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LEXIN: A lexical database from Spanish kindergarten and first-grade readers


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The LEXIN database offers psycholinguistic indexes of the 13,184 different words (types) computed from 178,839 occurrences of these words (tokens) contained in a corpus of 134 beginning readers widely used in Spain. This database provides four statistical indicators: F (overall word frequency), D (index of dispersion across selected readers), U (estimated frequency per million words), and SFI (standard frequency index). It also gives information about the number of letters, syntactic category, and syllabic structure of the words included. To facilitate comparisons, LEXIN provides data from LEXESP's (Sebastián-Gallés, Martí, Cuetos, & Carreiras, 2000), Alameda and Cuetos's (1995), and Martínez and García's (2004) Spanish adult psycholinguistic frequency databases. Access to the LEXIN database is facilitated by a computer program. The LEXIN program allows for the creation of word lists by letting the user specify searching criteria. LEXIN can be useful for researchers in cognitive psychology, particularly in the areas of psycholinguistics and education.
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Psycholinguistic databases collect indexes of psycho-
linguistic properties of words. This information is very
useful for experimental psychologists interested in con-
trolled research with oral and written language stimuli.
The use of these psycholinguistic indexes started within
the field of applied educational psychology (see, e.g.,
Thorndike, 1921) and expanded to more basic cognitive
research, such as research on visual word recognition.
One important index of printed words is the frequency
of occurrence; written frequency has been shown to in-
fluence reading accuracy and response times to words
greatly. Specifically, research has demonstrated that high-
frequency words are responded to more quickly and more
accurately than low-frequency words are (Becker, 1976;
Forster & Chambers, 1973; for a lexical decision task, see
Balota & Chumbley, 1984; for a pioneering work, see Cat-
tell, 1886; for a word-naming task, see Hino & Lupker,
2000; for a review on word frequency effects, see Mon-
sell, 1991). This lexical frequency effect is also evident in
the reading performance of neuropsychological patients,
such as dyslexics (for a revision, see Behrmann, Plaut, &
Nelson, 1998) and patients with Alzheimer’s disease (see,
e.g., Glosser, Grugan, & Friedman, 1999).
Printed-word frequency counts are usually obtained
by collecting words from a representative pool of print
resources that are read by a particular group of readers.
These counts are presented as frequency dictionaries or fre-
quency norms. Two of the most frequently quoted counts
are the Kukera and Francis (1967) dictionary for American
English and the CELEX (Baayen, Piepenbrock, & Guli-
kers, 1995) dictionary for English, Dutch, and German. In
Spanish, there are also very widely used counts, such as
the Sebastián-Gallés, Martí, Cuetos, and Carreiras (2000)
dictionary (for another dictionary, see also Alameda & Cue-
tos, 1995; for the addition of other indexes to the pool from
Sebastián-Gallés et al., 2000, see Davis & Perea, 2005). All
of these counts were obtained from adult print resources.
Similarly, there are many specific counts collected from
children’s print resources that account for children’s re-
duced visual lexicon (due to their inexperience in read-
ing). The purpose of these children’s dictionaries is to
offer a more accurate tool for testing initial visual word
recognition in this sample. Two of the most frequently
quoted counts for primary school grades are The Ameri-
can Heritage Word Frequency Book (Carroll, Davies, &
Richman, 1971) and The Educator’s Word Frequency
Guide (Zeno, Ivens, Millard, & Duvvuri, 1995), both in
American English. Counts in other European languages
are the Marconi, Ott, Pesenti, Ratti, and Tavella (1994)
dictionary in Italian for primary-school children; the
Stuart, Dixon, Masterson, and Gray (2003) dictionary in
English for children from 5 to 7 years old; and the Lété,
Sprenger-Charolles, and Colé (2004) dictionary in French
for primary-school children (for an extension, see Peere-
man, Lété, & Sprenger-Charolles, 2007).
In Spanish, there are dictionaries of elementary school
children’s reading vocabulary (Casanova & Rivera, 1989;
Martínez & García, 2004; for an extension, see also Mar-
tínez & García, 2008) and productive written vocabulary
(Justicia, 1995). However, there is no dictionary for the ear-
liest stages of reading acquisition. This seems surprising if
we consider that the vocabulary of the average preschool
child ranges between 2,500 and 5,000 lemma or word
families (Beck & McKeown, 1991) and that the average
1009 © 2009 The Psychonomic Society, Inc.
LEXIN: A lexical database from Spanish
kindergarten and first-grade readers
University of Deusto, Bilbao, Spain
The LEXIN database offers psycholinguistic indexes of the 13,184 different words (types) computed from
178,839 occurrences of these words (tokens) contained in a corpus of 134 beginning readers widely used in
Spain. This database provides four statistical indicators: F (overall word frequency), D (index of dispersion
across selected readers), U (estimated frequency per million words), and SFI (standard frequency index). It also
gives information about the number of letters, syntactic category, and syllabic structure of the words included.
To facilitate comparisons, LEXIN provides data from LEXESP’s (Sebastián-Gallés, Martí, Cuetos, & Car-
reiras, 2000), Alameda and Cuetos’s (1995), and Martínez and García’s (2004) Spanish adult psycholinguistic
frequency databases. Access to the LEXIN database is facilitated by a computer program. The LEXIN program
allows for the creation of word lists by letting the user specify searching criteria. LEXIN can be useful for re-
searchers in cognitive psychology, particularly in the areas of psycholinguistics and education.
Behavior Research Methods
2009, 41 (4), 1009-1017
E. Goikoetxea,
& Ellis, 1997). One objective measure of the age of ac-
quisition of reading vocabulary involves the use of texts
specifically designed for readers of certain ages. Thus, a
children’s frequency dictionary based on kindergarten and
first-grade reading material, like the one presented here,
can be used not only as a tool for accurately measuring
children’s early reading vocabulary but also as an objec-
tive estimate of the frequency of occurrence of each word
in these specific age groups.
