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Identifying Kindergarteners At-Risk of Writing Difficulties Based on Foundational Literacy Skills

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Title: Identifying Kindergarteners At-Risk of Writing Difficulties Based on Foundational Literacy Skills
Language: English
Authors: Juan E. Jiménez (ORCID 0000-0002-7466-8340), Cristina Rodríguez (ORCID 0000-0001-9929-9767), Jennifer Balade (ORCID 0009-0005-4917-7506)
Source: Reading and Writing: An Interdisciplinary Journal. 2025 38(2):397-424.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 28
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Education Level: Early Childhood Education
Elementary Education
Kindergarten
Primary Education
Descriptors: Kindergarten, Writing Evaluation, Writing Skills, Functional Literacy, Writing Difficulties, At Risk Students, Spanish Speaking, Ability Identification, Test Reliability, Test Validity
DOI: 10.1007/s11145-024-10518-7
ISSN: 0922-4777
1573-0905
Abstract: The main aim of this study was to evaluate the Early Grade Writing Assessment for Kindergarten (EGWA-K), which is grounded in foundational literacy skills, for its validity and diagnostic accuracy in identifying children at risk of developing early learning disabilities in writing (LDW). To the best of our knowledge, no such tool exists for Spanish-speaking children. A sample of 363 Spanish kindergarten children aged 4.7 to 6.6 years was selected for this purpose. The EGWA-K protocol, comprising four tasks (i.e., phonological awareness, writing words from pictures, free writing of words, and oral narrative), was administered to the sample. Additionally, two criterion tasks based on free letter writing and teacher ratings were included for validation purposes. First, an exploratory factor analysis (EFA) was conducted using parallel analysis to determine the dimensionality of the EGWA-K, which was confirmed by a confirmatory factor analysis (CFA) yielding two factors (one related to transcription ability and the other to narrative competence). Additionally, measurement invariance was confirmed at the configural, metric, scalar, and residual levels by gender. The EGWA-K had an acceptable area under the ROC curve (AUC in the 0.87 range), particularly when free letter writing was utilized as the criterion measure, with adequate sensitivity (0.90) and specificity (0.71) indices. Therefore, a reliable and construct-valid screening tool such as the EGWA-K is now available for the early identification of LDW in Spanish kindergarten children.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1461752
Database: ERIC
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  Value: <anid>AN0183535474;2ap01feb.25;2025Mar11.02:17;v2.2.500</anid> <title id="AN0183535474-1">Identifying kindergarteners at-risk of writing difficulties based on foundational literacy skills </title> <p>The main aim of this study was to evaluate the Early Grade Writing Assessment for Kindergarten (EGWA-K), which is grounded in foundational literacy skills, for its validity and diagnostic accuracy in identifying children at risk of developing early learning disabilities in writing (LDW). To the best of our knowledge, no such tool exists for Spanish-speaking children. A sample of 363 Spanish kindergarten children aged 4.7 to 6.6 years was selected for this purpose. The EGWA-K protocol, comprising four tasks (i.e., phonological awareness, writing words from pictures, free writing of words, and oral narrative), was administered to the sample. Additionally, two criterion tasks based on free letter writing and teacher ratings were included for validation purposes. First, an exploratory factor analysis (EFA) was conducted using parallel analysis to determine the dimensionality of the EGWA-K, which was confirmed by a confirmatory factor analysis (CFA) yielding two factors (one related to transcription ability and the other to narrative competence). Additionally, measurement invariance was confirmed at the configural, metric, scalar, and residual levels by gender. The EGWA-K had an acceptable area under the ROC curve (AUC in the 0.87 range), particularly when free letter writing was utilized as the criterion measure, with adequate sensitivity (0.90) and specificity (0.71) indices. Therefore, a reliable and construct-valid screening tool such as the EGWA-K is now available for the early identification of LDW in Spanish kindergarten children.</p> <p>Keywords: Screening; Writing; At-risk; ROC curve; Kindergarten</p> <hd id="AN0183535474-2">Introduction</hd> <p>The early years of schooling, particularly in kindergarten, are crucial for identifying and providing targeted support to children who may be at risk for writing difficulties (Troia, [<reflink idref="bib70" id="ref1">70</reflink>]). Difficulties with writing during early educational years can impede a child's ability to catch up with his or her peers, leading to poor academic performance and lower self-esteem (Thomas et al., [<reflink idref="bib68" id="ref2">68</reflink>]). Therefore, it is crucial for educators and caregivers to be knowledgeable about the signs of potential writing difficulties and to implement appropriate interventions that support children's development (Dombek & Al Otaiba, [<reflink idref="bib20" id="ref3">20</reflink>]).</p> <p>Writing relies on related foundational literacy skills (e.g., phonological processing, phonological memory, phonemic awareness, handwriting; Berninger et al., [<reflink idref="bib8" id="ref4">8</reflink>]; Graham & Hebert, [<reflink idref="bib24" id="ref5">24</reflink>]; Kim et al., [<reflink idref="bib42" id="ref6">42</reflink>]; Olive, [<reflink idref="bib51" id="ref7">51</reflink>]; Sanders et al., [<reflink idref="bib64" id="ref8">64</reflink>]). There are different models of writing that have received significant conceptual support: the simple view of writing (SVW) model (Juel, [<reflink idref="bib33" id="ref9">33</reflink>]; Juel et al., [<reflink idref="bib34" id="ref10">34</reflink>]), the not-so-simple view of writing (NSVW) model (Berninger & Amtmann, [<reflink idref="bib6" id="ref11">6</reflink>]; Berninger & Winn, [<reflink idref="bib7" id="ref12">7</reflink>]), and the interactive dynamic literacy model (IDLM) (Kim, [<reflink idref="bib40" id="ref13">40</reflink>]). According to the SVW model, writing is a product of two skills: transcription and ideation (also known as text generation) (Berninger et al., [<reflink idref="bib8" id="ref14">8</reflink>]; Juel et al., [<reflink idref="bib34" id="ref15">34</reflink>]). A revision of this model was proposed, which expanded upon the simple view of writing in two ways (Kim & Schatschneider, [<reflink idref="bib41" id="ref16">41</reflink>]). First, executive function and self-regulatory processes (e.g., attention, goal setting, revision, etc.) were included in addition to text generation and transcription skills (Berninger & Amtmann, [<reflink idref="bib6" id="ref17">6</reflink>]; Berninger & Winn, [<reflink idref="bib7" id="ref18">7</reflink>]). Second, working memory was placed as the regulatory center for these three components (text generation, transcription, and self-regulation), which require access to long-term memory during the planning and composing process and short-term memory during the revising process (Berninger & Winn, [<reflink idref="bib7" id="ref19">7</reflink>]). Therefore, in this new model, transcription skills (i.e., handwriting fluency and spelling) and executive self-regulatory functions (i.e., attention and memory) work together for text generation. Text generation involves both idea generation and the transformation of ideas into linguistic propositions, which are closely related to oral language skills. This is supported by both