Criterial Features and the
CASP Model of SLA
John A. Hawkins
Department of Linguistics, UC Davis
From 2005-2011 I co-directed a research program on second
language learning at Cambridge University (the “English Profile
Programme”) with three components:
(a) Cambridge Learner Corpus [CLC]: 40+ million words of
written English from learners around the world;
(b) Computational techniques: CLC was first searchable lexically,
with 76 error codes; subsequently tagged for parts of speech
and parsed using an automatic parser, RASP, Briscoe et al 2006;
(c) New research methodology: designed to yield practical
benefits for learning/teaching/assessment, and to make a
theoretical contribution to SLA.
The key theoretical and methodological innovations include:
(i) the concept of criterial features, as a means of distinguishing
levels of proficiency in the learning of a second language;
(ii) the development of a general learning model, CASP
(“complex adaptive system principles of SLA”) informed by the
criterial features of the CLC and by other empirical studies in the
literature.
These two innovations, especially CASP, were developed on the
basis of joint work with my principal collaborator, Luna Filipović
(then Cambridge, now University of East Anglia). Further
assistance from members of the Cambridge team is recognized
in the Acknowledgements at the end of this talk.
Criterial features are properties of learners’ English that
are distinctive and characteristic of L2 proficiency at
the different levels. The CLC scripts have been graded
by Cambridge examiners and assigned grades A-F at
each of six levels of proficiency, following the
Common European Framework of Reference (CEFR),
see the Council of Europe 2001 :
Levels:
C2
C1
B2
B1
A2
A1
Mastery
[CPE]
Effective Operational Proficiency [CAE]
Vantage
[FCE]
Threshold
[PET]
Waystage
[KET]
Breakthrough
When searching for criterial differences between
levels we focussed on the scripts of students who had
achieved passing grades of A-C at each level.
The questions that motivated this research are:
1) how much of the grammar and lexicon of
English do learners actually know and/or
produce at each of these CEFR levels?
2) what empirical patterns and principles are there
in these developing second language stages of
English? and
3) what are the practical benefits, for learning,
teaching and assessment of gathering this
information?
Electronic corpora of learner English make it
possible for us to answer these questions.
The CLC is the biggest learner corpus of English or of any
language. It gives us empirical evidence for developmental
stages in the learning of new constructions, words and word
meanings.
It gives us quantitative data on learner errors in syntax,
morpho-syntax and lexical choice.
It was originally searchable only lexically, in conjunction with
the error codes. Subsequently it has been tagged and parsed
using the automatic parser, RASP.
Sample Error Codes in the CLC
RN Replace noun Have a good travel (journey)
RV Replace verb I existed last weekend in London
(spent)
MD Missing determiner I spoke to President (the)
I have car (a)
AGV Verb agreement error The three birds is singing
(are)
IV Incorrect Verb Inflection I spended last week in London
(spent)
FJ Wrong Adjective Form
The situation got worst (worse)
UQ Unnecessary Quantifier A little bit quite common (quite
common)
DY Derivation of Adverb
It happened fastly (fast)
Briscoe’s RASP (Robust Accurate Statistical
Parser)
•
•
•
identifies parts of speech (PoS) probabilistically
tagging
generates a parse forest representation containing
all possible subanalyses with associated
probabilities
weighted Grammatical Relations yielded by the nbest parses of the input.
Criterial features can be found in all areas of
English: syntax, morphology, phonology, the
lexicon, semantics, and discourse. They distinguish
higher proficiency levels from lower levels in an
efficient way.
In this talk some of these features are illustrated, as is the
theoretical learning model derived from them, “CASP”.
An analogy:
Languages change over time, and when historians of
English examine Old English, Middle English and
Early Modern English, they focus on important
differences between these stages, not on what
stayed the same. Similarly in a learning context, we
are interested in changes from one level to another.
There are different types of criterial features.