In sum, the LEXIN database was created in order to
offer a new normative tool for the study of the reading
vocabulary of beginning readers in Spanish, a widely used
language. In order to facilitate the use of this database, we
created software called “LEXIN.” This program provides
the indexes that have been incorporated into the database
and that can be utilized by the user as search criteria for
the creation of word lists.
Corpus Sampling
The LEXIN corpus was compiled from 134 reading
and spelling books that were designed for children learn-
ing to read (76 for kindergarten and 58 for first grade)
by the leading Spanish publishers (see the Appendix for a
complete list of readers and additional information). These
books are intended to be used in kindergarten or first grade,
depending on what each school decides. In Spain, formal
reading instruction takes place in the first year of primary
school. During the three preschool years (3–6 years old),
children are not usually taught how to read. However, pre-
school literacy instruction varies from school to school.
Thus, some teachers try to develop basic decoding skills
by introducing some letter–sound correspondences com-
bined with a limited number of sight words.
The reading texts were selected, first, on the basis of sales
for the years 2002 and 2003 (per a Santillana representa-
tive, personal communication, November 2003). Thus, we
computed the cumulative sales figures for the set of readers
available for kindergarten and first grade and then retained
the sample that accounted for 90% of the sales.
Second, we included readers that used all of the ap-
proaches to reading instruction, from code-emphasis ap-
proaches to whole-language approaches. However, the
majority of the materials are based on a code-emphasis
approach, which is the prevailing teaching method in
Spain. As Chall (1983) defined it, the code-emphasis
approach puts the instructional emphasis on developing
learners’ recognition of letter–sound correspondences
while providing the children with sufficient opportunities
to establish their decoding skills. Thus, using a phonics
method, the readers present one grapheme at a time and
then immediately provide practice in blending the sounds
into syllables and whole words. Using a syllabic method,
the readers present syllabic families from the beginning
(e.g., ma, me, mi, mo, mu). Children learn to sound out
words by combining known syllables.
Third, we include readers drawn from a broad range
of material. We incorporate readers (reading workbooks),
narrative texts (stories), and school texts. Therefore, the
first grader will acquire about 6,000 more (Chall, 1987).
And, whereas a preschool reading book includes about 500
word forms, according to our calculations, a first-grade
reading book includes about 23,000 words. This acceler-
ated vocabulary growth from preschool to primary school
justifies the need for developing a specific dictionary for
children who are in the earliest stages of reading acquisi-
tion. Thus, the main purpose of this database is to create a
specific dictionary for beginning readers.
This dictionary is useful for two purposes. First, using
a corpus of words that are common in beginning reading
materials makes it possible to create sensitive measures
of early reading ability while avoiding the floor effects
that usually appear in standardized tests (Bowey, 2005).
Second, using this corpus of words provides a more ap-
propriate lexicon for teaching initial word recognition to
beginning readers. Therefore, this database is intended to
become a useful tool for both researchers and profession-
als who need an early lexical database of beginning read-
ing materials in Spanish.
Although there is strong evidence for the effects of word
frequency, as we stated above, a growing body of litera-
ture exists on the issue of whether the effects of word
frequency would be better described in terms of the age
of acquisition (also termed order of acquisition). Age
of acquisition, or the age at which words are incorpo-
rated into the lexicon, is a variable investigated in ac-
counts of the lexical retrieval and lexical production pro-
cesses (see, e.g., Barry, Morrison, & Ellis, 1997; Brown
& Watson, 1987; Carroll & White, 1973; Gilhooly &
Logie, 1980). For example, the effect of age of acquisi-
tion on word recognition speed has been demonstrated
(for lexical decision tasks, see, e.g., Brysbaert, Lange,
& Van Wijnen daele, 2000; Pérez, 2004). This effect has
also been shown on other tasks, such as picture naming
(e.g., Ellis & Morrison, 1998) and word naming (e.g.,
Coltheart, Laxon, & Keating, 1988). It seems that the
nature of these different tasks influences the size of the
age-of-acquisition effect. This effect has been larger in
tasks such as picture naming, which involves an arbitrary
mapping between picture and phonology, than in tasks
such as word naming, which involves a quasiconsistent
mapping between orthography and phonology and where
it is possible to use what was learned first in later learned
words (Lambon-Ralph & Ehsan, 2006; Zevin & Seiden-
berg, 2002, 2004). Although some authors have argued
that it is more parsimonious to explain the effect of the
age of acquisition as being one of accumulated fre-
quency, others provide evidence that it is an independent
and strong variable (for a revision, see Juhasz, 2005).
Because of its controversial status, age of acquisition is
a relevant index of printed words for researchers.
Age of acquisition has been estimated using subjective
methods, such as adult subjective judgments (e.g., Carroll
& White, 1973; Gilhooly & Hay, 1977; Gilhooly & Logie,
1980; Lyons, Teer, & Rubenstein, 1978; Rubin, 1980).
However, objective measures, such as objective records
of oral production in children, are more accurate (for ob-
jective measures in Spanish and English, respectively, see,
e.g., Álvarez & Cuetos, 2007, and Morrison, Chappell,
Finally, although the majority of the words had an entry
in the RAE dictionary, some nonsense words were also
included, as were misspellings that did not meet this con-
dition. These are not the results of typing or scanning er-
rors in the input; those were carefully edited out. These
nonwords and misspellings resulted instead from several
other sources, such as improperly written onomatopoeias
(e.g., toc, instead of tac), expressions from the children’s
colloquial language itself (e.g., michín, yupi), and incor-
rectly written interjections (i.e., hmm, instead of hum). In
the latter case, the errors were corrected if they consisted
of repetitions and not of substitutions (e.g., ayyy, instead
of ay). We did not eliminate these nonsense words and
misspellings from the database because, although they
have no meaning, they form a part of the written material
directed toward children.
Description of the File
The LEXIN database and the associated program
can be downloaded by anonymous file transfer (http://
Our database includes 13,184 words. Each word is fol-
lowed by 10 columns corresponding to the 10 indexes
described below. The frequency indexes were computed
following the methods first described by Carroll et al.
(1971) and more recently by Breland (1996) and Lété
et al. (2004).
