Printer Friendly

The Loleva oral and written language test: psychometric properties.

This paper presents a psychometric analysis of the Lenguaje Oral, Lenguaje Escrito: Evaluacion (LolEva) [Oral & Written Language: Assessment] (Mayor, Fernandez, Tunas, Zubiauz, & Duran, 2012; Peralbo, Brenlla, Garcia, Barca, & Mayor, 2012). Taking a psycholinguistic perspective, the test is built on the assumption that an interacting set of regular, continuous processes brings about language comprehension and use, both oral and written. Metalinguistic processes refer to a person's awareness of the component parts of words, which seems to facilitate initial reading acquisition in languages with transparent as well as non-transparent orthographies (Alegria, 2006; Caravolas, Lervag, Defior, Malkova, & Hulme, 2013). Phonological awareness has been defined as consciously knowing that words have several constituent units of sound (Gillam & van Kleecl, 1996), and being able to reflect on and manipulate the subunits of speech: syllables, intrasyllabic units, and phonemes (Anthony et al., 2011; Morais, 1991; Treiman, 1991). Morais (1991) put it thusly:

   Phonological awareness is a special kind of phonological
   knowledge. It differs from the phonological
   knowledge used in comprehending and
   producing language by the fact that it refers
   to conscious representations of the phonological
   properties and constituents of speech. Indeed,
   this definition is a loose one unless we specify
   the criteria by which a phonological representation
   can be said to be conscious. (p. 34)

Not all knowledge can be easily verbalized, so using recognition or free response tasks, for example, is justified. Furthermore, researchers are not in complete agreement about how phonological awareness develops in different languages, and whether the level of PA a person attains in one language can predict his or her PA in a second language.

This study, however, is based on several assumptions with ample empirical support (Alegria, 2006; Brady & Shankweiler, 1991; Defior, 1996; Jimenez & Ortiz, 1995; Stanovich, 2000):

a. In the development of phonological skills, there is a gradual progression beginning with the ability to manipulate words, followed by syllable manipulation, and finally phoneme manipulation.

b. The position within the word of the unit being manipulated has an effect according to which it is harder to manipulate units at the end of the word that at the beginning, at least on certain types of tasks.

c. The type of syllable structure (CV, VC, CCV, etc.) may influence task complexity.

d. Phonological skills can improve with training, even at a very young age.

e. Phonological skills predict successful initial reading acquisition.

f. There is a reciprocal relationship between phonological awareness and reading.

It has been demonstrated that phonological awareness plays a critical role in learning to read (Bryant & Bradley, 1985; Caravolas et al., 2013; Carroll, Snowling, Stevenson, & Hulme, 2003; Marquez & de la Osa, 2003), and PA assessment has become increasingly necessary for professionals who guide and implement clinical and educational interventions. Utilizing standardized tests adapted for Spanish populations, PA assessment has mostly used a paper-and-pencil format. Examples include the Prueba de Segmentacion Linguistica (PSL) [Word Segmentacion Test] (Jimenez & Ortiz; 1995), Batena de Evaluacion de los Procesos Lectores, Revisada (PROLEC-R) [Battery of Reading Processes Tests, Revised] (Cuetos, Rodriguez, Ruano, & Arribas, 2007), and the Test de Analisis de la LectoEscritura (TALE2000) [Test of Reading-Writing Analysis] (Toro, Cervera, & Urio, 2000). Nevertheless, ICT (Information and Communication Technology) is only just beginning to be used in developing computerized instruments, instruments like the LolEva (the subject of the present study), SICOLE-R-PriMaria [SICOLE-R-Primary] (Jimenez et al., 2007), or the Prueba Informatizada de Habilidades Metafonologicas [Computerized Test of Metaphonological Skills] (Carrillo & Marin, 1996). To create this sort of computerized test would help complete the current arsenal of tests for the earliest levels of childhood education, covering a wide time span so that phonological awareness difficulties can be identified at an early age and timely intervention can be applied to facilitate the initial learning-to-read process.

A requirement of any assessment tool is that its psychometric properties guarantee it for use and lend credibility to its results (Muniz,, 1999). In terms of validity, the abundant literature to date has confirmed the LolEva's content validity, and its internal structure has emerged from research results. Jimenez and Ortiz (1995) posit that a person's level of phonological awareness can be established according to task difficulty, which varies depending on the linguistic, analytical, and memory aptitude it demands. Similarly, some authors (Leong, 1991; Morais, 1991) draw a distinction between classification and pairing tasks, and segmentation tasks (which require the production or manipulation of isolated elements), arguing that classification tasks are easier. Adams (1990) has proposed as many as five difficulty levels on tasks that measure phonological awareness. In order of difficulty from lowest to highest, the tasks are the following: i. Remember familiar rhymes; ii. Recognize and classify rhyme and alliteration patterns in words; iii. Blend syllables into words, or split one syllable component from the rest (for example, isolate the first phoneme); iv. Word segmentation into phonemes; v. Add, omit, or reverse phonemes, and identify the resulting word or pseudoword.

In their influential study, Anthony et al. (2011) attributed developmental differences between 3 and 6 years of age to the relative influence of task complexity. In their study, items that included the same cognitive operations (addition and omission), or had the same response format (free response or multiple choice) shared a certain amount of variance regardless of the structural segment of the affected word (word, syllable, or phoneme). According to those authors' data, word structure in Spanish does not seem to impact item difficulty. They posit the following developmental sequence of phonological awareness skills (which they believe are one-dimensional). First, children become able to blend two words to form a new one. Next, they learn to connect syllables and form words on their own. Ultimately, the most developed among them can omit sounds from words to create new words. In their study, multiple-choice addition tasks were easier than free-response addition tasks, which were easier than free-response omission tasks. The same sequence was observed regardless of the structural level of the word analyzed. In other words, good results could be obtained if one assesses level of phonological development by selecting just one word structure (syllable or phoneme), and manipulating only task complexity. In Spanish however, as described above, task difficulty seems to stem from other factors, which the aforementioned study ruled out as discriminant (e.g. the type of segment affected, and its position within the word).