Here we focus on just two:
Positive Criterial Features
These refer to positive, i.e. correct, linguistic
properties of English that have been acquired at a
certain L2 level and that generally persist at all
higher levels. A property P (e.g. a new construction
type) acquired at B2 may differentiate that level and
higher levels from [A1, A2, B1] and will be criterial
for the former. Or P may be acquired at C2 and
differentiate this level from all lower levels.
Negative Criterial Features
These are incorrect properties of English, or errors,
that occur at a certain level or levels and with a
characteristic frequency. Both the presence versus
absence of the errors, and especially their
frequency (the "error bandwidth"), can be criterial
for the level(s).
Examples of Positive Criterial Features
(from Hawkins & Filipović 2012 and using data from the CLC)
The A levels (A1 and A2)
Simple intransitive clauses (NP-V) and the
slightly more complex transitive (NP-V-NP)
sentence types are present from the
beginning:
He went. (NP-V) A1
He loved her. (NP-V-NP)
A1
Modal auxiliary verbs like may, might, can
and must appear first at A1 or A2, but only
in some of their senses.
Can is first attested in the PERMISSION sense at A1
and in the POSSIBILITY sense at A2:
And if you want, you can bring pencils or pens. (PERMISSION)
A1
In this magazine you can see all the new C.D.[s] and all the
dates of the concerts. (POSSIBILITY) A2
Noun Phrase sequences of Pronoun plus
Infinitive are found at A2:
something to eat
nothing to do
A2
A2
as are postnominal modifiers with participial
–ed:
beautiful paintings [painted by famous Iranian painters]
A2
Lexical verbs appearing at the A levels are
typically among the most basic and frequent
verbs of English; they appear first in their
most basic and frequent senses.
Verbs attested at A1 include:
catch, eat, give, put, take and walk
New lexical verbs appearing at A2 include:
break, cut, hit, push, stand, and fall
again typically in their most basic and literal senses.
For break this includes its primary physical sense:
I broke a beautiful glass. A2
for cut it includes the following example in its
primary sense:
First I cut the cake with my mother. A2
The B Levels (B1 and B2)
The new features at B1 involve more complex
syntax, e.g. an “Object Control” structure such as:
I ordered him [to gather my men to the hall]
B1
him is both the object of ordered and the logical
subject of gather here.
This is a criterial construction for B1 and higher
levels which distinguishes them from the A levels.
Structures like the following with finite or
non-finite subordinate clauses and
movement of the WH-word (how, where, etc)
to the front of its clause are also first
attested at B1:
I don’t know [how I could have done it]
I did not know [where to look for it]
B1
B1
And postnominal modifiers in participial –ing
become productive at B1:
I received your mail [asking for the sales report]
B1
Structures with a finite subordinate clause
positioned to the right of predicates like is
true and seems with a subject it are also
criterial for B1 and higher levels:
It’s true [that I don’t need a ring to make me remember you]
B1
i.e. so-called “Extraposition” structures
A large number of new lexical verbs appear
for the first time at B1 including:
divide, fit, grab, spill, stick and tear
And the meanings of the verbs that appeared first
at A1 and A2 begin to expand from their basic
senses.
break appears for the first time in the extended
sense of INTERRUPT at B1:
At last I managed to break the routine of the city … B1
Constructions that are criterial for B2 and
higher levels include “secondary predications”
go and paint the houses yellow and blue
B2
with yellow and blue predicated of the direct object
houses
“Extraposition” structures with a non-finite
subordinate clause positioned to the right of
its predicate are B2
It would be helpful [to work in your group as well]
B2
And so-called “Pseudocleft” structures with
an initial what functioning as subject of its
verb:
What fascinated me was [that I was able to lie on the sea surface]
B2
“Subject-to-Subject Raising” constructions
appear first at B2 with most of the higher
verbs and adjectives that trigger this rule,
for example prove:
The car has proved [to be one of the most important
inventions of our century]
B2
Similar examples are found at B2 with other raising verbs and
adjectives (The car happened to be …, The car appeared to be
…, The car turned out to be …, The car is likely to be …, etc)
New lexical verbs at B2 include
acquire, capture, drag, rush, spread,swallow
and new meanings and uses are attested for the
verbs that appeared earlier.