theoretical and empirical evidence (Dockrell & Connely, [<reflink idref="bib19" id="ref20">19</reflink>]; Kim et al., [<reflink idref="bib43" id="ref21">43</reflink>]; Kim et al., [<reflink idref="bib42" id="ref22">42</reflink>]). Additionally, the IDLM (Kim, [<reflink idref="bib40" id="ref23">40</reflink>]) extends the simple view of writing and delineates the convergence of core skills and knowledge required for writing acquisition. The underlying concept posits that written composition stems from interconnected foundational literacy proficiencies and knowledge in conjunction with other correlated competencies, such as oral language, content and discourse familiarity, and higher cognitive functions. Consequently, these competencies exhibit interplay and mutual influence during the processes of written composition. The IDLM also underscores the significance of achieving a level of precision and automaticity in skill development to alleviate cognitive load and thereby allocate mental resources to more advanced cognitive processes. Overall, transcription skills and oral language skills are both recognized as strong predictors of writing development in early childhood (Kent & Wanzek, [<reflink idref="bib38" id="ref24">38</reflink>]; Kim et al., [<reflink idref="bib42" id="ref25">42</reflink>]; Puranik et al., [<reflink idref="bib60" id="ref26">60</reflink>]; White, [<reflink idref="bib73" id="ref27">73</reflink>]).</p> <hd id="AN0183535474-3">Transcription skills and writing</hd> <p>Transcription skills (TS), including handwriting fluency and spelling, are crucial components of writing skills (Berninger, [<reflink idref="bib5" id="ref28">5</reflink>]; Graham et al., [<reflink idref="bib25" id="ref29">25</reflink>]). In their review of studies on TS, Kim et al. ([<reflink idref="bib44" id="ref30">44</reflink>]) concluded that handwriting fluency can be defined as the accuracy and rate of writing letters and words. They found that this skill was typically measured by asking the child to write alphabet letters accurately with speed within a specified time. Findings from the meta-analysis conducted by Feng et al. ([<reflink idref="bib21" id="ref31">21</reflink>]) showed that handwriting is critical for predicting writing development, regardless of student grade level. Spelling, another transcription skill, is assessed primarily for accuracy and involves multiple skills, such as morphological awareness, phonological awareness, orthographic awareness, and letter sound correspondence knowledge.</p> <p>Children's ability to write alphabet letters not only reflects their emerging orthographic knowledge (Ritchey, [<reflink idref="bib61" id="ref32">61</reflink>]) but also exhibits substantial predictive validity for early-grade writing fluency, spelling, and compositional skills (Graham et al., [<reflink idref="bib25" id="ref33">25</reflink>]). As stated by Berninger et al. ([<reflink idref="bib9" id="ref34">9</reflink>]), "Letter production is a fundamentally important process in written expression" (p.87). Alphabet knowledge encompasses a child's capacity to comprehend both the names and sounds associated with individual letters (Treiman & Broderick., ([<reflink idref="bib69" id="ref35">69</reflink>]). Manolitsis and Tafa ([<reflink idref="bib48" id="ref36">48</reflink>]) conducted a study to longitudinally examine the development of letter-sound and letter-name knowledge and their relation to each other and to various aspects of phonological awareness in a sample of Greek kindergarten children who did not know how to read. They found that letter-sound knowledge predicted letter-name knowledge slightly better than vice versa. Furthermore, research focused on child development in writing has revealed notable progress in letter-writing skills as children grow older. For instance, Puranik et al. ([<reflink idref="bib58" id="ref37">58</reflink>]) found a clear improvement in the ability to write uppercase letters between the ages of 3 and 4, as well as between 4 and 5 years. Additionally, Worden and Boettcher's influential study ([<reflink idref="bib74" id="ref38">74</reflink>]) revealed substantial advancements in writing proficiency during the crucial period from ages 3 to 6, with a significant annual increase in both uppercase and lowercase letter composition abilities. In another study conducted by Puranik et al. ([<reflink idref="bib57" id="ref39">57</reflink>]), it was found that children's letter writing abilities might serve as a more accurate predictor of children's emergent literacy and developmental skills than their name-writing skills by the end of kindergarten. Later, Justi et al. ([<reflink idref="bib36" id="ref40">36</reflink>]) examined the effectiveness of the letter-name knowledge task in identifying students at risk of writing difficulties. The authors concluded that this task demonstrates high precision in detecting writing difficulties among kindergarten students.</p> <hd id="AN0183535474-4">Oral language and writing</hd> <p>Both the SVW and the NSVW models emphasize the significance of oral language. SVW focuses on 'ideation', while NSVW emphasizes 'text generation.' Kim's IDLM further elaborates on this notion, positing that written composition results from a fusion of foundational literacy skills and broader competencies, prominently including oral language and higher cognitive functions. Therefore, this approach is assumed to contribute to text generation. Writers need to use their knowledge of grammar and vocabulary to generate words and sentences in text production (Abbott & Berninger, [<reflink idref="bib1" id="ref41">1</reflink>]; Babayigit & Stainthorp, [<reflink idref="bib3" id="ref42">3</reflink>]). Despite its importance in the translation process, research on the relationship between oral language and writing has been limited (Shanahan, [<reflink idref="bib65" id="ref43">65</reflink>]; see Kent & Wanzek, [<reflink idref="bib38" id="ref44">38</reflink>], for a review). Empirical evidence has demonstrated that early oral language skills predict writing composition, the primary objective of writing, both concurrently and longitudinally (e.g., Kent et al., [<reflink idref="bib39" id="ref45">39</reflink>]; Kim et al., [<reflink idref="bib42" id="ref46">42</reflink>], [<reflink idref="bib44" id="ref47">44</reflink>]).</p> <p>As students develop lower-level transcription skills, they also acquire the higher-order oral language skills necessary for text generation. Furthermore, most emergent literacy models incorporate oral narrative competence (Pinto et al., [<reflink idref="bib53" id="ref48">53</reflink>]). In this sense, oral narrative skills emerge as essential oral competencies causally linked to narrative writing composition (Kim et al., [<reflink idref="bib44" id="ref49">44</reflink>]; Kirby et al., [<reflink idref="bib45" id="ref50">45</reflink>]; Pinto et al., [<reflink idref="bib55" id="ref51">55</reflink>]). Kim et al. ([<reflink idref="bib44" id="ref52">44</reflink>]) reported that kindergarteners' oral language skills predict their narrative writing skills in third grade. In addition, Pinto et al. ([<reflink idref="bib55" id="ref53">55</reflink>]) analyzed the development of narrative competences from oral to written stories in five- to seven-year-old Italian children. They found that among the emergent literacy variables (i.e., phonological awareness, oral narrative competence, and conceptual knowledge of the writing system), narrative competence was the only statistically significant predictor of children's competence in giving structure, coherence, and cohesion to their written stories. In addition, structure in oral narratives was the only statistically significant predictor of narrative competence in written production. Recently, Kirby et al. ([<reflink idref="bib45" id="ref54">45</reflink>]) provided empirical evidence that oral language instruction has an immediate positive effect on the narrative quality of students' writing. Taken together, these findings highlight the critical role of children's linguistic skills, particularly oral narrative competence, in predicting and facilitating the development of their writing skills, underscoring the importance of both lower-level transcription skills and higher-order oral language abilities in written expression (Berninger et al., [<reflink idref="bib10" id="ref55">10</reflink>]; Kim et al., [<reflink idref="bib44" id="ref56">44</reflink>]; Kirby et al., [<reflink idref="bib45" id="ref57">45</reflink>]; Pinto et al., [<reflink idref="bib53" id="ref58">53</reflink>]).