Tasks to evaluate reading processes are based on the psycholinguistic processes they involve: from perceptual, linguistic letter recognition; to dual-route lexical access (direct or phonological); and syntactic and semantic analysis. This series of constituent processes is present in practically every test that measures reading processes, and is a point of reference for the LolEva scale of initial reading competence.

With that in mind, this study's objective is to determine and evaluate the main psychometric properties of the LolEva and its constituent parts, specifically: to determine the reliability of total and partial scores (by subscale and subsample), conduct item analysis, and identify the underlying factor structure and, comparing it to the one used when the instrument was created, take a measure of construct validity.



Participants in this study were 341 students, from the first year in Early Childhood Education (ECE) [Educacion Infantil] to the second year in Primary Education (PE) [Educacion Primaria], from public and state-subsidized schools in A Coruna and Salamanca, Spain. They were all 3 to 8 years old, and both sexes were represented (49.6% girls). No one was repeating a grade. The only exclusion criterion was exhibiting severe developmental alteration that could affect comprehension or task performance, but no such case was found. The children were authorized to participate by their parents through an informed consent procedure.


The computerized LolEva test was employed, designed to identify difficulties in phonological skills development that can lead to problems learning to read. It can be administered to an age range of 3 to 8 years old, and it consists of two subscales: Phonological Awareness (PA) and Initial Reading Competence (IRC). The first is made up of seven tasks with 10 items each: rhyme identification and identification-addition-omission of syllable or phoneme. On half the latter items, the objective syllable or phoneme is positioned at the beginning of the word, and on the other half, it is at the end. The IRC subscale covers six tasks: reading uppercase and lowercase letters (29 items each), reading simple words (simple grapheme-phoneme agreement), reading complex words (complex grapheme-phoneme agreement; e.g. the Spanish word quien), reading pseudowords (10 items each), and splitting sentences into words (laovejadalana [thesheepgiveswool]) (5 items). On both subscales, the number of correct responses is recorded, and on the IRC, the time elapsed before responding correctly is measured as well. All instructions and examples are provided in audiovisual format, as determined in advance (1).


The test was administered on an individual basis in classrooms where participants could complete it with no outside interference. The items were presented on a laptop computer (controlled by the test proctor), starting with two examples. Each respondent had to solve at least one sample question on his or her own before the test could be administered. The test took between 40 and 50 minutes to complete. Data collection was carried out during the second semester of the school year in March, April, and May. The data were analyzed using IBM SPSS Statistics 21.



To ensure the quality of this measure, we first analyzed the reliability of scores on its subscales, obtaining an alpha coefficient of .94 for PA with all 7 tasks taken into account (Rhyme Recognition, Syllable Identification, Phoneme Identification, Syllable Addition, Phoneme Addition, Syllable Omission, Phoneme Omission), and an alpha coefficient of .96 when the parts corresponding to position (beginning vs. end of word) were considered separately. Scores on the IRC subscale, which included six tasks (Reading Uppercase Letters, Lowercase Letters, Simple words, Complex words, Pseudowords, and Word Separation), had an alpha coefficient of .92. Eliminating any particular item from the set did not produce meaningful differences in the coefficients listed above.

PA Subscale Analysis

The following data inspection aimed to analyze the relationship between results on this subscale and the Year in School variable (Table 1), because in the developmental range covered by the test, having completed different years in school implies having developed different skills that have bearing on what the test measures.

First, a one-way analysis of variance was conducted on total scale scores, with results indicating significant differences and effect size showing that Year in School predicted 70% of variability in PA: F(4, 336) = 191.385, p < .001, [[eta].sup.2.sub.p] = .695, 1-[beta] = 1.0. However, given the unequal size of year-in-school subsamples, and the inequality of variance, Levene (4.336) = 11.614, p < .001, and bearing in mind that F is especially vulnerable when those two conditions apply (Howell, 2013), a robust test of equality of means was conducted. Its results, too, suggest significant differences: Welch (4, 157.662) = 554.676, p < .001.

As Table 1 conveys, participants' average number of correct responses increased with year in school. To ascertain which specific differences were important, we used the Games-Howell test for multiple comparisons, which is considered to have greater power (smaller confidence intervals) than other tests in cases of unequal samples or variances, and can also control FWER (Cardinal & Aiken, 2006; Kirk, 2013; Zimmerman, 2004). Our post-hoc comparison revealed that differences did not occur between all years in school; rather, four subsets were identified: one for each level of ECE, and a single homogenous subgroup combining the two levels of PE. In other words, all differences in means turned out to be statistically significant where p < .001, except for the first and second years of PE: difference = -.32, p = .82.

Item Difficulty Indexes (DIs = p-values), too, showed this pattern of similarity and difference between students' results in different years in school. DIs were calculated according to how they are defined within the psychometrics literature: the proportion of people in the sample who answered correctly. It has been said on numerous occasions that it would be more appropriate to refer to this as an item "easiness" index, because the larger it is, the easier the item. With that in mind, this paper will present DIs using quantitative measures as well as the usual qualitative measures from Classical Test Theory.