For break, first attested at A2, these include new
collocations such as break a promise or break the
law:
For cut, also an A2 verb, they include new meanings
at B2 such as REDUCE in cut the cost
The C Levels (C1 and C2)
“Subject-to-Object Raising” constructions with the
verb believe appear first at C1 and are criterial for the
C levels:
I believe her [to be this country’s best representative]
C1
Passivized Subject-to-Object Raising
constructions such as the following with
assumed are also criterial for C1:
the low cost of membership and entry was assumed to be an
advantage. C1
Sequences of two prenominal –s genitives are
found at C1:
in the bride’s family’s house
C1
Structurally:
in [[[the bride’s] family’s] house]
New lexical verbs appearing first at C1
include
accumulate, boast, quote, reassure, shape and
stain
along with new meaning possibilities for the verbs
already introduced. E.g. break appears first in the
idiomatic sense of break the bank at C1.
New features appearing at C2 include less
common Subject-to-Object Raising
constructions with higher predicates such as
presume, declare and remember:
He presumed work [to be the way to live]
C2
New lexical verbs at C2 include
stagger, sway, limp, saunter, raid,squander
New meanings for break at C2 include original
figurative senses such as the attested break the
wall that surrounds him.
Negative Criterial Features
One major distinguishing feature of the C levels can
be seen in the low frequencies for “negative
features” or error types such as those illustrated
above.
There are significant improvements in ALL of the
syntactic and morpho-syntactic error types at the C
levels.
By contrast, at the B levels improvements are
relatively modest, and for many error types the
scores actually get worse, especially at B2, before
they get better again at C1.
The error codes involve morpho-syntactic
errors of inflection, derivation and
grammatical form, syntactic errors of
omission, positioning and co-occurrence,
and errors of appropriate lexical choice. It is
clear that learners at the C levels are
increasingly mastering these rules of
English, whereas B-level learners are not
(see Hawkins & Filipović 2012 for details).
We must now ask: WHY do we see these
patterns in the data and why do we see the
criterial features changing the way they do
at the different levels? In particular, WHAT
is it about the features of the higher
proficiency levels that makes them late
acquired rather than early?
It cannot simply be that learners are
imitating the words and constructions they
are explicitly taught in their textbooks.
First, because there are many different textbooks
and teaching methods around the world.
But secondly because learners learn more than they
are explicitly taught, from their reading materials,
papers, magazines, movies, TV, conversations, etc.
I.e. second language learning shares many
similarities with first language learning, but not all
obviously.
For example, more frequently occurring
words and constructions are learned before
less frequent ones,
and simpler words, constructions and
meanings are learned before more complex
ones,
in both first and second language
acquisition.
E.g. learning English nouns and verbs with high
frequencies of use is easier than learning those
with lower frequencies, because they are
encountered more frequently (greater exposure);
frequent lexical items are overrepresented at first
in L2 English, moving gradually to L1 English
norms (see Hawkins & Buttery 2009, Hawkins & Filipović 2012)
The constructions of English that are
learned earliest are those that occur most
frequently in the input, as reflected in e.g.
the British National Corpus. This could be
established by comparing the CLC with the
British National Corpus (BNC), see Williams
(2007).
The new constructions that are criterial for
A2, B1 and B2, in Williams’ (2007) data,
appear to be learned in direct proportion to
their frequency in the input, as reflected in
the BNC. The more exposure, the earlier the
acquisition and the easier the learning.
This is shown in Tables 1, 2 and 3. Table 1 lists the
new construction types found, for example, at B1.
Tables 2 and 3 give the frequency correlations
between the CLC and the BNC for the different levels.