</p> <hd id="AN0183535474-5">Writing screener for kindergarten</hd> <p>The earlier writing problems are identified, the easier it is for educators to identify students who may struggle academically and require supplementary support or intervention (Thomas et al., [<reflink idref="bib68" id="ref59">68</reflink>]). This early detection of struggling writers can help prevent students from falling further behind and improve their chances of success (Jung et al., [<reflink idref="bib35" id="ref60">35</reflink>]). Screening was defined as "the systematic application of a test or enquiry to identify individuals at sufficient risk of a specific disorder to warrant further investigation or direct preventive action" (Wald, [<reflink idref="bib71" id="ref61">71</reflink>], p. 1). There is a large body of research on the early identification of children with reading problems (e.g., Jenkins et al., [<reflink idref="bib29" id="ref62">29</reflink>]). In contrast to the expanding literature based on the development of effective reading screens, work on the most effective screens in writing is in its infancy. Little is known about the most effective screens or even the characteristics of struggling kindergarten writers (Coker & Ritchey, [<reflink idref="bib17" id="ref63">17</reflink>]). Indeed, little research has been conducted in recent years on identifying struggling writers in kindergarten (for a systematic review, see Balade et al., [<reflink idref="bib4" id="ref64">4</reflink>]).</p> <p>There are several pioneering studies in the search for a universal writing screening tool for kindergartens providing preliminary support for the diagnostic accuracy of early written expression screening tools in this stage (e.g., Coker & Ritchey, [<reflink idref="bib17" id="ref65">17</reflink>]; Keller-Margulis et al., [<reflink idref="bib37" id="ref66">37</reflink>]; Puranik et al., [<reflink idref="bib59" id="ref67">59</reflink>]). For instance, Coker and Ritchey ([<reflink idref="bib17" id="ref68">17</reflink>]) examined the diagnostic accuracy of an early written expression screener among kindergarten students. The study included researcher-developed writing tasks of letter writing, sound spelling, word spelling, and sentence writing, as well as the use of DIBELS to assess early literacy skills. The area under the curve (AUC) for individual early writing tasks ranged from 0.60 to 0.87 for predicting performance on various criteria, including the TEWL-2, contextual writing, global writing, and teacher ratings. Puranik et al. ([<reflink idref="bib59" id="ref69">59</reflink>]) analyzed whether a timed alphabet writing fluency task measure compared to an untimed measure of alphabet writing is more appropriate for kindergartens. They concluded that the latter approach would be more appropriate because imposing a time constraint results in low output and does not provide the teacher with much useful information, although they acknowledge the need for further research to draw more conclusive conclusions. More recently, Keller-Margulis et al. ([<reflink idref="bib37" id="ref70">37</reflink>]) identified measures such as picture words and word dictation as promising options for screening early writing skills. These studies have been carried out in English, a language characterized by a deep orthography in which the correspondences between graphemes and phonemes are inconsistent. However, to our knowledge, no studies have analyzed screening instruments for kindergarten in Spanish, a language characterized by a transparent orthography in which the correspondence between graphemes and phonemes is relatively simple and consistent.</p> <p>Several previous studies have also utilized teacher ratings of emergent literacy skills as a screening tool in early grades; however, the results have been mixed (Cabell et al., [<reflink idref="bib14" id="ref71">14</reflink>]; Coker & Ritchey, [<reflink idref="bib17" id="ref72">17</reflink>]). On the one hand, Cabell et al. ([<reflink idref="bib14" id="ref73">14</reflink>]) examined the extent to which teacher reports accurately differentiate children who exhibit low levels of emergent literacy skills relative to their peers. The results indicated that teacher ratings were significantly lower for children in the at-risk group than for those in the low-risk group, but the ratings were not sufficient to reliably identify at-risk children. Conversely, teacher ratings performed quite well in identifying children at low risk. On the other hand, Coker and Ritchey ([<reflink idref="bib17" id="ref74">17</reflink>]) used teacher ratings to evaluate the accuracy of identifying children as either at risk or not at risk in kindergarten. The writing measures demonstrated greater accuracy when teacher ratings were used as the criterion. However, none of these studies incorporated linguistic measures. Nevertheless, other studies have focused on oral language skills, specifically communication skills, and have shown the validity and usefulness of using teacher-reported indicators to monitor the oral language skills of children entering school, including vulnerable subpopulations (Gray et al., [<reflink idref="bib26" id="ref75">26</reflink>]).</p> <hd id="AN0183535474-6">Purpose of the study</hd> <p>The present study aimed to fill this gap by providing a screening tool to identify Spanish-speaking children at risk of writing difficulties at an earlier stage. To achieve this goal, a norm-referenced criterion measure and a teacher rating of student writing achievement were selected to validate a writing screening tool for use in Spanish kindergartens. Both types of measures have been found to be important ways to identify risk (Lembke et al., [<reflink idref="bib47" id="ref76">47</reflink>]; McMaster et al., [<reflink idref="bib49" id="ref77">49</reflink>]). It was hypothesized that the <emph>Early Grade Writing Assessment for Kindergarten</emph> (EGWA-K) would demonstrate moderate to strong relationships with a standardized norm-referenced measure of Free Writing Letter (FWL) and Teacher Rating (TR) and exhibit adequate diagnostic accuracy for identifying kindergarten students at risk. The EGWA-K includes a set of tasks designed to assess early writing and oral language skills, which are considered foundational for writing, and it was hypothesized that these dimensions could underlie the screening test. In sum, the present study aimed to address the following research questions: Do measures of early writing and oral language skills predict risk status in writing at the end of kindergarten? What is the diagnostic accuracy of early writing and oral language skills screening measures for identifying Spanish kindergarten students at risk? Does the inclusion of teacher ratings improve the prediction of risk status?