs set up to assist native businesspeople,
most of it has been an outgrowth of native ingenuity and
innovation. Native Americans are in charge of some of the
largest resource development companies, some of the
largest restaurant chains, some of the largest casinos, and some
very popular capital investment firms and financing
companies all over the country. While these natives represent a
wide range of economic interests, one thing they share is the
way their heritage has influenced the way they handle their
business operations.
Zipf’s Law
Zipf’s Law
• “the most frequent word [in a text occurs]
approximately twice as often as the second
most frequent word, which occurs twice as often
as the fourth most frequent word, etc.” (N. C. Ellis, 2015, p. 262).
• Implications
• the implicit acquisition of less frequent English
vocabulary words through unassisted reading
requires a lot of reading
• “it is not unusual to find lots of words occurring once
in course books written for learners of English” (Nation, 2013, p. 33).
Can we expect our pupils to learn AWL words implicitly?
• Some researchers question this
• Krashen – Input Hypothesis / Cobb (2007)
• Cobb (2007) - in-text frequency of word families with
BNC frequency levels at the first 3000 levels.
• He compiled a 517,000 token corpus of fiction, press
writing and academic writing taken from the Brown
corpus
• Findings: only half of the 3,000 level words were
repeated six or more times (Cobb, 2007).
• Nation (2013)
Analysis of AWL vocabulary in textbook texts
• A majority of the Academic Word List (AWL) word families were
used only once, even across three and four topic-related texts
(Skjelde, 2015).
• These findings support previous research (Cobb, 2007; Matsuoka
and Hirsh, 2010).
Narrow reading of 3-4 texts
related to Global English and
Indigenous Peoples.
Textbooks: Targets (2015),
Access to English (2013), Stunt
(2009)
Narrow Reading
• Reading several topic related texts
(Kang, 2015)
• Can lessen the lexical load
• Can provide possibilities for students to meet
vocabulary in different contexts (increase frequency
of exposure)
• Newpaper articles –
• may provide higher levels of AWL in context
Why explicit teaching of general academic vocabulary?
Four main reasons:
• AWL vocabulary is
• common to a wide range of academic texts, and
not so common to non-academic texts
• accounts for a substantial number of words in
academic texts
• generally not known as well as technical
vocabulary
• the kind of specialized vocabulary that an English
teacher can usefully help learners with (Nation,
2013, pp. 291-293).
Nation’s Four Strands – Course development
• Learning a L2 from comprehensible meaning-
focused input
• main focus of attention is on the information in what
students are listening to or reading.
• Learning a L2 from meaning-focused output
• Main focus of attention is on the information they are
trying to convey
Nation’s Four Strands – Course development
• Language-focused learning
• Usefully focused deliberate teaching and learning of
language items
• Debated part of L2 learning
• Fluency development
• Learners do not work with new language items, but
become more and more fluent in using items they
know already
• If fluency is not a part of a L2 course, learning done
in the other three strands will not be available for
normal use
(Nation, 2013, p. 2-3)
Expected Reading Comprehesion – Textbook texts
Flash Cards and Glossary Tests
Theory and Research
• The Involvement Load Hypothesis
(Laufer in Nation, 2013, pp 98-99)
• Technique Feature Analysis - see handout
(Nation, 2013, pp 98-101)
• Noticing and decontextualization
(Nation, 2013, p. 103)
Flash Cards and Glossary Tests
• Vocabulary profile of texts (pre-reading)
• Methods for learning words explicitly
• Flash cards/quizlet
• Self designed glossary testing
• Individual Golssary Tests
• See handout
Lexical Profiling
• Cobb’s Vocab Compleat
• Provide students with a simplified list of vocabulary at
the 3000 level and above
• Ask them to chose 10 words to learn before
they read the text.
• Provide time in class to learn the words and
make a glossary test
Individual Glossary Test
• Pick 10 words to learn from one text
• Use quizlet.com or paper flash cards to help learn the words
• Glossary test next class (Pass at 95% correct)
• Read the text (again or for the first time)
Vocabulary Assessment
New Vocabulary Levels Test (NVLT) –
http://www.lextutor.ca/tests/levels/recognition/nvl
t/test.pdf
Vocabulary Size Test (VST) – vocabualrysize.com
PHRASAL VOCABULARY SIZE TEST
http://www.lextutor.ca/tests/levels/recognition/phra
sal/
References
Cobb, T. (2007). Computing the Vocabulary Demands of L2 Reading. Language Learning & Technology, 11(3), 38-63.