Table 1 New B1 Verb Co-occurrence Frames
NP-V-NP-NP
She asked him [his name]
NP-V-VPinfin (Wh-move) He explained [how to do it]
NP-V-NP-V(+ing) (Obj Control)
I caught him stealing
NP-V-NP-PP (P=to) (Subtype: Dative Movement) He gave [a big kiss] [to his
mother]
NP-V-NP-(to be)-NP (Subj to Obj Raising)
I found him (to be) a good doctor
NP-V-NP-Vpastpart (V=passive) (Obj Control) He wanted [the children] found
NP-V-P-Ving-NP (V=+ing) (Subj Control)
They failed in attempting the climb
NP-V-Part-NP-PP
I separated out [the three boys] [from the crowd]
NP-V-NP-Part-PP
I separated [the three boys] out [from the crowd]
NP-V-S (Wh-move)
He asked [how she did it]
NP-V-PP-S They admitted [to the authorities] [that they had entered illegally]
NP-V-Part
She gave up
NP-V-S (whether = Wh-move) He asked [whether he should come]
NP-V-P-S (whether = Wh-move) He thought about [whether he wanted to go]
Table 2 Frequencies for Verb Co-occurrence
Frames in English Corpora (including BNC)
Average Token Frequencies in the BNC for
the new Verb Co-occurrence Frames
appearing at the learner levels
A2
1,041,634
B1
38,174
B2/C1/C2
27,615
Table 3 Frequency Ranking
Average Frequency Ranking in the BNC for
the new Verb Co-occurrence Frames
appearing at the learner levels
A2
8.2
B1
38.6
B2/C1/C2
55.6
These kinds of data enable us to set up the
following principle of second language
learning (for which there are also well-attested
parallels in first language learning, see e.g.
Tomasello 2003, Diessel 2004, MacWhinney 2005):
(1) Maximize Frequently Occurring Properties (MaF)
Properties of the L2 are learned in proportion to
their frequency of occurrence (as measured, for
example, in the BNC): more frequent exposure of a
property to the learner facilitates its learning and
reduces learning effort.
I.e. more frequent properties will result in earlier L2
acquisition, more of the relevant properties learned, and
fewer errors, in general. Infrequency makes learning more
effortful, with precise predictions depending on other factors.
Highly correlated with frequency is another principle
of second language learning (shared with first
language learning) that involves the relative
simplicity or complexity of structures and meanings.
The criterial grammatical features of earlier levels
are, in general, simpler than those of later levels.
In phonology also simpler consonants and
consonantal distinctions are acquired earlier
than more complex ones (see e.g. Eckman
1984).
Simpler and more basic meanings for verbs
are acquired earlier than more complex and
derived extensions in meaning, figurative
uses, etc.
The verb break in its basic physical sense at A2
break in the sense of INTERRUPT (break the routine) B1
break an agreement, promise, etc. B2
break the bank (idiomatic) C1
break the wall that surrounds him (original figurative) C2
(2) Maximize Structurally and Semantically Simple
Properties (MaS)
Properties of the L2 are learned in proportion to
their structural and semantic simplicity: simplicity
means there are fewer properties to be learned and
less learning effort is required.
I.e. simpler properties will result in earlier L2 acquisition,
more of the relevant properties learned, and fewer errors.
Complexity makes learning more effortful, in general, since
there are more properties to be learned, with precise
predictions depending on other factors.
In second language learning we also see
‘transfer’ effects from the first language,
either positive (when the transfer results in a
correct L2 property) or negative (when it
results in an error).
This is one thing that differentiates second from
first language acquisition.
E.g. speakers of languages with definite and
indefinite articles find it easier to acquire
the article system of English than do
speakers of languages without articles (see
Hawkins & Buttery 2009, 2010)
Errors involving missing definite and
indefinite articles in the L2 English of the
CLC are consistently low when the L1s also
have articles.
Recall: MD
I spoke to President (the)
I have car (a)
Table 4 (next slide) shows missing
determiner error rates for “the” and “a” at all
proficiency levels for French, German and
Spanish as first languages. All three
languages have an article system. (Data from
Hawkins & Buttery 2009)
The figures indicate the percentage of errors with respect to
the total number of correct uses. For instance a percentage of
10.0% would indicate that a determiner was omitted 1 in every
10 times that it should have appeared.
We see generally low error rates for these languages, without
significant deviation between levels.