As Figure 1 shows, for ECE first-years, all the tasks were either difficult (DI in the second quartile, not counting the interval around [Q.sub.50]: .44 > DI [greater than or equal to] .25) or very difficult (DI in the first quartile: DI [less than or equal to] .25), to the point that they only managed to solve the Rhyme Recognition and Syllable Identification tasks. For ECE second-years, however, those last two tasks were easy (DI in the third quartile not counting the interval around [Q.sub.50]: DI [greater than or equal to] .55) and the rest were very difficult (DI in the fourth quartile: DI [greater than or equal to] .75). However, the proportion of students able to solve the tasks rose considerably. For ECE third-years, in contrast, most items were easy, but Rhyme Recognition and Phoneme Omission had medium task difficulty (.54 DI [greater than or equal to] .45). In contrast to the above, first and second-year PE students scarcely differed from one another, although all subtests were very easy for second-years (DI [greater than or equal to]. 75), and that was not the case for first-years.

Regarding item difficulty indexes, we observed that task difficulty generally decreased as year in school progressed, and for all years in school, phoneme-involved tasks were more difficult than syllable-involved tasks.

On another note, the test structure enabled us to construct a within-subjects model to analyze task type (identification/addition/omission), objective type (syllable/phoneme), and objective position (beginning/ end), and how they relate to the year-in-school variable. Repeated measures analysis revealed significant main effects, significant interaction effects (Table 2), and a significant between-subjects effect of the year-in-school variable (academic level): F(1, 4) = 2073.876, p < .001, [[eta].sup.2.sub.p] = .708, 1-[beta] = 1.0.

Furthermore, making multiple comparisons and graphically analyzing student profiles, we observed the following main effects (Figure 2): (1) regarding type of task, identification was easier than Addition and Omission, but their difficulty tended to equalize as year in school progressed; (2) about objetive, syllable-related tasks were easier than phoneme-related tasks at all academic levels; (3) regarding objective position, once the ability to solve these tasks had been generally acquired (starting in the third year of ECE), they were easier if the syllable or phoneme was at the end of the word than if it was at the beginning.

As for the rhyme test, which is purely recognition-based (in the task, neither position nor demand gets manipulated), the only analysis possible was by year in school. In that respect, one-way analysis of variance revealed significant differences, and post-hoc tests yielded the same subgroups as those based on total scores, although the effect size was much smaller in this case: F(1, 4) = 34.370, p < .001, [[eta].sup.2.sub.p] = .29, 1-[beta] = 1.0.

Though difficulty is the most essential component of item analysis for any skills test (Wilson, 2005), item discrimination indexes provide important information by relating each item to the overall test. Corrected item-total correlations (where the item in question's score is not included in the total score) were computed to measure discriminant power, that is, the ability of each task to differentiate adequately among students with different levels of the construct that the test measures. According to Table 3, except in ECE first-years, practically all the tasks' indexes reflected high discriminant power ([greater than or equal to] .40). Phoneme Identification in ECE second-years and Rhyme Recognition in ECE third-years did not meet that standard, but had acceptable results nonetheless (.30 [less than or equal to] .374 [less than or equal to] .39). Conversely, syllable identification had little discriminant power in ECE second-years, and for ECE first-years, discriminant power was low across the board. However, that is not to say the items were not useful in other ways.

Obviously, by employing smaller, more homogenous samples like the subgroups created by year in school, reliability dropped. Results nonetheless indicated good (ECE second-years) or very good (all other years in school) reliability.

IRC Subscale Analysis

The relationship between total scores on this subscale and academic level appears in Table 4.

Here, too, analysis of variance revealed significant differences, both in number of correct answers, which increased as schooling progressed , F(4, 336) = 197.897, p < .001, and Welch (5,107.275) = 410.550, p < .001), and task completion time, which decreased as education progressed, F(4, 335) = 47.048, p < .001, and Welch (4, 130.276) = 59.904, p < .001. The effect size was larger in the first case than in the second ([[eta].sup.2.sub.p] = .702 and [[eta].sup.2.sub.p] = .360, respectively). In both cases, the power of statistical tests reached 1.0.

On the other hand, post hoc tests indicated the proportion of correct answers was about the same in the PE first- and second-year subsamples. The same was true for PA: all differences in means were found to be statistically significant where p < .001, except between PE first- and second-years (difference = -.004, p = 1.00). Likewise, ECE second- and third-years used about the same amount of time to complete tasks: difference between PE first- and second-years = 4.09, p = .48; difference between ECE second- and third-years = 12.37, p = .36.

Differences between tasks remained as school went on, but the magnitude of those differences decreased, and different profiles emerged in terms of correct responses and time used. Grouping tasks according to their required skills, three groups emerge (letter reading, word reading, and word separation). Of those, letter reading got the most correct answers, but participants responded fastest on word reading tasks. The word separation task, on the other hand, had the fewest correct answers and took the longest to solve, indicating it was the most difficult at every academic level. Furthermore, we observed that within these groups, response speed was generally slower on tasks requiring higher accuracy (Figure 3).

Separately analyzing the three task types, significant differences in accuracy as well as speed became apparent (except for letter reading time), but the differences had a very small effect size (Table 5).

With regard to difficulty indexes at different academic levels, Figure 4 shows that ECE first- and second-years only managed to solve letter identification tasks. The subgroups differed in that for first-years, uppercase letter identification was difficult, and lowercase letter identification was very difficult, while for second-years, the first was easy and the second had medium difficulty. At the other end of the spectrum were PE first- and second-years, for whom all the tasks were very easy, although the Word Separation task was borderline for that category in first-years. The most remarkable data occurred in the ECE third-year subsample, who showed a linear progression in the difficulty of different subtests, from very easy to very difficult.

In terms of different tasks' discriminant capacity (Table 6), they all showed high discriminant power ([greater than or equal to] . 40) except Word Separation in ECE third-years. In that case, its discriminant power was acceptable (.30 [less than or equal to] .323 [less than or equal to] .39). Furthermore, reliability measures were very good in all subgroups.