</p> <hd id="AN0183535474-7">Method</hd> <p></p> <hd id="AN0183535474-8">Participants</hd> <p>A total of 363 Spanish kindergarteners (age M = 5.81 months; SD = 0.31, 180 males, 183 females) were selected from seven schools in the Canary Islands. All the children were monolingual Spanish speakers. Under Spanish law, the Education Act (Ley Orgánica para la Mejora de la Calidad Educativa - LOMCE 8/2013, 9th Dec) defines students with specific educational support needs (SESNs) as those who require additional educational support due to their special educational needs (SENs) (i.e., those who require support and specific educational attention due to their sensory impairment or acquired neurological problems, among others; these are traditionally used as exclusionary criteria for learning disabilities or severe behavioral disorders, either temporarily or throughout their schooling). The education act also contemplates those with specific learning disabilities, those who are gifted, or those who are late entering the education system (i.e., students coming from other countries or those who enter the education system late for any other reason), or due to personal circumstances or past school records.</p> <p>In the present study, only children with SEN were excluded (i.e., children who had sensory, acquired neurological, or other problems traditionally used as exclusionary criteria for learning disabilities). This information was provided by the Dirección General de Ordenación, Promoción e Innovación Educativa belonging to The Canary Islands Government (BOC 250, 22 December, [<reflink idref="bib13" id="ref78">13</reflink>]; BOC 40, 24 February, [<reflink idref="bib12" id="ref79">12</reflink>]). The children came from urban areas and from average socioeconomic backgrounds and attended state and nonstate schools.</p> <hd id="AN0183535474-9">Measures</hd> <p> <bold> <emph>Early Grade Writing Assessment for Kindergarten</emph> </bold> (EGWA-K) (Jiménez et al., [<reflink idref="bib32" id="ref80">32</reflink>]). The EGWA is an instrument based on foundational literacy skills that enables the early identification of kindergarten students at risk of experiencing learning difficulties in writing. The EGWA-K includes the following measures of early writing and oral language skills:</p> <p> <bold> <emph>Picture word writing</emph> </bold> (WP). The purpose of this assignment is to assess the transcription process from visual support, specifically images, to written words. It is designed as a dictation-like task with visual support, where the student is required to transcribe the word that corresponds to the presented image or drawing. Research has shown that spelling words is an excellent indicator of children's developing understanding of the alphabetic principle (Gehsmann & Mesme, [<reflink idref="bib23" id="ref81">23</reflink>]). Spelling a word requires translating spoken language into print (i.e., identifying phonemes and translating them to letters followed by the actual writing of the letter represented by that sound) (Puranik & Al Otaiba, [<reflink idref="bib56" id="ref82">56</reflink>]). A set of twelve images are provided, each representing regular, familiar words of varying length, both short and long. At the word level, one point is awarded for each accurately transcribed word. Orthographic errors and discrepancies between uppercase and lowercase letters are not penalized. If students named a word other than the target word (e.g., instead of saying "house", they said "cottage"), the examiner could redirect the situation with the question "Look at the picture. Can you think of another way to say it? Can you think of another word for it?". In extreme cases where the student did not recognize a picture, the examiner could offer the target word, but this rarely happened. The examiner provided the following instructions: "Your teacher has informed me of your proficiency in writing multiple words. For this task, I will display images, and you will orally identify the word it represents, subsequently transcribing it to the line beside the image to the best of your ability. If you are uncertain about the spelling of a word, do not worry about it, simply inform me, and we will proceed to the next image. Let us first begin with an example." The maximum possible score achieved on this task is 12 points. Cronbach's alpha for this task for this sample was 0.91.</p> <p> <bold> <emph>Phoneme segmentation</emph> </bold> (PS). This subscale is grounded in the theory that phonological awareness is a key predictor of early writing development. Children who can identify and manipulate individual sounds within words have a solid foundation for understanding phonetic and orthographic rules in language, which is fundamental for early writing (Pinto et al., [<reflink idref="bib53" id="ref83">53</reflink>]). Evidence suggests that children's phonological awareness predicts their writing skills at age 7 and older (Berninger et al., [<reflink idref="bib10" id="ref84">10</reflink>]). Therefore, this task assesses the student's ability to segment the auditory aspects of spoken language using 20 pseudowords. Pseudowords were generated to prevent segmentation by the orthographic pathway. We ensured that the pseudowords followed the same structure as real words in Spanish, meaning that they adhered to legal orthography and were phonetically pronounceable. These pseudowords consisted of 20 items distributed across four difficulty levels based on syllabic structure, as outlined by Jiménez et al. ([<reflink idref="bib31" id="ref85">31</reflink>]): CVCV (e.g., lesa), VCV (e.g., usi), CVCCV (e.g., teldo), and CCVCV (e.g., crimo). The stimuli were presented in five consecutive blocks, with each block containing one item from each difficulty level, ordered from the least to the most difficult. The student is asked to say the sounds of each pseudoword, evaluating their ability to segment the pseudoword using a phonemic strategy. The instructions for this task were as follows: "I am going to say a series of invented words out loud that have no meaning. Your task is to separate the sounds in each word, telling me each individual sound, one by one, as quickly as you can, trying not to make mistakes. Let us do an example first." The number of phonemic hits by the student in the first minute was recorded, with 1 point assigned for each phoneme that the student could identify in the first minute. The maximum possible score that can be achieved on this task is 85 points. The Cronbach's alpha for this task for this sample was 0.97.</p> <p> <bold> <emph>Free word writing</emph> </bold> (FWW). The aim of this task is to evaluate transcription ability through free word writing. In studies conducted in a transparent orthography, such as Italian, tasks designed to assess children's conceptual understanding of orthographic variations in sound quantity (as observed in Bigozzi et al., [<reflink idref="bib11" id="ref86">11</reflink>] and Pinto et al., [<reflink idref="bib53" id="ref87">53</reflink>]) involve instructing children to attempt to write a word they are familiar with, the shortest word they know, and the longest word they are acquainted with. Children who achieve higher scores in their conceptual understanding of orthography demonstrate the ability to access the orthographic representations of letters within a word and transcribe them onto paper. The findings from these studies emphasize the crucial role of kindergarten children's conceptual understanding of the writing system. This ability enables them to accurately encode written symbols and significantly contributes to their competence in various early writing tasks. Therefore, children are asked to write down words they want to write: a word they can write very well, a short word, and a long word. The total number of correctly written words was counted, with 1 point assigned for each correctly written word. Words are considered correct if they contain all the letters and are in the correct order. Spelling mistakes are not penalized, nor is the use of uppercase or lowercase letters. The maximum possible score that can be achieved on this task is 3 points. The instructions for this task were as follows: "Your teacher told me that you know how to write many words. In this game, I'm going to ask you to think of a word that you know how to write very well, then you have to say it out loud, and then you have to write the word on the line. Try to do this as quickly as possible without making mistakes. If you do not remember how to write a word, do not worry, just tell me, and we can think of another word."