Table 4 Missing Determiner Error Rates for L1s with
Articles
French
German
Spanish
French
German
Spanish
A2
4.76
0.00
3.37
Missing “the”
B1
B2
4.67
5.01
2.56
4.11
3.62
4.76
C1
3.11
3.11
3.22
C2
2.13
1.60
2.21
A2
6.60
0.89
4.52
Missing “a”
B1
4.79
2.90
4.28
C1
4.76
3.62
5.16
C2
3.41
2.02
3.58
B2
6.56
3.83
7.91
Table 5 (next slide) shows missing
determiner error rates for “the” and “a” at all
levels for Turkish, Japanese, Korean,
Russian and Chinese as first languages.
These languages do not have an article
system.
There is a general linear improvement, i.e. a decline, in error
rates across the levels with increasing proficiency (shown
from left to right).
Chinese shows an interesting inverted U-shaped progression,
especially in the case of missing “a”.
Table 5 Missing Determiner Error Rates for L1s
without Articles
Turkish
Japanese
Korean
Russian
Chinese
Missing “the”
A2
B1
B2
22.06
20.75
21.32
27.66
25.91
18.72
22.58
23.83
18.13
14.63
22.73
18.45
12.41
9.15
9.62
C1
14.44
13.80
17.48
14.62
12.91
C2
7.56
9.32
10.38
9.57
4.78
Table 5 continued
Turkish
Japanese
Korean
Russian
Chinese
Missing “a”
A2
B1
24.29
27.63
35.09
34.80
35.29
42.33
21.71
30.17
4.09
9.20
B2
32.48
24.26
30.65
26.37
20.69
C1
23.89
27.41
32.56
20.82
26.78
C2
11.86
15.56
22.23
12.69
9.79
One of the learning principles proposed in Hawkins &
Filipović (2012) to account for these data is
Maximize Positive Transfer:
(3) Maximize Positive Transfer (MaPT)
Properties of the L1 which are also present in the
L2 are learned more easily and with less learning
effort, and are readily transferred, on account of
pre-existing knowledge in L1.
Shared L1/L2 properties should result, in general, in earlier L2
acquisition, in more of the relevant properties being learned,
and in fewer errors, unless these shared properties involve e.g.
high complexity and are impacted by other factors. Dissimilar
L1/L2 properties will be harder to learn by virtue of the
additional learning that is required, again in general.
More generally, Filipović & Hawkins (2013)
provide a multi-factor model of learning,
supported and informed by data in the CLC,
and comprising a set of interacting principles
such as those illustrated.
The model is a type of “complex adaptive
system” (see Gell-Mann 1992) and is called the
“CASP” model, short for “complex adaptive
system principles of SLA”.
The principles interact, sometimes reinforcing each
other (e.g. early acquired frequent items are also
often simple), sometimes competing to produce
variable outputs and alternative interlanguages.
Some of the principles are more general, others more
specific. Two of the more general principles are:
(A) Minimize Learning Effort and (B) Minimize
Processing Effort.
(A) Minimize Learning Effort (MiL)
Learners of a second language (L2) prefer to
minimize learning effort when they learn the
grammatical and lexical properties of the L2.
Learning effort is minimized when shared properties of the L1
can be transferred directly into the L2 (MaPT), when properties
of the L2 are frequently occurring in the L2 input (MaF), when
structural and semantic properties of the L2 are simple rather
than complex (MaS), and when there are fewer linguistic items
to be learned in a given grammatical or lexical domain.
(B) Minimize Processing Effort (MiP)
Learners of a second language (L2) prefer to
minimize processing effort when they use the
grammatical and lexical properties of the L2, just as
native speakers do.
E.g. even when more complex properties have been learned at
an acquisition stage, L2 learners will still prefer to use simpler
properties, just like native speakers do.
Principles (A) and (B) are principles of least effort. If these
were the only principles determining learning and production
our learner corpora would reveal increasingly minimal
outputs.