To determine LolEva's construct validity, Exploratory Factor Analysis was conducted, excluding Confirmatory Factor Analysis for now because as other authors have pointed out (Perez-Gil, Chacon, & Moreno, 2000), it would be redundant. Before proceeding with EFA, we confirmed that the following conditions were met: more than half the correlations between variables were above .30, Bartlett's test of sphericity allowed us to reject the null hypothesis that the correlation matrix was an identity matrix, [chi square] (300) = 10371.73, p < .001, and the Kaiser-Meyer-Olkin measure of sampling adequacy (Kaiser, 1974) yielded a value that is considered optimal: KMO = .952.

A principal components extraction procedure was carried out, applying the criterion that components with initial eigenvalues > 1 get extracted. Equamax rotation (reducing the number of variables with high loadings on one factor, and the number of factors needed to explain one variable) was later applied. This yielded three factors, each explaining rather similar proportions of total variance, and together explaining 75.03%. The results appear in Table 7 (loadings below 0.30 were eliminated).

As the table illustrates, the first factor is basically made up of tasks from the PA subscale. Meanwhile, the IRC subscale comprises factors two and three, the latter including time measures on the reading and word splitting tasks. Upper and lowercase letter reading times are part of the second factor, but their factor loadings were negative.


Our analyses have confirmed the test's high reliability, with alpha values of .94 for PA and .92 for IRC, and a factor structure that explains a high percentage of variance (75%). Furthermore, they show that the tasks utilized, and their respective items, have the psychometric properties needed to statistically guarantee the test and its usefulness as a tool in the early detection of learning difficulties. Scores on this test had comparable if not higher reliability than other similar tools with a pencil-and-paper format (the PROLEC-R by Cuetos et al., 2007; the TALE-2000 by Toro et al., 2000; and the PSL by Jimenez & Ortiz, 1995), apart from the age range covered.

On the other hand, results on the PA and IRC subscales (both in terms of accuracy and speed) suggested a distinct growth process in development between the first year of ECE and the beginning of PE. The way writing is introduced, socially and educationally, seems to influence that development.

In fact, while children in their first year of ECE become able to identify rhyme and recognize syllables, they can only identify uppercase (in the learning-to-read process, those are introduced first, so logically, their outcomes are best) and lowercase letters with difficulty. In the second year of ECE, they can to some extent complete PA tasks (except phoneme addition and omission). At that point they can also recognize upper and lowercase letters, like in the year before, but now with ease. Reading words and sentences is still absent at this stage. Thus, it is the level of difficulty posed by letter reading that differentiates these groups from one another.

In the third year of ECE, there is a qualitative and quantitative jump. Students are able to do all the PA tasks, with different levels of difficulty, and easily or very easily read uppercase letters, lowercase letters, and simple words. They can also read pseudowords of medium difficulty, but words with complex graphemephoneme agreement (referred as complex in this paper for the sake of brevity) and splitting sentences into words remain difficult and very difficult for them, respectively. Therefore, during this year in school, lexical access is already possible via both routes--direct or phonological--and they also display the ability to separate words at every level.

Regarding our results pertaining to phonological awareness, the developmental sequence we observed coincides with the levels described in Treiman's (1991) hierarchical model; and the five levels of difficulty Adams (1990) identified on phonological awareness tasks according to linguistic, analytic, and memory demands; and the growing body of data on phonological awareness development (Jimenez & Ortiz, 1995). Conversely, these results only partially support those of Anthony et al. (2013). They were consistent with those authors' findings about the unidimensionality of PA, but not about what elements define task complexity and difficulty. Task complexity seems to play an important role in the development of phonological awareness skills. However, a word's structural complexity, the position and type of segment being manipulated within the word, and response format are all included under the concept of complexity. In this study, PA task complexity or difficulty referred to those two factors interacting in such a way as to impact the expression of a skill that seems to have just one factor. On that point, this study found that skills' different levels of difficulty matched their order of emergence.

Certain differences between our two studies make it challenging to compare them; task type was not entirely consistent. The present research utilized multiple-choice tasks, or similar, to assess rhyme recognition, beginning and ending syllable recognition, and beginning and ending phoneme recognition. In all other cases (omission and addition), free response tasks were employed. The fact that all PA tasks were grouped into a single factor may support the notion of one-dimensionality these authors suggest, but the influence of developmental sequence seems to include additional factors it interacts with reciprocally (working memory and executive functions, processing speed, bilingual context, etc.). The data presented here can be said to reflect that sort of interaction by showing that with age, free recall tasks have the same level of difficulty as recognition tasks (Identification is easier than Addition and Omission but their difficulty/ease tends to equalize as academic level increases); syllable-involved tasks are easier than phoneme-involved tasks at all academic levels; and finally, once respondents can manipulate syllables as well as phonemes (from the third year of ECE on), it is easier when the segment involved--syllable or phoneme--is at the end of the word than when it is at the beginning. Phonological awareness involves knowledge, capacity for manipulation, supervision, and conscious control (like other aspects of metalanguage), and requires interactive feedback from other top-down and bottom-up processes.

The results of this research, therefore, seem to indicate that although phonological awareness has just one factor, it follows one course or another as a function of other variables (cognitive and contextual) that, while independent, favor or hinder its development with age.

ECE first- and second-year students' difficulty manipulating the phoneme segments of words, and thirdyears' ease in doing so, appear to be the result of not only their levels of metaphonological development, but also their capacity to manage other cognitive-type functions (like executive functions and naming speed) that, while independent of PA, have a well established effect on reading acquisition (Caravolas et al., 2013; Mayor et al., 2012; Peralbo et al., 2012). This situation, paired with increasing, more systematic exposure to reading in both school and extracurricular contexts, may explain how ECE third-years could already exhibit the hothouse effect posited by Torgesen and Davis (1996), and Defior (2008), who suggested that "phonological awareness may act like an enzyme that helps establish a more comfortable context for learning written language" (p. 344).