</p> <p> <bold> <emph>Narrative competence</emph> </bold> (NC). This assignment aims to assess a child's capacity to organize oral information and convey coherence in their discourse. The most commonly employed approach in research for evaluating children's narrative competence is to request that they narrate a story (Gazella & Stockman, [<reflink idref="bib22" id="ref88">22</reflink>]). This task is supported by studies demonstrating that children's ability to organize and communicate ideas coherently and sequentially correlates with writing development (Pinto et al., [<reflink idref="bib54" id="ref89">54</reflink>]). Evaluating narrative structure and the use of connectors in oral narration reflects children's ability to organize thoughts and convey them in writing (Akmese & Kanmaz, [<reflink idref="bib2" id="ref90">2</reflink>]; Piasta et al., [<reflink idref="bib52" id="ref91">52</reflink>]). Therefore, this task requires identifying whether the child can narrate a story from a given drawing; employing suitable resources such as articles, words, sentences, and connectors (cohesion) to relate them logically; and constructing a well-structured discourse including an introduction, characters, a sequence of events, solutions to problems, and a conclusion (structure). Additionally, this assignment evaluates productivity (i.e., number of words), lexical diversity (i.e., number of unique words), accuracy (number of correct words), fluency (i.e., number of correct words in one minute), grammaticality (i.e., number of grammatical errors), syntactic complexity of the discourse (i.e., number of sentences), and T-units (i.e., number of ideas). To codify the narrative structure (NS) measure, each dimension (i.e., title, opening of the story, characters, main event, problem, emotions, resolutions, and closure) was assessed based on the presence and depth of the student's performance. Students were awarded 2 points in each dimension for including this information and providing detailed elaboration, 1 point for merely including the element, and 0 points if the element was absent. For each dimension, specific instructions and examples were provided. The final score was computed as the aggregate of the points earned across all dimensions. Therefore, the final score could reach 16 points. For the purpose of coding Unique Words (UW), each nonrepetitive word was assigned a value of 1 point, and the final score was determined by tallying up all the unique words utilized in the student's oral narrative. To codify the T-Unit (TU) measure, every proposition was considered. A T-Unit is defined as a proposition along with all associated subordinate sentences (Green & Klecan-Aker, [<reflink idref="bib27" id="ref92">27</reflink>]). Based on these criteria, the following guidelines were established: (<reflink idref="bib1" id="ref93">1</reflink>) a simple sentence constitutes a single T-Unit; (<reflink idref="bib2" id="ref94">2</reflink>) a compound sentence constitutes two T-Units; and (<reflink idref="bib3" id="ref95">3</reflink>) a complex sentence constitutes a single T-Unit. Therefore, the final score represents the cumulative total of all T-Units present in the student's oral narrative. The instructions for this task were as follows: "I will present you with an image, and I expect you to narrate a story about it. Take your time to observe the image closely [allow for 30 seconds], and then begin to narrate the story. Try to recall a similar story that has happened to you or someone you know." The stories were recorded through an external recorder for later correction. The examiners had to relisten to the recordings to transcribe what the students told and to calculate the corresponding measures.</p> <p> <bold> <emph>Standardized Free Writing of Letters</emph> </bold> (Jiménez, [<reflink idref="bib30" id="ref96">30</reflink>]). This task is instrumental in appraising students' ability to form individual letters, which constitutes a fundamental aspect of early writing competence (Puranik et al., [<reflink idref="bib57" id="ref97">57</reflink>], [<reflink idref="bib58" id="ref98">58</reflink>]). Extensive research has established a compelling association between emergent literacy skills, such as alphabet knowledge and phonological awareness, and the development of letter-writing skills during the initial years of formal education (Puranik et al., [<reflink idref="bib57" id="ref99">57</reflink>]; Zhang et al., [<reflink idref="bib75" id="ref100">75</reflink>]). The student is asked to write down as many letters as they know without repeating any. The student was allowed to write the letters in uppercase or lowercase. In addition, they were instructed to write the letters as best as they could and as quickly as possible without making mistakes. The examiner provided the following instructions: "In this task, you must write down the letters you know. You will write them in each of these lines. You have to write each letter as quickly as possible without making mistakes." The number of correctly written letters in 1 min was recorded. A point was assigned when the following two conditions were met: (a) when the child writes a letter that can be roughly recognized, the quality or details of the grapheme are not considered; and (b) when the name or sound of the letter given by the child for the written letter is correct. Writing the letters in uppercase or lowercase was not penalized. That is, if the child wrote the same phoneme using two different forms of the corresponding letter, whether in lowercase or uppercase, only one point was assigned. Therefore, if both forms were used, only one was included in the total score. Letters that were unrecognizable or did not correspond to the name or sound the student had given were scored as 0 points. It is not possible to use homogeneity coefficients such as alpha for this task since they are inappropriate for highly speeded tests.</p> <p> <bold> <emph>Teacher rating</emph> </bold>. In the autonomous community of the Canary Islands, assessments in the early childhood education stage are divided into three main areas: (<reflink idref="bib1" id="ref101">1</reflink>) self-knowledge and personal autonomy, (<reflink idref="bib2" id="ref102">2</reflink>) knowledge of the environment, and (<reflink idref="bib3" id="ref103">3</reflink>) language: communication and representation. The scores of the "teacher evaluation" variable included in the analysis are based on the quantitative scores derived from students' grades in the "language, communication and representation" area. This area provides information about students' development throughout the academic year in oral language skills, phonological awareness, communicative abilities, and initial writing skills. Eighteen teachers from the seven participating schools took part in the study. Teachers were asked to rate each student's overall achievement based on classroom performance. Teachers were provided with a list of participating students and asked to rate each student on a 1 to 4 scale. The scoring range for these assessments ranged from 1 to 4, where a score of 1 represented "poor" and a score of 4 represented "excellent". These scores are based on the teacher's perception of the students' progress in this specific area throughout the academic year. We rely on the scores in this area because there are no specific or isolated scores available for the writing domain.