Frequency (F) is the number of occurrences of each
word. Dispersion (D) is the dispersion or distribution of
the frequency of each word, across readers. D ranges from
.00 to 1.00 and is equal to .00 when all occurrences of
the word are found in a single reader, regardless of the
frequency. D is equal to 1.00 if the frequencies are dis-
tributed in exactly equal proportions across readers. The
formula for calculating D is
D log(Åpi) [( pi log pi) / Åpi] / log(n),
where n is the number of readers in the corpus, i is the
reader number (1, 2, . . . , n), and pi is the frequency of a
word in the ith reader, with pi log pi 0, if pi 0.
Frequency per million (U) is the estimated frequency of
each word per million words adjusted for D. When D 1,
U is computed simply as the frequency per million words.
But when D 1, the value of U is adjusted downward.
When D 0, U has a minimum value that is based on
the average weighted probability of the word’s occurrence
across all of the readers. The adjustment is made using the
following formula:
U (1,000,000/N) [FD (1D) * fmin],
where N is the total number of words in the corpus
(13,184), F is the frequency of the word in the corpus,
D is the index of dispersion, and fmin is 1/N times the sum
of the products of fi and si, fi is the frequency in Reader i,
and si is the number of words in that reader.
Standard frequency index (SFI) is derived directly from
U. As Lété et al. (2004) pointed out, the user should find
this index to be a simple and convenient way of indicat-
ing frequency counts. Thus, for example, a value that can
serve as a reference when using this index is the SFI of 40,
sample is reasonably representative of printed Spanish
materials for kindergarten and first-grade children.
Frequency Count Computation
We manually copied into a computer all the text data
from the readers described above and proofread them. In
this process, a word form was considered to be the let-
ters between two blank spaces. Words separated by a dash
were included in the database as one entry. The titles of
the readers, the names of the authors, and all numerals
were omitted.
Next, two computer programs were used. The first one
was used to count the frequency of each word in each
reader. The second one was used to assign the frequency
from the other three Spanish frequency dictionaries to
each word and to tag the words for grammatical category.
The categories into which the words were classified were
taken from the LEXESP dictionary (Sebastián-Gallés
et al., 2000): abbreviations, adjectives, adverbs, articles,
conjunctions, determiners, interjections, nouns, numer-
als (cardinal and ordinal numerals, not Arabic numerals),
prepositions, pronouns, residuals, and verbs.
Finally, two people carried out an extensive editing of
the input files manually. Any printing or spelling errors in
the words were corrected using the electronic consultation
system of the Web page of the Real Academia Española
(RAE, 2001). To facilitate the recording (computation) of
those words that involved some difficulty, the following
criteria were adopted.
. We converted uppercase letters to lowercase,
even in the case of proper nouns.
Individual letters and syllables
. We included the
names of all the letters in the alphabet, both vowels and
consonants, except w, since its name is a compound word.
However, we eliminated the nonsense syllables designed
to show letter associations (e.g., ba, dro).
. We respected the slang that appeared in the chil-
dren’s books, such as “enfadao” (enfadado), as well as the
shortened forms, such as “profe” ( profesor) and “tele”
Diminutives and augmentatives
. On the basis of
the suffixes and prefixes included in the RAE diction-
ary, we included all those words that indicate diminu-
tive and augmentative conditions (e.g., quesito, gatazo,
Invented or fictional feminine or masculine words
Words were included that were formed according to the
usual rules for forming the masculine and feminine, even
when they did not have an entry in the RAE dictionary
(e.g., azafato).
Prefixes and suffixes
. All the prefixes and suffixes
that accompany a word (e.g., desilusión, cucharada) were
included, and those that appeared alone ( pre-, -dad) were
excluded. All the words that were properly formed by
a prefix or suffix were included, even if they were not
known words (superpollo).
Foreign words
. We respected the words coming from
other languages, regardless of whether they had an entry
or a hispanicized version in the RAE dictionary (e.g.,
walkman, anorak).
contains the different operations the user can perform with
the application: new list (to include a new list of words in
the database that can later be consulted), search (to per-
form searches using different criteria from the Word lists
already included in the database), and exit (to stop running
the program). (2) By means of the language option, the user
can select the language with which to work in the applica-
tion. The user can choose from among Spanish, English, or
Basque. The separate Help Word file contains the necessary
instructions for exploring these options.
Hardware Specifications
The program will run on any IBM-compatible (Pen-
tium) computer with any operating system (e.g., Win-
dows, Red Hat, OS/2). The program itself amounts to ap-
proximately 3.3 MB, and the LEXIN database amounts to
approximately 6.4 MB.
Descriptive Statistics
LEXIN contains 93,514 characters divided into 13,184
different words (types) and 178,839 occurrences of these
words (tokens). From the total, 6,912 words are included
in readers recommended for kindergarten (but not exclu-
sively kindergarten) children, and 6,276 words are included
in readers for first graders. Like other databases in other
languages with counts based on word forms (e.g., Carroll
et al., 1971; Stuart et al., 2003), the most obvious character-
istic is the bias toward the lower frequencies. Thus, the 100
most frequently occurring words (less than 1%) account
for 44.53% of all tokens. The 500 most frequently occur-
ring words (3.79%) account for 61.77% of all tokens. The
fact that such a reduced number of words makes up a large
part of the total frequency shows an irregular distribution
of frequencies in the set of words. Furthermore, the propor-
tion of hapax (one occurrence) words in this database—
almost a third of the words (3,644 words, 27.6%)—is also
a reflection of this lack of balance. This proportion is not
as large as that of the majority of the corpora, where hapax
words usually represent 50% of the total corpus (e.g., Car-
roll et al., 1971; Stuart et al., 2003). Moreover, 71% of the
words have low frequencies (below 5 occurrences). This
high percentage of low-frequency words in readers for be-
ginners can represent a problem that was previously pointed
out by Stuart et al.—that is, that children do not see some
words repeated enough times to be able to learn them.