In the present research, the difficulty of reading processes increased much more linearly: uppercase letters, lowercase letters, simple words, pseudowords, complex words, and splitting sentences into words. Furthermore, the more correct responses a student gave, the less reading time they needed. That is essentially consistent with what we know about reading acquisition and the processes it involves (Cuetos, 2008).

This study had two main limitations. The first has to do with the number of participants in the ECE firstyear group. That subsample's size should be increased in order to corroborate these results which, while theoretically consistent, need more complete empirical validation. The second limitation would also require a considerably larger sample size. Given our interest in determining the role of variables related to socialeconomic-cultural context in the level and progression of metalinguistic development (family's level of education, monolingual vs. bilingual context, public or private school, etc.), taking such contextual variables into consideration would help us better understand not only what develops (in which case the psycholinguistic perspective has been predominant), but how it develops (basic knowledge for implementing any educational or clinical approach).

Subsequent studies will allow us to confirm LolEva's underlying factor structure through Confirmatory Factor Analysis, and to ascertain its concurrent, discriminant, and predictive validity. To do so will require, on the one hand, analyses to examine its relationship with other phonological awareness scales (like the ones highlighted in this paper), and on the other, analyses to identify the profile associated with atypical forms of development, whether the result of learning difficulties or more or less severe developmental disorders.

doi: 10.1017/sjp.2015.15


Adams M. J. (1990). Beginning to read: Thinking and learning about print. Cambridge, MA: Bolt.

Alegria J. (2006). Por un enfoque psicolinguistico del aprendizaje de la lectura y sus dificultades -20 anos despues [Support for a psycholinguistic approach to reading acquisition and reading difficulties--20 years later]. Infancia y Aprendizaje, 29, 93-111. http://dx.doi. org/10.1174/021037006775380957

Anthony J. L., Williams J. M., Duran L. K., Gillam S. L., Liang L., Aghara R., ... Landry S. H. (2011). Spanish phonological awareness: Dimensionality and sequence of development during the preschool and kindergarten years. Journal of Educational Psychology, 103, 857-876. http://dx.doi. org/10.1037/a0025024

Brady S. A., & Shankweiler D. R. (Eds.) (1991). Phonological processes in literacy. Hillsdale, NJ: Erlbaum.

Bryant P., & Bradley L. (1985). Childhood reading problems. Oxford, UK: Blackwell.

Cardinal R. N., & Aitken M. R. F. (2006). ANOVA for the behavioural sciences researcher. New Jersey, NJ: Erlbaum.

Caravolas M., Lervag A., Defior S., Malkova G. S., & Hulme C. (2013). Different patterns, but equivalent predictors, of growth in reading in consistent and inconsistent orthographies. Psychological Science, 24, 1398-1407.

Carrillo M. S., & Marin J. (1996). Desarrollo metafonologico y adquisicion de la lectura: Un programa de entrenamiento [Metaphonological development and reading acquisition: A training program]. Madrid, Spain: CIDE.

Carroll J. M., Snowling M. J., Stevenson J., & Hulme C. (2003). The development of phonological awareness in preschool children. Developmental Psychology, 39, 913-923.

Cuetos F. (2008). Psicologia de la lectura [Psychology of reading] (7th Ed.). Madrid, Spain: Kluwer.

Cuetos F., Rodriguez B., Ruano E., & Arribas D. (2007). PROLEC-R: Bateria de evaluacion de los procesos lectores -revisada [Test battery for reading processes assessment -revised]. Madrid, Spain: TEA.

Defior S. (1996). Una clasificacion de las tareas utilizadas en la evaluacion de las habilidades fonologicas y algunas ideas para su mejora [A classification of tasks utilized in phonological skills assessment, and some ideas on how to improve them]. Infancia y Aprendizaje, 19, 49-63. http://

Defior S. (2008). ^Como facilitar el aprendizaje inicial de la lectoescritura? Papel de las habilidades fonologicas [How to facilitate initial literacy acquisition? The role of phonological skills]. Infancia y Aprendizaje, 31, 333-345.

Gillam R., & van Kleeck A. (1996). Phonological awareness training and short-term working memory: Clinical implications. Topics in Language Disorders, 17, 72-81.

Howell D. C. (2013). Statistical methods for psychology (8th Ed.). Belmont, CA: Wadsworth.

Jimenez J. E., & Ortiz M. R. (1995). Conciencia fonologica y aprendizaje de la lectura: Teoria, evaluacion e intervencion [Phonological awareness and reading acquisition: Theory, assessment and intervention]. Madrid, Spain: Sintesis.

Jimenez J. E., Anton L., Diaz A., Guzman M. R., Hernandez-Valle M. I., Ortiz M. R., ... Muneton M. A. (2007). SICOLE-R-PriMaria: Manual de uso e instrucciones para el examinador [SICOLE-R-Basic: Manual and examiner instructions]. Santa Cruz de Tenerife, Spain: Ocide.

Kaiser H. F. (1974). An index of factorial simplicity. Psychometrika, 39, 31-36. BF02291575

Kirk R. E. (2013). Experimental design: Procedures for the behavioral sciences (4th Ed.). Thousand Oaks, CA: Sage.

Marquez J., & de la Osa P. (2003). Evaluacion de la conciencia fonologica en el inicio lector [Assessing phonological awareness in initial reading]. Anuario de Psicologia, 34, 357-370.

Leong C. K. (1991). From phonemic awareness to phonological processing to language access in children developing reading proficiency. In D. J. Sawyer & B. J. Fox (Eds.), Phonological awareness in reading: The evolution of current perspectives (pp. 217-254). New York, NY: Springer-Verlag.