</p> <hd id="AN0183535474-10">Procedure</hd> <p>This study was conducted according to the Research Ethics Committee guidelines from La Universidad de la Laguna (https://viinv.ull.es/ceiba/). Prior to the administration of the instrument, authorization was requested from the school and families for the study to be conducted. To collect the information, a total of 18 examiners were trained in the administration of the EGWA-K. These examiners were given a first training session in which they were taught how the tasks were to be administered and what their characteristics were. After the data were collected, a second training session was conducted in which the examiners were instructed on how to assess the content of the recorded oral narratives. During this session, they were trained in evaluating and scoring the content of the recorded narratives and were also provided guidance on entering the assessment data into an Excel template. The narrative coding process involved training sessions with examiners utilizing writing protocols as illustrative examples. Each examiner was provided with a manual containing correction criteria to ensure maximum objectivity in the correction process. This manual outlined how to code the various dimensions evaluated in the oral narrative. To achieve interrater reliability, examiners were given the same writing protocol for correction, and the results were collectively reviewed. In cases where there was disagreement on any dimension, the correction criteria were revisited, and this iterative process was applied to multiple protocol examples. The tests were administered in the spring, coinciding with the end of the school year. The administration was carried out individually during school hours, informing the students of the study's objectives and confidentiality.</p> <hd id="AN0183535474-11">Data analysis</hd> <p>Through exploratory factor analysis (EFA), parallel analysis was used to determine the dimensionality of the EGWA-K. Sedimentation graphs, eigenvalues, and proportions of eigenvalues were examined, with eigenvalues > 1 indicating whether a factor was included in the factorial structure. Oblimin rotation was used. When interpreting the pattern of rotated factor loadings, an item was deemed to load on a given factor if the factor loading was ≥ 0.40 for that factor. This structure was subsequently confirmed via confirmatory factor analysis (CFA) with maximum likelihood estimation. Measurement invariance at the configural, metric, scalar, and residual levels was also analyzed by sex.</p> <p>To analyze the diagnostic accuracy of the EGWA-K, a receiver operating characteristic (ROC) curve was generated, and the standardized Writing of Free Letters test and TR were used as the criterion measures. The area under the curve (AUC) is an overall measure of accuracy, with values greater than 0.70 and p values less than 0.05 indicating an acceptable fit and significance. According to Hinzte and Silberglitt (2005), while a consensus on the specific threshold for minimally acceptable sensitivity (or specificity) remains elusive, recommendations in the literature generally fall within the range of 0.70 to 0.90 for sensitivity and 0.70 or higher for specificity. An AUC of 0.50 to 0.70 was considered low, 0.70 to 0.90 was considered moderate, and 0.90 to 1.00 was considered high. The sample was first divided into two random halves. The first half was used for both EFAs and to observe the distribution of scores on the Free Letter Writing task as a function of percentiles. Although the 25th percentile is typically used as the cutoff point, this is not common in the field of writing research. Therefore, we used the 10th percentile since the distribution was skewed to the left, and the 25th percentile encompassed almost half of the sample. It is also plausible that the observed deviation in the sample may be attributed to the impact of COVID-19, as the children in this cohort experienced a few months of school closure during the onset of the pandemic. In fact, previous studies have illustrated the influence of the COVID-19 pandemic on writing proficiency. Skar et al. ([<reflink idref="bib66" id="ref104">66</reflink>]) reported that first-grade children, who were assessed immediately after the conclusion of emergency remote instruction in the Spring of 2020 (during the COVID-19 cohort), exhibited lower scores in writing quality, handwriting fluency, and attitude toward writing than first-grade students from the same schools tested a year prior before the onset of the pandemic (before the COVID-19 cohort). Subsequently, using the remaining half of the sample, a new categorical variable was calculated relative to the percentile calculated in the first sample on the FWL test, labeling children at risk or not at risk based on whether they fell above or below the cutoff point. Additionally, CFA was conducted with this second half of the sample. The EGWA-K test consists of different subtests that are evaluated using different units of measurement, so the scores of each subtest were transformed to be expressed on the same scale. To do this, we used the estimation of the proportion of maximum scale (POMS) (Cohen et al., [<reflink idref="bib15" id="ref105">15</reflink>]) according to the following formula:</p> <p>Graph</p> <p>Because POMS scores are calculated at the individual level for each variable, it is not necessary to establish an initial baseline, and they allow covariances to be maintained for conducting confirmatory factor analysis. With this approach, each variable is scored on a scale between 0 (minimum possible value) and 100 (maximum possible value). The resulting POMP-transformed scores can be interpreted as percentages of the maximum possible score (Moeller, [<reflink idref="bib50" id="ref106">50</reflink>]). The analyses presented below were conducted using the R program (R Core Team, [<reflink idref="bib18" id="ref107">18</reflink>]) and the lavaan package (Rosseel, [<reflink idref="bib63" id="ref108">63</reflink>]).</p> <hd id="AN0183535474-12">Results</hd> <p>Table 1 presents the descriptive statistics for each task of the EGWA-K, including maximum and minimum values, means, standard deviation, skewness, and kurtosis for each task. By examining the skewness and kurtosis values of all the study variables, it can be observed that there are no issues with the data distribution, as the absolute values of these indices do not exceed 3.0 and 10.0, respectively (Kline, [<reflink idref="bib46" id="ref109">46</reflink>]).