The most frequent grammatical categories in LEXIN
are nouns (46.09%), verbs (33.06%), and adjectives
(18.39%); the less frequent grammatical categories are
interjections (0.02%), pronouns (0.15%), and conjunc-
tions (0.2%). However, when lexical frequency is taken
into account, our database confirms that the most fre-
quent words in the early reading vocabulary are the func-
tion words (i.e., articles, prepositions, adverbs, pronouns),
rather than the content words, just as occurs in children’s
early reading vocabulary in English (Stuart et al., 2003).
Table 1 shows the syntactic category of the 100 most
frequent words in the database, of which function words
alone account for 39.11%. Nevertheless, just as in the En-
glish database (Stuart et al., 2003), as the frequency token
decreases, there is an increase in the percentage of content
which corresponds to the value for a word that occurs once
in a million words. Other values that can be of practical
use are an SFI of 70, which corresponds to words that can
be expected to occur once in every 1,000 words, and an
SFI of 90, which corresponds to words that are expected
to occur once in every 10 words, and so forth. The SFI is
computed from U by using the formula
SFI 10 * [log10(U) 4].
Taking, for example, the words leer and bayas, it is pos-
sible to see the use of the indexes described above. Both
of the words have the same frequency (48), but they have
different D values (.57 and .04, respectively). Their re-
spective estimated frequencies per million are 13,152 and
2,262. Consequently, the SFI values are 81.19 and 73.54,
N letters is the number of letters in each word. Structure
is the syllabic structure of each word. We used a syllabi-
cation algorithm that followed the rules for syllabicating
Spanish language words, as stated by the RAE (1999).
LEXESP is the frequency of each word in the LEXESP
database (Sebastián-Gallés et al., 2000). LEXESP is a fre-
quency database that is based on a count of approximately
5 million Spanish words and includes indexes such as
number of syllables, stress location, pronunciation, im-
ageability, concreteness, and familiarity, among others.
A&C is the frequency of each word in Alameda and
Cuetos’s (1995) database. Alameda and Cuetos’s fre-
quency dictionary is based on a count of approximately
2 million Spanish words.
M&G is the frequency of each word in Martínez and
García’s (2004) database. Martínez and García’s frequency
dictionary has a total of approximately 100,000 words se-
lected from the books that a small group of children from
6 to 12 years of age read during the year.
Category refers to the syntactic categories that have been
included in the database—namely, abbreviations, adjec-
tives, adverbs, articles, conjunctions, determiners, interjec-
tions, nouns, numerals (cardinal and ordinal numerals, not
Arabic numerals), prepositions, pronouns, residuals, and
verbs. In turn, we included syntactic subcategories whose
attributes varied according to the syntactic category to
which they referred. Both the categories and the subcatego-
ries were taken from the LEXESP database.
Grade refers to the school grade (kindergarten or first
grade) in which it is probable that children will encounter
the word for the first time, according to the publishers’
suggested use for the readers. Note that it is only a recom-
mended use and that, in fact, several readers are intended
for use by both kindergartners and first graders.
Description of the Program
The LEXIN program was written in Java. It is a multi-
platform program with a .jar file for every platform and an
.exe file for the Windows platform. It is menu driven for
all options, which makes it easy for novices to use. Help
is available in a separate Word file. The Help file covers
the running of the program.
When starting to use the database, the user has to choose
from a menu containing two options. (1) The archive option
word frequency count in beginning readers is clear for
several reasons. Frequency dictionaries for children will
make it possible to control the frequency of words, which,
as stated earlier, is one of the most influential character-
istics on several tasks related to visual and oral language
processing research. Consequently, this information is
very useful in developmental reading research. Another
important use of dictionaries for children is in the fields
of applied and educational assessment and teaching. Chil-
dren’s frequency dictionaries can guide the selection and
sequencing of target language features for language as-
sessment and teaching/instruction. A third important use
is the possible application of this database for adult read-
ing research that aims to employ printed words with a very
early age of acquisition. Thus, the LEXIN database can be
a useful tool for linguistic and psycholinguistic research,
as well as for teachers and other education professionals.
The development of a software program to expedite the
creation of word lists discussed in this study would have
a huge beneficial impact on the use of LEXIN, both in
research and in professional settings.
One limitation of the present database is that the useful-
ness of the results and their possible generalization might
words, until they come to represent 99% of the last 100
words of the first thousand.
With regard to the length of the words in the beginning
reading vocabulary, approximately 75% of the words have
between 5 and 9 letters, with a mean length of 7.09 let-
ters per word (SD 2.16). Less than 10% of the words
have 4 letters or less, and only 2.7% have 3 letters or less,
unlike other languages, like English, with shorter words
and a greater number of monosyllables (Fenk-Oczlon &
Fenk, 2008).
Another characteristic of the Spanish beginning vocab-
ulary is the variety of syllabic structures. Evidence of this
lies in the seven different syllabic structures observed in
the 100 most frequent monosyllables. These are listed in
order of frequency in Table 2. As Table 2 also shows, the
most common structures are the CVC and CV syllables,
as is the case in English (Stuart et al., 2003), followed by
CVV and then VC structures.
There are no previous word dictionaries that have mea-
sured the frequency of words in beginning reader materi-
als in Spanish. However, the importance of the printed-
Table 1
Syntactic Categories of the 100 Most Frequent Words in the LEXIN Database
Category N Items Classification
Definite article 5 la, el, los, las, lo Function
Indefinite article 2 un, una Function
Conjunctions 5 y, cuando, pero, o, porque Function
Determiners – Function
Prepositions 9 de, a, en, para, por, sin, si, hasta, con Function
Pronouns 12 que, se, le, qué, me, yo, te, nos, ese, les, esta, quién Function
Adverbs 10 no, muy, más, como, ya, cómo, sí, así, también, después Function
Verbs 23 es, tiene, está, escribe, ha, son, hay, lee, era, soy, hace, dijo,
va, había, estaba, da, dice, rodea, tengo, colorea, lleva,
hacer, están
Contractions 2 al, del Function
Interjections – Function
Nouns 20 casa, mamá, día, papá, sol, luna, gato, agua, bien, monstruo,
abuelo, niño, palabra, niños, nombre, perro, mar, niña,
animales, mesa
Proper noun 1 Ana Content
Adjectives 11 su, mi, sus, dos, todos, completa, todo, mucho, tu, cada, tres Content
Note—Many words in this table have multiple classifications, with the possibility of being classified into
two or more categories (e.g., “bien” can be a noun, conjunction, or adverb). Here, we chose the first clas-
sification given by RAE.