Mayor M. A., Fernandez M. L., Tunas A., Zubiauz B., & Duran M. (2012). La relacion entre funciones ejecutivas y conciencia fonologica en Educacion PriMaria [The relationship between executive functions and phonological awareness in Primary School]. In L. Mata, F. Peixoto, J. Morgado, J. Castro, & V. Monteiro (Eds.), Educacao , aprendizajem e desenvolvimento [Education, learning and development] (pp. 1792-1806). Lisbon, Portugal: ISPA.

Morais J. (1991). Phonological awareness: A bridge between language and literacy. In D. J. Sawyer & B. J. Fox (Eds.), Phonological awareness in reading. The evolution of current perspectives. Springer Series in Language and Communication (Vol. 28, pp. 31-71). New York, NY: Springer.

Muniz J. (1999). Psicometria [Psychometrics]. Madrid, Spain: Piramide.

Peralbo M., Brenlla J. C., Garcia M., Barca A., & Mayor M. A. (2012). Las funciones ejecutivas y su valor predictivo sobre el aprendizaje inicial de la lectura en educacion priMaria [The executive functions and their predictive value in initial reading acquisition during Primary School]. In L. Mata, F. Peixoto, J. Morgado, J. Castro, &

V. Monteiro (Eds.), Educacao , aprendizajem e desenvolvimento [Education, learning and development] (pp.76-90). Lisbon, Portugal: ISPA.

Perez-Gil J. A., Chacon S., & Moreno R. (2000). Validez de constructo: El uso de analisis factorial exploratorioconfirmatorio para obtener evidencias de validez [Construct validity: The use of exploratory-confirmatory factor analysis to collect evidence of validity]. Psicothema, 12, 442-440.

Stanovich K. E. (2000). Progress in understanding reading: Scientific foundations and new frontiers. New York, NY: Guilford Press.

Torgesen J. K., & Davis C. (1996). Individual difference variables that predict response to training in phonological awareness. Journal of Experimental Child Psychology, 63, 1-21.

Toro J., Cervera M., & Urio C. (2000). EMLE-TALE 2000. Escalas Magallanes de Lectura y Escritura [Magallanes Reading and Writing Scales]. Baracaldo, Spain: Albor-COHS.

Treiman R. (1991). Phonological awareness and its roles in learning to read and spell. In D. J. Sawyer & B. J. Fox (Eds.), Phonological awareness in reading. The evolution of current perspective (pp. 159-189). New York, NY: Spinger-Verlag.

Wilson M. (2005). Constructing measures: An item response modeling approach. Mahwah, NJ: Lawrence Erlbaum.

Zimmerman D. W. (2004). A note on preliminary tests of equality of variances. British Journal of Mathematical and Statistical Psychology, 57, 173-181. http://dx.doi. org/10.1348/000711004849222

(1) Examples of the various tasks can be found at -> Loleva --> Video de demostracion.

Manuel Peralbo (1), Maria Angeles Mayor (2), Begona Zubiauz (2), Alicia Risso (1), Maria Luz Fernandez-Amado (3) and Alejandro Tunas (4)

(1) Universidad de A Coruna (Spain)

(2) Universidad de Salamanca (Spain)

(3) Colegio San Juan Bosco (Spain)

(4) Altia Consultores (Spain)

Correspondence concerning this article should be addressed to Alicia Risso. Departamento de Psicologia. Campus de Elvina, s/n. Universidad de A Coruna. 15071. A Coruna (Spain). Phone: +34-981167000.


Table 1. Average Proportion of Correct Responses on Each of the
Test's Phonological Awareness Tasks in Each School Year

Task                  1st ECE     2nd ECE     3rd ECE     1st PE

                      (n = 39)    (n = 50)    (n = 91)    (n = 74)

                      M (SD)      M (SD)      M (SD)      M (SD)

Identification   R    .37 (.18)   .57 (.18)   .47 (.31)   .72 (.25)
                 FS   .33 (.31)   .63 (.25)   .76 (.24)   .89 (.17)
                 LS   .12 (.19)   .47 (.24)   .70 (.31)   .81 (.25)
                 FP   .00 (.00)   .04 (.20)   .61 (.30)   .77 (.29)
                 LP   .00 (.00)   .02 (.14)   .58 (.32)   .70 (.32)
Addition         FS   .00 (.00)   .13 (.26)   .51 (.34)   .74 (.29)
                 LS   .01 (.03)   .26 (.42)   .76 (.30)   .87 (.27)
                 FP   .00 (.00)   .00 (.00)   .49 (.36)   .60 (.35)
                 LP   .00 (.00)   .00 (.00)   .69 (.34)   .86 (.26)
Omission         FS   .00 (.00)   .18 (.37)   .62 (.38)   .83 (.28)
                 LS   .01 (.06)   .23 (.39)   .67 (.36)   .86 (.24)
                 FP   .00 (.00)   .00 (.00)   .37 (.35)   .68 (.31)
                 LP   .00 (.00)   .00 (.00)   .62 (.37)   .88 (.27)
Total                 .09 (.04)   .22 (.13)   .59 (.21)   .78 (.19)

Task                  2nd PE

                      (n = 87)

                      M (SD)

Identification   R    .80 (.22)
                 FS   .84 (.22)
                 LS   .80 (.25)
                 FP   .80 (.26)
                 LP   .75 (.30)
Addition         FS   .77 (.29)
                 LS   .91 (.19)
                 FP   .68 (.31)
                 LP   .90 (.23)
Omission         FS   .89 (.25)
                 LS   .85 (.22)
                 FP   .71 (.32)
                 LP   .88 (.27)
Total                 .81 (.19)

Note: R = rhyme; FS = first syllable; LS = last syllable; FP = first
phoneme; LP = last phoneme.