Clearly, they do not. MLUs (i.e. mean length of utterance
figures) increase at each higher proficiency level (cf. Hawkins
& Filipović 2012:ch.2.2) as greater use is made of less
frequent and more complex structures and meanings:
A2
B1
B2
C1
C2
7.9
10.8
14.2
17.3
19.0
The reason is that learners are trying to increase
their expressive power in the L2, and to behave like
native speakers, which means learning and using the
mix of infrequent and frequent, and complex and
simple, linguistic items, just like native speakers do.
(C) Maximize Expressive Power (MaE)
Learners of a second language (L2) prefer to maximize their
expressive power, i.e. to formulate in the L2 whatever thoughts
they would wish to express in the L1, and to perform the same
language functions as L1 users.
Successive stages of acquisition reveal more native-like L2 outputs with
increasingly complex and less frequent structures for the expression of
increasingly complex thoughts, in partial opposition to principles (A)
MiL and (B) MiP.
(D) Maximize Communicative Efficiency (MaC)
Learners of a second language (L2) prefer to maximize their
communicative efficiency in relation to the hearer and his/her
mental model.
Communication is efficient when the message (M) intended by
the speaker (S) is calibrated to the hearer's (H) mental model in
such a way as to achieve accurate comprehension of M with
rapid speed.
This requires sometimes more, sometimes less, processing
effort, in partial opposition to principle (B) MiP.
Principle (D) can help us explain some interesting differences
between ‘positive’ and ‘negative’ transfers, i.e. transfers from
the L1 that are correct rather than error-ful.
The three more specific principles introduced earlier follow
from these more general principles:
(1) Maximize Frequently Occurring Properties (MaF)
Properties of the L2 are learned in proportion to their frequency of
occurrence: more frequent exposure of a property to the learner
facilitates its learning and reduces learning effort.
(2) Maximize Structurally and Semantically Simple Properties (MaS)
Properties of the L2 are learned in proportion to their structural and
semantic simplicity: simplicity means there are fewer properties to
be learned and less learning effort is required.
(3) Maximize Positive Transfer (MaPT)
Properties of the L1 which are also present in the L2 are learned
more easily and with less learning effort, and are readily transferred,
on account of pre-existing knowledge in L1.
Let’s now consider a fourth specific principle, involving negative
transfers from the L1. CASP can explain some interesting
puzzles here in the SLA literature:
(4) Permit Negative Transfer (PNT)
Properties of the L1 which are not present in the L2 can be
transferred, resulting in errors, as learners strive to achieve an
expressive power and communicative efficiency in L2
comparable to that in their L1 (see principles C and D), while
minimizing learning effort (principle A) and/or processing
effort (principle B).
I.e. when grammatical and lexical properties are shared, transfers from
L1 into L2 result in positive or correct properties in the L2. When
properties are not shared, and the transfer still takes place, this results
in negative or incorrect properties in the L2.




One major difference between positive and negative transfers
is that there are severe limitations on expressive power and
on communicative efficiency that can be conveyed by
linguistic properties when they are not part of the L2 and are
not used by its native speakers.
When native speakers communicate with L2 learners they
tolerate and compensate for departures from the native
language conventions. But when learners depart too radically
from these conventions, they are not understood by native
speakers.
Learners accordingly acquire a sensitivity to the native
speaker’s ability to compensate for these violations in
conventions of grammar and use.
This, we believe, plays a major role in determining whether
and when negative transfer can occur and when errors will be
found, see principle (5):
(5) Communicative Blocking of Negative Transfer (CBN)
The transfer of negative properties from L1 to L2 is
filtered in proportion to communicative efficiency
(principle D): the more an L1 property impedes efficient
communication in L2, the less negative transfer there is.



In phonology substitution of L1 consonants like [t] or [s] or [f]
for L2 [θ] in English thin minimizes learning and processing
effort for learners whose L1s do not have this consonant, and
these substitutions generally succede communicatively (Lado
1957).
In syntax Spanish Pro-Drop (e.g. *is a beautiful country for it
is a beautiful country) is often transferred into early L2
English to express the proposition in question and the
removal of the subject it does not impede communicative
success. This structure is simpler than its English counterpart
with an overt subject, and transfer is not blocked, as
predicted by our principle (3) MaS.