</p> <p>Table 1 Descriptive statistics of early writing measures, oral language skills, and spring criterion measures</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" /><th align="left"><p>M</p></th><th align="left"><p>SD</p></th><th align="left"><p>median</p></th><th align="left"><p>trimmed</p></th><th align="left"><p>mad</p></th><th align="left"><p>min</p></th><th align="left"><p>max</p></th><th align="left"><p>range</p></th><th align="left"><p>skew</p></th><th align="left"><p>kurtosis</p></th><th align="left"><p>se</p></th></tr></thead><tbody><tr><td align="left"><p>WP</p></td><td align="left"><p>5.18</p></td><td align="left"><p>4.22</p></td><td align="left"><p>5</p></td><td align="left"><p>5.06</p></td><td align="left"><p>5.93</p></td><td align="left"><p>0</p></td><td align="left"><p>12</p></td><td align="left"><p>12</p></td><td align="left"><p>0.02</p></td><td align="left"><p>-1.53</p></td><td align="left"><p>0.23</p></td></tr><tr><td align="left"><p>PS</p></td><td align="left"><p>11.09</p></td><td align="left"><p>10.28</p></td><td align="left"><p>8</p></td><td align="left"><p>9.36</p></td><td align="left"><p>7.41</p></td><td align="left"><p>0</p></td><td align="left"><p>50</p></td><td align="left"><p>50</p></td><td align="left"><p>1.42</p></td><td align="left"><p>1.57</p></td><td align="left"><p>0.61</p></td></tr><tr><td align="left"><p>FWW</p></td><td align="left"><p>1.84</p></td><td align="left"><p>1.02</p></td><td align="left"><p>2</p></td><td align="left"><p>1.93</p></td><td align="left"><p>1.48</p></td><td align="left"><p>0</p></td><td align="left"><p>3</p></td><td align="left"><p>3</p></td><td align="left"><p>-0.37</p></td><td align="left"><p>-1.04</p></td><td align="left"><p>0.06</p></td></tr><tr><td align="left"><p>NS</p></td><td align="left"><p>6.72</p></td><td align="left"><p>2.76</p></td><td align="left"><p>7</p></td><td align="left"><p>6.66</p></td><td align="left"><p>2.97</p></td><td align="left"><p>0</p></td><td align="left"><p>16</p></td><td align="left"><p>16</p></td><td align="left"><p>0.25</p></td><td align="left"><p>0.21</p></td><td align="left"><p>0.15</p></td></tr><tr><td align="left"><p>UW</p></td><td align="left"><p>21.03</p></td><td align="left"><p>9.70</p></td><td align="left"><p>19</p></td><td align="left"><p>19.95</p></td><td align="left"><p>7.41</p></td><td align="left"><p>0</p></td><td align="left"><p>54</p></td><td align="left"><p>54</p></td><td align="left"><p>1.02</p></td><td align="left"><p>0.88</p></td><td align="left"><p>0.54</p></td></tr><tr><td align="left"><p>TU</p></td><td align="left"><p>3.98</p></td><td align="left"><p>2.19</p></td><td align="left"><p>4</p></td><td align="left"><p>3.75</p></td><td align="left"><p>1.48</p></td><td align="left"><p>1</p></td><td align="left"><p>14</p></td><td align="left"><p>13</p></td><td align="left"><p>1.17</p></td><td align="left"><p>1.66</p></td><td align="left"><p>0.12</p></td></tr><tr><td align="left"><p>FWL</p></td><td align="left"><p>6.72</p></td><td align="left"><p>3.24</p></td><td align="left"><p>6</p></td><td align="left"><p>6.54</p></td><td align="left"><p>2.97</p></td><td align="left"><p>0</p></td><td align="left"><p>18</p></td><td align="left"><p>18</p></td><td align="left"><p>0.57</p></td><td align="left"><p>0.31</p></td><td align="left"><p>0.17</p></td></tr><tr><td align="left"><p>TR</p></td><td align="left"><p>3.00</p></td><td align="left"><p>0.72</p></td><td align="left"><p>3</p></td><td align="left"><p>3.03</p></td><td align="left"><p>0.00</p></td><td align="left"><p>0</p></td><td align="left"><p>4</p></td><td align="left"><p>4</p></td><td align="left"><p>-0.50</p></td><td align="left"><p>0.38</p></td><td align="left"><p>0.04</p></td></tr></tbody></table> </ephtml> </p> <p> <emph>Note</emph> WP = Word Picture; PS = Phoneme Segmentation; FWW = Free Word Writing; NS = Narrative Structure; UW = Unique Words; TU = T-Units; FWL = Free Writing Letter ; TR = Teacher Rating</p> <hd id="AN0183535474-13">Interrater reliability</hd> <p>According to Walter et al. ([<reflink idref="bib72" id="ref110">72</reflink>]), with two examiners and a null intraclass of 0.7 and an alternative value of 0.8 for alpha 0.05 and beta = 0.20 (power 0.80), the number of protocols to be analyzed must be 117. Now, we present the ICCs separately for each measurement and for each one with 117 protocols from two examiners. Notably, one of the psychologists involved in the ratings was also a researcher on the project, while the other examiner referred to a random selection of 117 protocols that had been independently scored by examiners participating in the project. The intraclass correlation coefficients (ICCs) presented in the subsequent analysis are based on the assessment of these 117 protocols by the two examiners ensuring a comprehensive evaluation of interrater reliability for each measure. An EGWA-K – Administrator Instructions and Protocol training manual was compiled, and a four-hour workshop was held to teach assessors how to score the EGWA-K. A set of 117 randomly selected writing protocols was double scored. The results were analyzed using intraclass correlation coefficients (ICCs), i.e., the value obtained for the correlation coefficient of absolute agreement (average fixed raters) between the two examiners. For narrative structure, the average ICC was 0.81, with a 95% confidence interval from 0.72 to 0.87. <emph>F</emph> (<reflink idref="bib114" id="ref111">114</reflink>, 114) = 5.2, <emph>p</emph> < 0.001. For unique word measurements, the average ICC was 0.96, with a 95% confidence interval from 0.94 to 0.97. <emph>F</emph> (<reflink idref="bib114" id="ref112">114</reflink>, 114) = 0.24, <emph>p</emph> < 0.001. For the t-unit measurements, the average ICC was 0.86, with a 95% confidence interval from 0.79 to 0.80. <emph>F</emph> (<reflink idref="bib114" id="ref113">114</reflink>, 114) = 7.0, <emph>p</emph> < 0.001. For free word writing, the average ICC was 1.0, with a 95% confidence interval from 0.99 to 1.0. <emph>F</emph> (<reflink idref="bib116" id="ref114">116</reflink>, 116) = 227, <emph>p</emph> < 0.001. These findings suggest that the raters exhibited good agreement in assessing narrative structure, capturing unique words, measuring t-units, and free word writing.</p> <hd id="AN0183535474-14">Validity results</hd> <p>The correlation matrix of the results obtained from the different tasks is shown in Table 2. All early writing and oral storytelling skills were significantly related to FWL, with the exception of PS. FWL was weakly related to WP (0.26), FWW (0.22), NS (0.19), UW (0.23), and TU (0.18). Scores for each early writing skill were significantly related to teacher ratings with moderate correlations. That is, TR was moderately related to WP (0.53), PS (0.42), and FWW (0.45), with the exception of NS, UW, and TU. In addition, the EGWA-K demonstrated a moderate correlation with TR (0.51) and was weakly related to FWL (0.30). Both the WP and the FWW tasks exhibited a significant correlation with NS, while they did not show a significant correlation with the use of UW or the TU in oral storytelling.</p> <p>Table 2 Correlations of early writing measures, oral language skills, and spring criterion measures</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" /><th align="left"><p>WP</p></th><th align="left"><p>PS</p></th><th align="left"><p>FWW</p></th><th align="left"><p>NS</p></th><th align="left"><p>UW</p></th><th align="left"><p>TU</p></th><th align="left"><p>FWL</p></th><th align="left"><p>TR</p></th></tr></thead><tbody><tr><td align="left"><p>WP</p></td><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left"><p>PS</p></td><td align="left"><p>0.55***</p></td><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left"><p>FWW</p></td><td align="left"><p>0.58***</p></td><td align="left"><p>0.39***</p></td><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left"><p>NS</p></td><td align="left"><p>0.17**</p></td><td align="left"><p>0.01</p></td><td align="left"><p>0.21***</p></td><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left"><p>UW</p></td><td align="left"><p>0.05</p></td><td align="left"><p>0.04</p></td><td align="left"><p>0.12</p></td><td align="left"><p>0.60***</p></td><td align="left" /><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left"><p>TU</p></td><td align="left"><p>0.05</p></td><td align="left"><p>-0.04</p></td><td align="left"><p>0.09</p></td><td align="left"><p>0.54***</p></td><td align="left"><p>0.72***</p></td><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left"><p>FWL</p></td><td align="left"><p>0.26***</p></td><td align="left"><p>0.01</p></td><td align="left"><p>0.22***</p></td><td align="left"><p>0.19**</p></td><td align="left"><p>0.23***</p></td><td