Table 2. Tests of Within-subjects Effects on the
Test's Phonological Awareness Tasks

Source                                          F             df

Task Type (b)                                    31.639 ***     2
Task Type x Year in School (b)                   11.129 ***     8
Error (Task Type) (b)                                         672
Syllable-Phoneme (b)                            229.000 ***     1
Syllable-Phoneme x Year in School (b)            26.188 ***     4
Error (Syllable-Phoneme) (b)                                  336
First-Last (b)                                   59.201 ***     1
First-Last x Year in School (b)                  18.851 ***     4
Error (First-Last) (b)                                        336
Task Type x Syllable-Phoneme (c)                 35.806 ***     1.848
Task Type x Syllable-Phoneme x Year in            9.664 ***     7.394
  School (c)
Error (Task Type x Syllable-Phoneme) (c)                      621.060
Task Type x First-Last (c)                       91.001 ***     1.879
Task Type x First-Last x Year in School (c)       2.374 *       7.516
Error (Task Type x First-Last) (c)                            631.367
Syllable-Phoneme x First-Last (b)                22.994 ***     1
Syllable-Phoneme x First-Last x Year in           2.526 *       4
  School (b)
Error (Syllable-Phoneme x First-Last) (b)                     336
Task Type x Syllable-Phoneme x First-Last (c)     7.153 ***     1.986
Task Type x Syllable-Phoneme x                    7.892 ***     7.943
  First-Last x Year in School (c)
Error (Task Type x Syllable-Phoneme                           667.221
  x First-Last) (c)

Source                                          [[eta].sup.2.sub.p]

Task Type (b)                                   .086
Task Type x Year in School (b)                  .117
Error (Task Type) (b)
Syllable-Phoneme (b)                            .405
Syllable-Phoneme x Year in School (b)           .238
Error (Syllable-Phoneme) (b)
First-Last (b)                                  .150
First-Last x Year in School (b)                 .183
Error (First-Last) (b)
Task Type x Syllable-Phoneme (c)                .096
Task Type x Syllable-Phoneme x Year in          .103
  School (c)
Error (Task Type x Syllable-Phoneme) (c)
Task Type x First-Last (c)                      .213
Task Type x First-Last x Year in School (c)     .027
Error (Task Type x First-Last) (c)
Syllable-Phoneme x First-Last (b)               .064
Syllable-Phoneme x First-Last x Year in         .029
  School (b)
Error (Syllable-Phoneme x First-Last) (b)
Task Type x Syllable-Phoneme x First-Last (c)   .021
Task Type x Syllable-Phoneme x                  .086
  First-Last x Year in School (c)
Error (Task Type x Syllable-Phoneme
  x First-Last) (c)

Source                                          1-[beta] (a)

Task Type (b)                                   1.000
Task Type x Year in School (b)                  1.000
Error (Task Type) (b)
Syllable-Phoneme (b)                            1.000
Syllable-Phoneme x Year in School (b)           1.000
Error (Syllable-Phoneme) (b)
First-Last (b)                                  1.000
First-Last x Year in School (b)                 1.000
Error (First-Last) (b)
Task Type x Syllable-Phoneme (c)                1.000
Task Type x Syllable-Phoneme x Year in          1.000
  School (c)
Error (Task Type x Syllable-Phoneme) (c)
Task Type x First-Last (c)                      1.000
Task Type x First-Last x Year in School (c)      .879
Error (Task Type x First-Last) (c)
Syllable-Phoneme x First-Last (b)                .998
Syllable-Phoneme x First-Last x Year in          .714
  School (b)
Error (Syllable-Phoneme x First-Last) (b)
Task Type x Syllable-Phoneme x First-Last (c)    .931
Task Type x Syllable-Phoneme x                  1.000
  First-Last x Year in School (c)
Error (Task Type x Syllable-Phoneme
  x First-Last) (c)

(a) Calculated for alpha = .05.

(b) Significance of Mauchly's W > .05 [right arrow] Sphericity

(c) Significance of Mauchly's W [less than or equal to] .05, Epsilon
> .70, and n > k + 10 [right arrow] Huynh-Feldt correction for
degrees of freedom (Collier, Baker, Mandeville, & Hayes, 1967; Field,
2005; Maxwell & Delaney, 2004).

* p <.001. ** p < .05.

Table 3. Discrimination Indices on the Test's Phonological Awareness

Alpha =                   1st ECE .14   2nd ECE .72   3rd ECE .84

Rhyme Recognition          .061         .428          .366
Syllable Identification    .141         .259          .692
Phoneme Identification                  .378          .651
Syllable Addition         -.114         .740          .655
Phoneme Addition                                      .667
Syllable Omission          .177         .728          .581
Phoneme Omission                                      .730

Alpha =                   1st PE .88   2nd PE .84

Rhyme Recognition         .502         .483
Syllable Identification   .536         .735
Phoneme Identification    .798         .756
Syllable Addition         .690         .720
Phoneme Addition          .727         .807
Syllable Omission         .666         .707
Phoneme Omission          .764         .802

Table 4. Average Proportion of Correct Responses and Time Used
(Sec.s) on Each of the Test's Initial Reading Competence Tasks by
Year in School

Task              1st ECE          2nd ECE         3rd ECE

Reading of:       (n = 39)         (n = 50)        (n = 91)

                  M (SD)           M (SD)          M (SD)

UcL           A      .38 (.25)       .78 (.17)       .81 (.22)
              S   115.24 (48.24)   79.07 (21.57)   52.29 (35.49)
LcL           A      .17 (.19)       .51 (.25)       .73 (.22)
              S    94.00 (42.86)   82.36 (22.55)   55.26 (52.03)
RW            A                                      .65 (.37)
              S                                    38.16 (27.09)
PW            A                                      .50 (.35)
              S                                    42.27 (2.16)
IW            A                                      .41 (.38)
              S                                    49.87 (23.26)
WS            A                                      .22 (.31)
              A                                    77.48 (39.81)
Total         A      .16 (.13)       .39 (.14)       .66 (.24)
              S   106.13 (41.23)   77.87 (28.52)   65.50 (52.03)

