Guy Aston

guy@sslmit.unibo.it

Using BNC-xml in language teaching and learning

Where do corpora fit in? As a teaching aid in the classroom

Replace teacher intuition Place native/non-native speaking teachers on equal terms

As a self-access learning aid Find out about the language/the culture for yourself (data-

driven learning)• Hypothesis testing• Hypothesis generation

Contradict your teacher

What the corpus can tell you Sinclair’s (2003) regularity types / Hoey’s (2005) Lexical

priming Collocations - associations with other word forms/lemmas:

immemorial with time Colligations - associations with

• grammatical categories: than with comparative adjectives; • structural positions: text-initial sixty

Semantic preferences - associations with semantic classes: ago with time nouns

Semantic prosodies - evaluative classes: a load of (rubbish)/loads of (money)

Contextual associations • text-type• register

Learners aren’t linguists The aim is NOT to provide

a complete description of all the data maximum generalisations/abstractions

The aim IS to take away usable partial generalisations memorable experiences enthusiasm

Using BNC-xml with Xaira can provide these? Examples focussing on Xaira improvements From my experience with advanced learners of English

Example 1: Grammer To + gerund

used to -ing, accustomed to -ing, look forward to -ing, object to -ing

Xaira AddKey Query allows you to look for any word with a specified POS value!

To + VVG|VBG|VDG|VHG

The AddKey query (any VVG)Or VBG, or VDG, or VHG (multiple selections)…

QueryBuilder: To NEXT VVGOr VBG, or VDG, or VHG …

Too many solutions

Random 30/14227 (sort 1L) look forward to / when it comes to / devoted to / well on the way to

To + V.G is written formal …

Collocates of to + V.G (1,0): by frequency

Learners should take something away which is

relevant memorable typical not over-general

E.g. The French are the meanest when it comes to sending

Christmas cards When it comes to buying houses, the British are keenest of

all I’m not exactly the archetypal Mills & Boon dark stranger

when it comes to courting girls

Example 2: the verb tend Missing from textbooks (Carter & McCarthy

1995)

Frequent (>100/M), widely distributed

How is it used?

Too many solutions? Try Collocation/Analysis

VERB collocates (0,3): by frequency

TEND to concentrate (30/96)

Colligates (0,2: lemmata)

Just what

nouns?

SUBST collocates (lemmata: 0,2)

Tend * SUBST collocates (25/352)

An odd list of nouns You can tend:

gardens cattle/sheep/flocks fires

Things can tend: to unity/infinity to sort of VERB

Isn’t this all in the dictionary? Perhaps, but the corpus gives

More frequency/distribution information More examples Access to wider contexts Practice in working things out for yourself Casual encounters – did you know tend to unity?

The corpus calls for an open mind – you regularly find the answer to a different question from the one you started off with … but you learn a lot in the process

Example 3: Hell for leather How, when and where an idiom is used

Frequency? Distribution? Variants? Grammatical roles? Semantic roles? Register/text-type association?

Hell for leather – with variants?

Invariant, adverbial (+ 1 adjectival)Semantic preference: go/drive/ride/headRare: n = 10All written

More hell Word Query hell

hell-for-leather (5)

• hell (random 100)• Sort left 2, right 2• like hell

Like hell

Like hell What do you do like hell? (152)

• Combat/suffer/flee Fight / hurt / run • Denials/Contradictions: Like hell + pronoun + auxiliary

A much more interesting exercise on auxiliary verb use than generally proposed in textbooks

Example 4: Decide how (not) to start your next novel The most frequent opening word is …?

Formulating the query

Class: fiction and verse; No regioncatRef: Beginning sample|Whole textp (first paragraph)

The compleat query

The … + past VBD/VDD/VHD/VVD

The air hostess smiled. The bodies were discovered at eight forty-five on the morning of

Wednesday 18 September by Miss Emily Wharton, a 65-year-old spinster

The call had come at 6.12 precisely. The castaways were lying together in the bilges of a cockboat when … The cat had finished with its night hunt, and came padding silently

back to its home territory. The dawn was breaking as the cars rolled off the ferry at North Wall; … The day was almost over before the young men made their move. The gypsies arrived on Dartmoor early that year. The house stood in a leafy street in the southern suburbs. The injuries in the aftermath of the bomb explosion looked horrific. The kitchen was full of the smells of baking. The ladies of Tollemarche, Alberta, were always wonderfully clever at

disposing of their menfolk; … The lecture ended on a humorous note and, as the laughter and

applause died away, Sophie Ferguson ..

and the runner up … It was It was a pretty churchyard. It was dark by the time he reached his destination. It was dark. It was dawn on the northern frontier of France; a border marked

only by a shallow stream which ran between the stunted trunks of …

It was first love — there had been no time for earlier romance because Nicandra was only eight on April 8th 1904.

It was half-past midnight, and some time before sunrise Ebenezer Judge knew that he was going to die.

It was like grabbing a tiger by the tail! It was the first dead body he had ever seen. It was the pivotal teaching of Pluthero Quexos, the most

celebrated dramatist of the Second Dominion, that in any fiction, no matter ...

It was the very first day of Mildred Hubble's second year at Miss Cackle's Academy for Witches.

And the learner task Choose one opening, read the whole first

chapter, and tell us what you think of it next time.