Retrieved from http://llt.msu.cdu/vol11num3/cobb/
Cobb, T. (2010). Learning about language and learners from computer programs. Reading in a Foreign Language,
22(1), 181-200. Retrieved from http://nflrc.hawaii.edu/rfl
Cobb, T. (). Web Vocabprofile. Retrieved from http://www.lextutor.ca/vp/
Cobb, T. (n.d.-a). The original idea behind this website Why & how to use frequency lists to learn words. Retrieved
from http://www.lextutor.ca/research/rationale.htm
Cobb, T. (n.d.-b). Web VP Classic v.4 Retrieved from http://www.lextutor.ca/vp/eng/
Coxhead, A. (2000). A New Academic Word List. TESOL Quarterly, 34(2), 213-238.
Ellis, N. C. (2012a). Formulaic Language and Second Language Acquisition: Zipf and the Phrasal Teddy Bear. Annual
Review of Applied Linguistics, 32, 17-44.
Ellis, N. C. (2012b). Frequency-based Accounts of Second Language Aacquisition. In S. M. Gass & A. Mackey (Eds.),
The Routledge Handbook of Second Language Acquisition (pp. 193-210). New York, NY: Routledge.
Ellis, N. C. (2015). Frequency Effects. In P. Robinson (Ed.), The Routledge Encyclopedia of Second Language
Acquisition (pp. vi-xxiv, 1-755). New York: Routledge.
Heibert, E. H., & Lubliner, S. (2008). The Nature, Learning, and Instruction of General Academic Vocabulary. In A. E.
Farstrup & S. J. Samuels (Eds.), What Research Has To Say about Vocabulary Instruction (pp. 106-129). Newark,
DE: International Reading Association.
Kang, E. Y. E. (2015). Promoting L2 Vocabulary Learning through Narrow Reading. RELC journal, 46(2), 165-179.
Larsen-Freeman, Diane (2001) Grammar. In Carter, R. & Nunan, D. (eds.) Teaching English to Speakers of Other
Languages. Cambridge: Cambridge University Press. (s 34-41).
Laufer, B. (2010). Lexical threshold revisited: Lexical text coverage, learners' vocabulary size and reading
comprehension. Reading in a Foreign Language, 22(1), 15-30.
References
Nation, I. S. P. (2006). How Large a Vocabulary Is Needed For Reading and Listening? The Canadian Modern
Language Review, 63(1), 59-82.
Nation, I. S. P. (2012). The BNC/COCA word families lists. Retrieved from
http://www.victoria.ac.nz/lals/about/staff/publications/paul-nation/Information-on-the-BNC_COCA-word-family-
lists.pdf:
Nation, I. S. P. (2013). Learning Vocabulary in Another Language (second ed.). Cambridge: University Printing House.
Nation, I. S. P., & Beglar, D. (2007). A vocabulary size test. The Language Teacher, 31(7), 9-13. Retrieved from
http://www.victoria.ac.nz/lals/about/staff/publications/paul-nation/Vocabulary-Size-Test-information-and-
specifications.pdf
Nagy, W., & Townsend, D. (2012). Words as Tools: Learning Academic Vocabulary as Language Acquisition. Reading
Research Quarterly, 47(1), 91-108.
Schmitt, D., & Schmitt, N. (2012). Plenary Speech A reassessment of frequency and vocabulary size in L2 vocabulary
teaching. Cambridge Journal, 1-20. Retrieved from http://journals.cambridge.org
Schmitt, N., Cobb, T., Horst, M., & Schmitt, D. (2015). How much vocabulary is needed to use English? Replication of
vanZeeland & Schmitt (2012), Nation (2006) and Cobb (2007). Language Teaching, 1-15. Retrieved from
http://journals.cambridge.org/abstract_S0261444815000075
Schmitt, N., Jiang, X., & Grabe, W. (2011). The Percentage of Words Known in a Text and Reading Comprehension.
The Modern Language Journal, 95(1), 26-43. doi:10.2307/41262309
Skjelde, K. (2015). Academic Vocabulary: Unleashed potential? A corpus study of English course materials for
advanced Norwegian learners of English (Master’s thesis) University of Bergen, Bergen. Available online at
https://bora.uib.no/bitstream/handle/1956/10981/141257421.pdf?sequence=1&isAllowed=y