Task              1st PE           2nd PE

Reading of:       (n = 74)         (n = 87)

                  M (SD)           M (SD)

UcL           A     .94 (.14)        .95 (.15)
              S   38.20 (15.67)    34.42 (22.79)
LcL           A     .92 (.10)        .92 (.16)
              S    4.65 (14.56)   36.13 (16.65)
RW            A     .94 (.18)        .94 (.19)
              S   17.75 (9.10)     15.46 (8.13)
PW            A     .92 (.20)        .93 (.20)
              S   23.43 (1          2.48 (8.84)
IW            A     .92 (.20)        .92 (.22)
              S   23.81 (11.48)     2.04 (1.43)
WS            A     .75 (.27)        .83 (.16)
              A   55.35 (28.54)     4.16 (16.40)
Total         A     .92 (.13)        .93 (.16)
              S   34.58 (13.43)     3.49 (18.31)

Note: UcL = Uppercase letters; LcL = Lowercase letters; RW = Simple
words; PW = Pseudowords; IW = Complex words; WS= Word splitting; A
(accuracy) = Proportion of correct responses; S (speed) = Response
time, in seconds.

Table 5. Results of Repeated Measures Analyses by Initial Reading
Competence Task Type

Task                              Measure    df    F

Letter Reading                    Accuracy   1     392.041 ***
                                  Speed      1        .704
Letters x Year in School          Accuracy   4     50.210 ***
                                  Speed      4      8.234 ***
Error (Letters)                   Accuracy   325
                                  Speed      325
Word Reading                      Accuracy   1     71.766 ***
                                  Speed      1     28.860 ***
Words x Year in School            Accuracy   2     31.463 ***
                                  Speed      2      5.802 ***
Error (Words)                     Accuracy   213
                                  Speed      213
Word Splitting (Accuracy/Speed)              1     716.501 ***
Word Splitting x Year in School              2      19.556 ***
Error (Word Splitting)                       190

Task                              Measure    [[eta].sup.2.sub.p]

Letter Reading                    Accuracy   .547
                                  Speed      .002
Letters x Year in School          Accuracy   .382
                                  Speed      .092
Error (Letters)                   Accuracy
Word Reading                      Accuracy   .252
                                  Speed      .119
Words x Year in School            Accuracy   .228
                                  Speed      .052
Error (Words)                     Accuracy
Word Splitting (Accuracy/Speed)              .790
Word Splitting x Year in School              .171
Error (Word Splitting)

Task                              Measure    1-[beta] (a)

Letter Reading                    Accuracy   1.000
                                  Speed       .133
Letters x Year in School          Accuracy   1.000
                                  Speed       .999
Error (Letters)                   Accuracy
Word Reading                      Accuracy   1.000
                                  Speed      1.000
Words x Year in School            Accuracy   1.000
                                  Speed       .867
Error (Words)                     Accuracy
Word Splitting (Accuracy/Speed)              1.000
Word Splitting x Year in School              1.000
Error (Word Splitting)

(a) Calculated where alpha = .05

*** p < .001

Table 6. Discrimination Indices on the Test's Initial Reading
Competence Tasks

Alpha =                    1st ECE .88   2nd ECE .88   3rd ECE .91

Uppercase Letter Reading   .825          .788          .820
Lowercase Letter Reading   .825          .788          .898
Simple Word Reading                                    .897
Complex Word Reading                                   .834
Pseudoword Reading                                     .935
Word Splitting                                         .323

Alpha =                    1st PE .87   2nd PE .92

Uppercase Letter Reading   .525         .913
Lowercase Letter Reading   .844         .925
Simple Word Reading        .860         .914
Complex Word Reading       .854         .843
Pseudoword Reading         .817         .887
Word Splitting             .643         .707

Table 7. Results of Factor Analysis on the LolEva Test with
Equamax Rotation

Components                        I        II       III

% Explained Variance              29.49    29.13    16.41

Rhyme Recognition                   .805
First Syllable Identification       .627
Last Syllable Identification        .685     .330
Addition of First Syllable          .694     .461
Addition of Last Syllable           .590     .487     .387
Omission of First Syllable          .570     .628
Omission of Last Syllable           .587     .567
Identification of First Phoneme     .622     .540     .327
Identification of Last Phoneme      .682     .419     .320
Addition of First Phoneme           .751              .359
Addition of Last Phoneme            .664     .470     .383
Omission of First Phoneme           .711     .496
Omission of Last Phoneme            .608     .573     .323
Reading Uppercase Letters           .319     .744
Uppercase Letter Reading Time               -.818
Reading Lowercase Letters           .453     .739
Lowercase Letter Reading Time               -.785
Simple Word Reading                 .457     .774
Complex Word Reading                .566     .726
Pseudoword Reading                  .519     .767
Word Separation                     .615     .575
Simple Word Reading Time                              .886
Complex Word Reading Time                             .939
Pseudoword Reading Time                               .936
Word Splitting Time                 .356     .362     .439

Note: Factor loadings < .30 were excluded.
COPYRIGHT 2015 Universidad Complutense de Madrid
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2015 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Title Annotation:texto en ingles
Author:Peralbo, Manuel; Angeles Mayor, Maria; Zubiauz, Begona; Risso, Alicia; Fernandez-Amado, Maria Luz; T
Publication:Spanish Journal of Psychology
Date:Jan 1, 2015
Previous Article:Development and validation of the Escala de Actitudes Emprendedoras para Estudiantes (EAEE).
Next Article:Incremental validity of personality measures in predicting underwater performance and adaptation.

Terms of use | Privacy policy | Copyright © 2019 Farlex, Inc. | Feedback | For webmasters