Table 2
Syllabic Structure of the 100 Most Frequent Monosyllables,
in Descending Order of Frequency of the Structure
Structure Items Total
CVC los, las, con, del, por, muy, sus, más, tos, son, hay, nos, sol, soy, sin,
les, mar, tan, ves, hoy, ver, han, ser, rey, van, pan, mis, voy, luz, sal,
has, mal, tor, dar, pez, ven, don, tus, fin, vos
CV la, de, se, no, su, le, me, lo, mi, yo, ha, te, si, ya, va, sí, tu, da, tú, ni,
he, mí, ve, sé, ti, mu, ja
CVV que, qué, lee, día, fue, río, veo, dio, pie, pío, tía, tío, vio, feo, zoo, ría 16
VC el, en, un, es, al, él, ir, ay, os 9
CCVC tres, flor, tren, gran, flan 5
V a, o 2
C y 1
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List of the Readers in the LEXIN Corpus
Title Grade Publisher
1. Lectoescritura 1 Kindergarten Algaida
2. Lectoescritura 2 Kindergarten Algaida
3. Lectoescritura 3 Kindergarten Algaida
4. Lectoescritura 4 Kindergarten Algaida
5. Lectoescritura 5 Kindergarten Algaida
6. Lectoescritura. Pecosete y Pecoseta. Consonantes 1 Kindergarten Algaida
7. Lectoescritura. Pecosete y Pecoseta. Consonantes 2 Kindergarten Algaida
8. Lectoescritura. Pecosete y Pecoseta. Consonantes 3 Kindergarten Algaida
9. Lectoescritura. Pecosete y Pecoseta. Consonantes 4 Kindergarten Algaida
10. 1ª Cartilla. Nuevo Palau Kindergarten Anaya
11. 2ª Cartilla. Nuevo Palau Kindergarten Anaya
12. 3ª Cartilla. Nuevo Palau Kindergarten Anaya
13. Proyecto siete colores: Aprendo a leer Kindergarten Anaya
14. Poquito a poco Kindergarten Anaya
15. Empiezo a leer Kindergarten Anaya
16. Toc, Toc, ábreme. Lecturas First grade Anaya
17. Lecturas 1. Ventana de colores First grade Anaya
18. Poquito a poco. Cuaderno 1 First grade Anaya
19. Poquito a poco. Cuaderno 2 First grade Anaya
20. Poquito a poco. Cuaderno 3 First grade Anaya
21. Micho 1 Kindergarten Bruño
22. Micho 2 Kindergarten Bruño
23. Colección BEABÁ/1. 1 Kindergarten Casals
24. Colección BEABÁ/1. 2 Kindergarten Casals
25. Colección BEABÁ/1. 3 Kindergarten Casals
26. Colección BEABÁ/1. 4 Kindergarten Casals
27. Colección BEABÁ/1. 5 Kindergarten Casals
28. Colección BEABÁ/2. 1 Kindergarten Casals
29. Colección BEABÁ/2. 2 Kindergarten Casals
30. Colección BEABÁ/2. 3 Kindergarten Casals
31. Colección BEABÁ/2. 4 Kindergarten Casals
32. Colección BEABÁ/2. 5 Kindergarten Casals
33. Colección BEABÁ/2. 6 Kindergarten Casals
34. Colección BEABÁ/2. 7 Kindergarten Casals
35. Colección BEABÁ/2. 8 Kindergarten Casals
36. Colección BEABÁ/2. 9 Kindergarten Casals
37. Colección BEABÁ/2. Lecturas. Tor y Tuga Kindergarten Casals
38. Casals. Libro de lengua. 1º First grade Casals
39. Casals. Cuaderno de actividades 0. 1º First grade Casals
40. Casals. Cuaderno de actividades 1. 1º First grade Casals
41. Casals. Cuaderno de actividades 2. 1º First grade Casals
42. Casals. Cuaderno de actividades 3. 1º First grade Casals
43. Casals. Cuaderno de enlace 1. 1º First grade Casals
44. Casals. Cuaderno de enlace 2. 1º First grade Casals
45. Proyecto Cosquillas. Lectoescritura. Cuadernos 1–10 Kindergarten Edebé
46. Lengua y Literatura 1 First grade Edebé
47. Cuaderno de Lengua 1 First grade Edebé
48. Cuaderno de Lengua 2 First grade Edebé
49. Cuaderno de Lengua 3 First grade Edebé
50. Érase una vez el país de las letras 1 Kindergarten Edelvives
51. Érase una vez el país de las letras 2 Kindergarten Edelvives
52. Érase una vez el país de las letras 3 Kindergarten Edelvives
53. Érase una vez el país de las letras 4 Kindergarten Edelvives
54. Lengua 1º First grade Edelvives
55. Imaginario Lecturas 1º First grade Edelvives
56. Cuaderno de actividades 1º First grade Edelvives
57. Proyecto Ágora. Lengua First grade Everest
58. Proyecto Ágora. Cuadernillo de evaluación First grade Everest
59. Proyecto Ágora. Cuadernillo de refuerzo y ampliación First grade Everest
60. Proyecto Luna. Cuadernillo 1. Primer trimestre Kindergarten Everest
61. Proyecto Luna. Cuadernillo 2. Segundo trimestre Kindergarten Everest
62. Proyecto Luna. Cuadernillo 3. Tercer trimestre Kindergarten Everest
63. Proyecto Fantasía. Cuadernillo 1. Primer trimestre Kindergarten Everest
64. Proyecto Fantasía. Cuadernillo 2. Segundo trimestre Kindergarten Everest
65. Proyecto Fantasía. Cuadernillo 3. Tercer trimestre Kindergarten Everest
66. Proyecto Nuevo Flopi. Cuadernillo 1. Primer trimestre Kindergarten Everest
67. Proyecto Nuevo Flopi. Cuadernillo 2. Segundo trimestre Kindergarten Everest
68. Proyecto Nuevo Flopi. Cuadernillo 3. Tercer trimestre Kindergarten Everest
69. 1ª Cartilla Kindergarten Lamela
70. 2ª Cartilla Kindergarten Lamela
71. 3ª Cartilla Kindergarten Lamela
72. Escritura cuaderno 1. Nivel 1 Kindergarten Santillana
73. Escritura cuaderno 2. Nivel 1 Kindergarten Santillana