Similarly, many article omission errors do not diminish
expressive power and communicative success, and at the
same time they minimize learning and processing effort
through the transfer of L1 structures, see above.

By contrast, Chinese prenominal relative clauses do not result
in errors whereby the English man whom the woman loves is
changed into its Chinese prenominal counterpart *the woman
loves whom man



This Chinese structure is complex and typologically marked
cross-linguistically (Hawkins 2004, Eckman 2011), and if
Chinese learners used it in L2 English, they wouldn’t be
understood.
More generally, many structures and meanings will often not
transfer from L1 to an L2 even when they are shared, and will
be blocked by principles (2) MaF, (3) MaS and (5) CBN.
I.e. our interacting CASP learning principles make predictions
for when an L1 feature will transfer, and when it will not.
Consider the basic word orders of English and
Japanese. These languages have mirror-image
patterns, head-initial versus head-final, that are both
frequent and productive across languages:
[went [to [the cinema]]] versus [[[the cinema] to] went],
(Greenberg 1966; Dryer 1992; Hawkins 1983, 1994, 2004)
Head-final Japanese orders are not transferred into L2 English
by Japanese learners, just as head-final Chinese noun phrases
are not transferred into L2 English. Why not?
Because that would result in extreme communicative
inefficiency: speakers using Japanese or Chinese word orders in
English L2 would simply not be understood! By contrast, headinitial word order variants of Spanish that lack precise
counterparts in English (e.g., I read yesterday the book) are
negatively transferred into L2 English, and they they do not
impact efficient communication.
We predict that because Japanese is a head-final language, the
contrast with the mirror-image word order patterns of English is
considerable and transferring head-final patterns into a headinitial language like English, and vice versa, would significantly
impair communication. This is why it is imperative for Japanese
learners of English, and English learners of Japanese, to acquire
correct basic word orders in their L2s early.
But speakers of L1 languages with flexible SVO like Spanish do
not have the same incentive, because even when they transfer
incorrect orders from their L1 into a fundamentally similar headinitial English L2, communication is not significantly impaired.
The CLC error data for Japanese and Spanish learners reflect this
difference perfectly: word order errors are rare or non-occurring
for the former, but common for the latter.
(6) Order of Second Language Acquisition (OSLA)
The order of acquisition for properties of the L2 is in
accordance with general principles (A)-(D), and with the more
specific principles and patterns that are supported empirically.
These principles can be incorporated within a multi-factor
model of SLA, the CASP model, and used to define possible
versus impossible, and likely versus unlikely, interlanguage
stages proceeding from a given L1 to a given L2.
These principles operate collectively to make constrained
predictions for the acquisition of properties of L2 English and of
other languages, and for their relative sequencing. Their
interaction is complex, because there are several such
principles, which sometimes compete and sometimes
cooperate, because they are gradient, and because they have
different relative strengths.
Some Practical Applications of this Research
Once criterial features of the different
proficiency levels and the interacting
principles of the CASP model have been
defined, they can be put to use for learning,
teaching and assessment purposes.
For Learning and Teaching
NB! Our criterial features are taken only from candidates who
scored passing grades at each level.
Hence learners who are studying for the relevant level can now
be told explicitly what their successful peers have mastered, and
teachers can incorporate these features in their teaching.
Grammatical and lexical properties of English, and teaching
materials and methods built around them, can be calibrated to
the criterial features of each level, making learning more
efficient.
Learners striving for B1 can be introduced to Object
Control structures that are first attested at B1 like
I ordered him [to gather my men to the hall]
B1
and to subordinate clauses with WH-movement:
I don’t know [how I could have done it]
I did not know [where to look for it]
B1
B1
They can be introduced to the lexical verbs that
successful candidates in B1 exams know, e.g.
divide, fit, grab, spill, stick, tear
and to the expanding meanings of verbs learned
earlier:
e.g. break appears for the first time in the
extended sense of INTERRUPT at B1:
At last I managed to break the routine of the city … B1
Similarly for the other levels and their features.