74. Escritura cuaderno 1. Nivel 2 Kindergarten Santillana
75. Escritura cuaderno 2. Nivel 2 Kindergarten Santillana
76. Lectura 1 Kindergarten Santillana
77. Lectura 2 Kindergarten Santillana
78. Chinchirimbola nº 1 Kindergarten Santillana
79. Chinchirimbola nº 2 Kindergarten Santillana
80. Chinchirimbola nº 3 Kindergarten Santillana
81. Chinchirimbola nº 4 Kindergarten Santillana
82. Cuentos de la luna lunera First grade Santillana
83. Luna Lunera. Nº 1 First grade Santillana
84. Luna Lunera. Nº 2 First grade Santillana
85. Luna Lunera. Nº 3 First grade Santillana
86. Luna Lunera. Nº 4 First grade Santillana
87. Luna Lunera. Nº 5 First grade Santillana
88. Luna Lunera. Nº 6 First grade Santillana
89. Luna Lunera. Nº 7 First grade Santillana
90. Luna Lunera. Nº 8 First grade Santillana
91. Luna Lunera. Nº 9 First grade Santillana
92. Luna Lunera. Nº 10 First grade Santillana
93. Luna Lunera. Cuaderno de escritura nivel 1 First grade Santillana
94. Luna Lunera. Cuaderno de escritura nivel 2 First grade Santillana
APPENDIX (Continued)
Title Grade Publisher
95. Lengua Castellana. Nuestro mundo. La granja First grade Santillana
96. Lengua Castellana. El bosque de los cuentos First grade Santillana
97. Cuaderno de lengua castellana. Fichas de lectura.1er trimestre First grade Santillana
98. Cuaderno de lengua castellana. Fichas de lectura. 2º trimestre First grade Santillana
99. Cuaderno de lengua castellana. Fichas de lectura. 3er trimestre First grade Santillana
100. Cuaderno de lengua castellana. Fichas de escritura. 1er trimestre First grade Santillana
101. Cuaderno de lengua castellana. Fichas de escritura. 2º trimestre First grade Santillana
102. Cuaderno de lengua castellana. Fichas de escritura. 3er trimestre First grade Santillana
103. Lecturas amigas. En marcha First grade Santillana
104. Lecturas amigas. Primeros pasos First grade Santillana
105. La cartilla First grade Santillana
106. Letras encantadas. Lectoescritura Kindergarten Santillana
107. Letras encantadas. Lectoescritura 1 Kindergarten Santillana
108. Letras encantadas. Lectoescritura 2 Kindergarten Santillana
109. Letras encantadas. Lectoescritura 3 Kindergarten Santillana
110. Letras encantadas. Lectoescritura 4 Kindergarten Santillana
111. Letras encantadas. Lectoescritura 5 Kindergarten Santillana
112. Letras encantadas. Lectoescritura 6 Kindergarten Santillana
113. Ven a leer 1 Kindergarten Siglo XXI
114. Ven a leer 2 Kindergarten Siglo XXI
115. Ven a leer 3 Kindergarten Siglo XXI
116. Iniciación a la lectura 1 Kindergarten SM
117. Iniciación a la lectura 2 Kindergarten SM
118. Iniciación a la escritura 1 Kindergarten SM
119. Iniciación a la escritura 2 Kindergarten SM
120. Proyecto Duendes. Lecturas 1 First grade SM
121. Proyecto Duendes. 1er Trimestre First grade SM
122. Proyecto Duendes. 2º Trimestre First grade SM
123. Proyecto Duendes. 3er Trimestre First grade SM
124. Proyecto Duendes. El álbum de las palabras First grade SM
125. Proyecto Duendes. Cuaderno de lengua 1er trimestre First grade SM
126. Proyecto Duendes. Cuaderno de lengua 2º trimestre First grade SM
127. Proyecto Duendes. Cuaderno de lengua 3er trimestre First grade SM
128. Proyecto Papelo. Lengua 1er curso First grade SM
129. Proyecto Papelo. Escribir 1 First grade SM
130. Proyecto Papelo. Escribir 2 First grade SM
131. Proyecto Papelo. Lecturas First grade SM
132. Vamos a jugar 1 Kindergarten Vicens vives
133. Leo y escribo First grade Vicens vives
134. Vamos a leer 1 Kindergarten Vicens vives
(Manuscript received December 10, 2008;
revision accepted for publication May 14, 2009.)
Appendix (Continued)
Title Grade Publisher
... Uma vantagem adicional do uso de legendasé a possibilidade de se ajustar o córpus para finalidades específicas a partir de filtros, por exemplo, estudos com crianc¸as de diferentes faixas etárias e escolaridades. O objetivo das bases lexicais infantisé ofe recer uma ferramenta sensível para estudos psicolinguísticos e de desenvolvimento com controle das variáveis psicolinguísticas para cada faixa etária [Corral et al. 2009]. Para tais propósitos, o uso de córpus baseado em textos escritos que somente a populac¸ão adulta está exposta tem recebido críticas, pois as variáveis psicolinguísticas, tais como frequência das palavras, tendem a não refletir a realidade linguística do mundo infantil, uma tendência observada nos córpus já existentes. ...
... Lexin [Corral et al. 2009]é uma base de vocabulário infantil do Espanhol composta por 134 livros destinados a estimular a leitura e a escrita em crianc¸as na pŕ eescola (76 livros) e no primeiro ano do ensino fundamental (58 livros). A base contém 13.184 palavras (types) e 178.839 tokens. ...
Conference Paper
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Corpus de palavras têm sido largamente utilizados na seleção de estímulos em experimentos psicolinguísticos, pesquisas em lexicologia, dentre outros usos. A frequência de palavras é um importante proxy em pesquisas psicolinguísticas, pois prevê com boa precisão os tempos de reação para o reconhecimento de palavras. Este artigo apresenta o primeiro dos três corpus do projeto LexPorBR-Infantil: legendas de filmes e séries de comédia, família e animações em português brasileiro ouvidos por crianças. Este trabalho disponibiliza publicamente um léxico de 130 milhões de tokens e 880 mil types, disponibilizando 48 categorias de informações para pesquisas em psicolinguística, análise de corpus e aplicadas à educação.
... It contains two lists of 12 pairs of words, half were "yes" pairs, sharing the same initial syllable (e.g., mano-mapa) or phoneme (e.g., mesa-moto), and the other half were "no" pairs, sharing no phoneme at all (e.g., seta-mono). All the words were chosen from LEXIN, the printed vocabulary for beginning readers (Corral, Ferrero, & Goikoetxea, 2009) and were represented by a normalized drawing. Instructions were the following: "Here we have two drawings. ...
... On this task the child read aloud 40 frequent words with a two to four syllable simple V or CV structure (e.g., tomate). All the words were chosen from LEXIN (Corral et al., 2009). Instructions given to the child were the same as the PROLEC-R word-reading subtest "Read these words aloud." ...
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We investigated the longitudinal predictors of reading and spelling of words and pseudowords with different syllabic structures in a shallow orthography. Participants were 47 Spanish-speaking children from kindergarten to second grade. Letter knowledge, phonological awareness, and rapid automatized naming were evaluated at the beginning and at the end of the school year, and reading and spelling skills were assessed at the beginning of the following year. Hierarchical multiple regression analysis revealed that letter knowledge was the strongest predictor of reading and spelling words and pseudowords with simple syllables after 6 and 12 months. Phonological awareness predicted reading and spelling stimuli with complex syllables. Mediation analysis confirmed the mediator role of phonological awareness in the relationship between letter knowledge and reading and spelling with complex syllabic stimuli. This research provides longitudinal evidence that the syllabic structure determines the role of letter knowledge and phonological awareness in reading and spelling skills in Spanish. Understanding the knowledge that is key to learning to read and write may lead to improving methods and materials for literacy in Spanish language.
... For this purpose, an algorithm including a seq2seq transformer was used, which was specifically designed to map phonetic coding of words to their graphemic representation. The input to the transformer consisted of a list of 13,184 frequent Spanish words in children's books (Corral et al., 2009), with the syllabic structure and psycholinguistic properties obtained from ESPAL (Duchon et al., 2013). As a result, an ordered sequence of letters was obtained for Spanish, based on the consistency of the grapheme to phoneme mappings, from simpler to more complex ones (Potier Watkins et al., 2019), coupled with words and phrases that can be used for practice. ...
We present three studies where the cognitive science of early mathematics and reading was used to design digital applications aimed at impacting education. We argue that this is especially urgent in low-income countries and show that the peculiarities of non-WEIRD (Western, educated, industrialized, rich, and democratic) countries should be called into the picture. First, interventions geared at low-income populations in mathematical cognition can be impactful, at variance with some current theories of mathematical cognition. Also, we show that reading in Spanish, an orthography underrepresented in research, differs from what is observed in less transparent (but hegemonic) orthographies like English. Lastly, we show that an intervention directed at early reading instruction needs to consider the task in the social milieu where it takes place, as other agents, who are also trying to promote change in education, produce complex interactions that obscure the interpretation of results.KeywordsReadingMath Technology Non-WEIRD Education
... The words to be learned, referred to as experimental words, were the same as in the Rosa et al. (2017) experiment: 12 words in Spanish (average length: 7.5 letters, range: 6-11), of which 11 were nouns and one was an adjective. These words did not occur in the LEXIN primary school lexical database in Spanish (Corral et al., 2009) and had a very low frequency of use (mean = 0.15, range 0-0.9) in the EsPal Spanish subtitle database (the average was less than 0.2 per million) (Duchon et al., 2013). We also checked that none of these words were known by children of this agethis was verified by presenting these words to a different sample of 53 children. ...
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Recent studies have revealed that presenting novel words across various contexts (i.e., contextual diversity) helps to consolidate the meaning of these words both in adults and children. This effect has been typically explained in terms of semantic distinctiveness (e.g., Semantic Distinctiveness Model, Jones et al., Canadian Journal of Experimental Psychology , 66 (2), 115, 2012). However, the relative influence of other, non-semantic, elements of the context is still unclear. In this study, we examined whether incidental learning of new words in children was facilitated when the words were uttered by several individuals rather than when they were uttered by the same individual. In the learning phase, the to-be-learned words were presented through audible fables recorded either by the same voice (low diversity) or by different voices (high diversity). Subsequently, word learning was assessed through two orthographic and semantic integration tasks. Results showed that words uttered by different voices were learned better than those uttered by the same voice. Thus, the benefits of contextual diversity in word learning extend beyond semantic differences among contexts; they also benefit from perceptual differences among contexts.
... This is particularly relevant now that a large number of studies involving children use computerised and online processing tasks (e.g., fMRI, MEG) to investigate developmental language differences. Childspecific databases have been developed for various languages, for example the Educator's Word Frequency Count for American English (Zeno, et al., 1995), the Children Word Printed Database for British English (Masterson, Stuart, Dixon, & Lovejoy, 2010), MANULEX for French (Lété, Sprenger-Charolles, & Colé, 2004), LEXIN for Spanish (Corral, Ferrero, & Goikoetxea, 2009) and ESCOLEX for Portuguese (Soares et al., 2014). ...