More generally, grammar and vocabulary can be
introduced in a sequence that reflects their
frequency in the input and their inherent
simplicity/complexity, as revealed both through
the CLC and through native speaking corpora like
the BNC.
For Assessment
This research provides content that can
help to validate the scores that examiners
of English have provided independently.
The assignment of a level and a grade to a sample of learner
English currently relies on judgments that examiners make
based on their experience and training. Examiners have
learned to assign scores with good inter-examiner
agreement, but there is still a certain amount of intuition that
they bring to the task. Examiners are implicitly rather than
explicitly aware of what to look for in many cases.
An individual script, let us abbreviate it as S, by a
candidate taking an exam at level X can be searched
for the presence versus absence of criterial features
derived ultimately from all passing scripts at X, and
from those at the immediately lower level X-1 or at
the immediately higher level X+1.
Script S may contain several constructions and
lexical items that are features of B2 and higher
levels. This establishes that S is at least B2. The
script might contain no uniquely C-level features,
however. These levels are eliminated, therefore,
and B2 is supported. S may even contain a unique
B2 feature. This all supports B2.
Criterial features can also be used in the
preparation of diagnostic grammar tests that
assign students to their appropriate levels of
instruction based on their command of
English grammar.
L1-specific ELT materials can be written for
different groups of learners.
For learners whose first languages have no definite
and indefinite articles, English language materials
can encourage explicit and implicit learning in this
area.
The learning stages, transfer effects and
error types characteristic of Spanish learners
of English can be reflected in textbooks and
teaching materials designed specifically for
them.
Similarly for Chinese learners, and Japanese
learners, and Russians, etc.
Theoretical interest of this work
The criterial features we are extracting from the
corpus are of direct benefit for theoreticians
studying language acquisition. They provide a new
set of empirical patterns that can inform predictive
and multi-factor theories of learning such as CASP
and they enable us to test and refine principles of
frequency, complexity and transfer, as illustrated in
this talk.
(see Hawkins & Filipović 2012 and Filipović & Hawkins 2013 for
further details)
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Acknowledgments
The findings reported here are based on joint work with Luna Filipović
(Cambridge Linguistics Department, now University of East Anglia), see
Hawkins & Filipović 2012 and Filipović & Hawkins 2013. The assistance of
many other researchers and collaborators was vital. Special thanks to:
Ted Briscoe of the Cambridge Computer Lab and his colleagues for use of the
RASP parser;
Paula Buttery of DTAL, Cambridge (see Hawkins & Buttery 2009, 2010);
Dora Alexopoulou of the Education First Research Unit, DTAL, for advice and
input;
Andrew Caines of DTAL, Cambridge, for help with numerous syntactic searches;
Annette Capel of CUP for help with the wordlist searches;
Kristen Kennedy of UC Davis for help with MLU calculations;
Mike Milanovic & Nick Saville of Cambridge ESOL for theoretical and practical
guidance and financial support (see below);
Mike McCarthy of CUP and Penn State U for advice and input;
Roger Hawkey and Angeliki Salamoura of Cambridge ESOL for advice and English
Profile Programme co-ordination;
Lu Gram of the Computer Lab for help with error calculations and other searches;
Caroline Williams of RCEAL, Cambridge for verb subcategorization data;
and to
CUP’s computational linguists who prepared "The <#S>
Compleat|Complete</#S> Learner Corpus Document" 2006, from which the error
codes and examples sentences are taken.
Financial Support
The work reported here was made possible by
generous financial support from Cambridge
Assessment and from Cambridge University Press,
within the context of the Cambridge English Profile
Programme, and by research funds and a seed
grant for international outreach from the University
of California, Davis. This support is gratefully
acknowledged.
Links to Learner Corpora for English and Other Languages
The EF (Education First) Cambridge Open Language Database
for English (30+ million words):
http://corpus.mml.cam.ac.uk/efcamdat/
Sylviane Granger’s summary of learner corpora for English and
other languages worldwide:
https://www.uclouvain.be/en-cecl-lcworld.html