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Undertaking a research visit to a different institution provides an excellent opportunity for PhD students to get in touch with new perspectives and research environments. Yet fitting a research visit within doctoral studies may seem like a daunting task, which requires much organisation and planning. This article will focus on why and when students should spend part of their PhD visiting another institution, and give a few practical tips on how to arrange and make the most of this experience. (Psychology Postgraduate Affairs Group Quarterly, 100:45-47)
... The four alternate forms of the LEO-1-min, each with 180 stimuli, were randomly drawn from a pool of 528 most frequent nouns (excluding names and colloquialisms; 32 words of one syllable, 279 of two syllables, 166 of three syllables, 43 of four syllables, and 8 of five syllables) selected from the vocabulary of LEXIN (Corral, Ferrero, & Goikoetxea, 2009). The list of 528 words was used to create the pseudowords by substituting interior letters according to the length of the words. ...
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Introduction: Teachers and researchers often need to evaluate word decoding skill in group-wise and in a short time. The LEO-1-min test is created to measure word reading through a lexical decision procedure where the examinee identifies pseudowords in a list of frequent words. Objective: To examine the reliability and validity of LEO-1-min, a silent word reading test, suitable for quick assess of reading abilities in a wide age range of students. Method: Participants were 284 children from 1st to 6th grade of a subsidized Primary School. We created four alternate forms of the LEO-1-min, each with 180 stimuli (132 words and 48 pseudowords). Results: The results show an adequate parallel forms reliability of the scores (range rs = from 0.57 to 0.81). High correlations were found between the scores on the LEO-1-min and the scores on a standardized reading aloud test. The discriminant analysis of the scores on the LEO–1-min shows a high level of success in predicting the oral word decoding performance. Discussion and Conclusion: LEO-1-min reliability is acceptable to good. Lexical decision in LEO-1-min and oral reading are highly correlated, which support using lexical decision as a groupwise test to screen for poor word readers. Form A of the test and provisional scales are presented for each primary grade.
This thesis focuses on the application, to French students, of advances in the understanding of how children learn to read, what methods best train literacy and how we can better assess reading deficits-so that these advances can fuel a virtuous circle between cognitive science and educational interventions.
Recent research has shown the benefits of high contextual diversity, defined as the number of different contexts in which a word appears, when incidentally learning new words. These benefits have been found both in laboratory settings and in ecological settings such as the classroom during regular hours. To examine the nature of this effect in young readers aged 11–13 years, we analyzed whether these benefits are modulated by the individuals’ reading comprehension scores; that is, would better comprehenders benefit the most from contextual diversity? The manipulation of contextual diversity was done by inserting the novel words into three different contexts/topics, or into only one of them, while keeping constant their frequency of occurrence. Results showed that words encountered in different contexts were learned more effectively than those presented in the same context. More important, the effect of contextual diversity was similar regardless of the participants’ comprehension skills. We discuss the implications of these findings for models of word learning and the practical applications in curriculum design.
The masked priming technique is widely used to explore the early moments of letter and word identification. Although this technique is increasingly used in experiments with young readers, the mechanism in play during masked priming with early readers has not yet been fully explored. We investigated the masked priming effects from a modeling perspective; we instantiated competing theories as data models (using Bayes factors) and as a computational model (diffusion model). We carried out a masked priming experiment using identity primes with second- and fourth-grade participants, and we analyzed the data through an evidence accumulation model lens. The priming effect manifests as a shift in the response time distribution, which in evidence accumulation models is accounted for by changes in the encoding process. We describe such changes as savings that have three features of theoretical importance. First, they are numerically very close to the stimulus onset asynchrony between primes and targets. Second, they remain relatively constant from second grade to fourth grade. Third, they seem to operate at the level of abstract orthographic representation because the priming effect occurs in both case-matched and case-mismatched pairs. These findings also have consequences for the practice of data transformation in developmental research; some patterns of data, when transformed, would produce spurious effects.
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Studies of lexical processing have relied heavily on adult ratings of word learning age or age of acquisition, which have been shown to be strongly predictive of processing speed. This study reports a set of objective norms derived in a large-scale study of British children's naming of 297 pictured objects (including 232 from the Snodgrass & Vanderwart, 1980, set). In addition, data were obtained on measures of rated age of acquisition, rated frequency, imageability, object familiarity, picture-name agreement, and name agreement. We discuss the relationship between the objective measure and adult ratings of word learning age. Objective measures should be used when available, but where not, our data suggest that adult ratings provide a reliable and valid measure of real word learning age.
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Starting from a view on language as a combinatorial and hierarchically organized system we assumed that a high syllable complexity favours a high number of syllable types , which in turn favours a high number of monosyllables . Relevant crosslinguistic correlations based on Menzerath's (1954) data on monosyllables in 8 languages turned out to be statistically significant. A further attempt was made to conceptualise "semantic complexity" and to relate it to complexity in phonology, word formation, and word order. In English, for instance, the tendency to phonological complexity and monosyllabism is associated with a tendency to homonymy and polysemy, to rigid word order and idiomatic speech. The results are explained by complexity trade-offs rather between than within the subsystems of language. 1
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Independent measures of age of acquisition (AoA), name agreement, and rated object familiarity were obtained from groups of British subjects for all items in the Snodgrass and Vanderwart (1980) picture set with single names. Word frequency measures, both written and spoken, were taken from the Celex database (Centre for Lexical Information, 1993). The line drawings were presented to a separate groupof participants in an object naming task, and vocal naming latencies were recorded. A subset of 195 items was selected for analysis after excluding items with, for example, low name agreement. The major determinants of picture naming speed were the frequency of the name, the interaction between AoA and frequency, and name agreement. (The main effect of the AoA of the name and the effect of the rated image agreement of the picture were also significant on one-tailed tests.) Spoken name frequency affects object naming times mainly for items with later-acquired names.
This article compares word counts made using four different collections of text, including one based on collections of electronic text. For each of the collections, standard word frequency indices were computed and compared with a carefully developed list of words ranked in order of difficulty as determined by vocabulary tests. Correlations between the word frequency indices and word difficulty ranks show that word frequencies for all four corpora are highly correlated with word difficulty. Despite these high correlations, the results show also that the difficulty of some words is not estimated accurately by word frequency. The reasons for disparities between word frequency and word difficulty are not clear. The high correlations obtained for the corpus based on electronic text suggest that this method of text sampling has potential, hut that caution is advisable in conducting such collections.