align="left"><p>0.18**</p></td><td align="left" /><td align="left" /></tr><tr><td align="left"><p>TR</p></td><td align="left"><p>0.53***</p></td><td align="left"><p>0.42***</p></td><td align="left"><p>0.45***</p></td><td align="left"><p>0.10</p></td><td align="left"><p>0.12</p></td><td align="left"><p>0.02</p></td><td align="left"><p>0.28***</p></td><td align="left" /></tr><tr><td align="left"><p>EGWA_K</p></td><td align="left"><p>0.77***</p></td><td align="left"><p>0.59***</p></td><td align="left"><p>0.76***</p></td><td align="left"><p>0.55***</p></td><td align="left"><p>0.51***</p></td><td align="left"><p>0.47***</p></td><td align="left"><p>0.30***</p></td><td align="left"><p>0.51***</p></td></tr></tbody></table> </ephtml> </p> <p> <emph>Note</emph> *p <.05; **p <.01; ***p <.001; WP = Word Picture; PS = Phoneme Segmentation; FWW = Free Word Writing NS = Narrative Structure; UW = Unique Words; TU = T-Units; FWL = Free Writing Letter; TR = Teacher Rating; EGWA-K = Early Grade Writing Assessment for Kindergarten</p> <p>In the first stage of our analysis, we divided the sample randomly into two equal parts. The first half was utilized for conducting an exploratory factor analysis (EFA). We examined the suitability of the data for EFA by examining the correlations between the different variables and ensuring that the variables were sufficiently intercorrelated. Then, we used Bartlett's test to confirm that our population correlation matrix was different from an identity matrix; that is, that our variables were intercorrelated or not independent of one another. We also used the Kaiser‒Meyer‒Olkin (KMO) test, a measure of sampling adequacy, to further assess the suitability of each of the variables to be included in EFA. We also checked the determinant of the correlation matrix to assess multicollinearity. We used three criteria to determine the number of factors to be extracted. The first criterion consisted of retaining variables that had eigenvalues equal to or greater than 1. Although it is a popular criterion among researchers, it often overestimates the number of factors to be retained; thus, the scree plot was also used for its accuracy in identifying the factors with eigenvalues in the sharp descent prior to levelling off for samples above 200 participants (Stevens, [<reflink idref="bib67" id="ref115">67</reflink>]). Apart from these two criteria reported as preferred by researchers, we also used parallel analysis, as it is the most accurate of all criteria (Henson & Roberts, [<reflink idref="bib28" id="ref116">28</reflink>]).</p> <p>The results of the exploratory factor analysis using parallel analysis revealed a two-factor solution. The scree plot and parallel analysis both supported the selection of two factors. The factor loadings for all variables were above 0.40 and were statistically significant (<emph>p</emph> < 0.001). One factor was related to TS (i.e., the number of accurately spelled words generated from pictures, the number of accurately spelled words written without visual support, and the number of accurately segmented phonemes in one minute), and the other factor was related to oral narrative competence (i.e., the number of unique words in the oral narrative, the number of T-units in the oral narrative, and structure). Table 3 shows the factorial weights, communality, uniqueness, and complexity of the transcription and narrative competence factors.</p> <p>Table 3 Factorial Weights, Communality, Uniqueness, and Complexity of early writing and oral language measures</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>item</p></th><th align="left"><p>NC</p></th><th align="left"><p>TS</p></th><th align="left"><p>Communality</p></th><th align="left"><p>Uniqueness</p></th><th align="left"><p>Complexity</p></th></tr></thead><tbody><tr><td align="left"><p>UW</p></td><td align="left"><p>0.885</p></td><td align="left" /><td align="left"><p>0.789</p></td><td align="left"><p>0.211</p></td><td align="left"><p>1.001</p></td></tr><tr><td align="left"><p>TU</p></td><td align="left"><p>0.872</p></td><td align="left" /><td align="left"><p>0.747</p></td><td align="left"><p>0.253</p></td><td align="left"><p>1.019</p></td></tr><tr><td align="left"><p>NS</p></td><td align="left"><p>0.621</p></td><td align="left" /><td align="left"><p>0.453</p></td><td align="left"><p>0.547</p></td><td align="left"><p>1.175</p></td></tr><tr><td align="left"><p>WP</p></td><td align="left" /><td align="left"><p>0.872</p></td><td align="left"><p>0.758</p></td><td align="left"><p>0.242</p></td><td align="left"><p>1.000</p></td></tr><tr><td align="left"><p>FWW</p></td><td align="left" /><td align="left"><p>0.654</p></td><td align="left"><p>0.443</p></td><td align="left"><p>0.557</p></td><td align="left"><p>1.018</p></td></tr><tr><td align="left"><p>PS</p></td><td align="left" /><td align="left"><p>0.626</p></td><td align="left"><p>0.386</p></td><td align="left"><p>0.614</p></td><td align="left"><p>1.013</p></td></tr></tbody></table> </ephtml> </p> <p> <emph>Note</emph> TS = Transcription skills; NC = Narrative Competence; UW = Unique Words; TU = T-Units; NS = Narrative Structure; WP = Word Picture; FWW = Free Word Writing; PS = Phoneme Segmentation</p> <p>The second half of the sample was then used to conduct a confirmatory factor analysis (CFA), which validated the structure identified by the EFA. The results of the confirmatory factor analysis indicated a good fit of the hypothesized model to the data, as evidenced by the following fit indices: the chi-square statistic (<emph>χ2</emph> = 9.141, df = 8, <emph>p</emph> = 0.33), comparative fit index (CFI = 0.99), Tucker‒Lewis index (TLI = 0.99), and root mean square error of approximation (RMSEA = 0.03, 90% CI [0.00, 0.10]). All standardized factor loadings were statistically significant (<emph>p</emph> < 0.001) and ranged from 0.59 to 0.89, indicating that the latent factors were well represented by the observed indicators. The omega index obtained was 0.78. A graphical representation of the model is shown in Fig. 1.</p> <p>Graph: Fig. 1 Confirmatory factor analysis model for the EGWA-K measure. Note TS = Transcription skills; NC = Narrative Competence; WP = Word Picture; PS = Phoneme Segmentation; FWW = Free Word Writing; NS = Narrative Structure; UW = Unique Words; TU = T-Unit</p> <p>Table 4 displays the fit indices of the confirmatory factor analysis model. Overall, the goodness-of-fit indices for the confirmatory factor analysis (CFA) model are indicative of a satisfactory fit. The traditional chi-square test, which assesses the difference between observed and estimated covariance matrices, yielded a nonsignificant p value (<emph>p</emph> = 0.466), suggesting adequacy in representing the data. Simultaneously, robust goodness-of-fit indices, accounting for potential nonnormality, also demonstrated robustness in model fit, with a nonsignificant robust chi-square p value (<emph>p</emph> = 0.33). Normed fit indices, including NFI, NNFI, CFI, and TLI, consistently approached or reached values close to 1.0, indicating favorable fits for both traditional and robust models. The RMSEA, a measure of approximation error, was low for both the traditional (RMSEA = 0.000) and robust (RMSEA = 0.031) models. In conclusion, the model exhibits robustness and adequacy in capturing the underlying structure of the observed data, as evidenced by both traditional and robust goodness-of-fit indices.</p> <p>Table 4 Confirmatory factor analysis model fit indices</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" /><th align="left"><p>chisq</p></th><th align="left"><p>df</p></th><th align="left"><p>pvalue</p></th><th align="left"><p>nfi</p></th><th align="left"><p>nnfi</p></th><th align="left"><p>cfi</p></th><th align="left"><p>tli</p></th><th align="left"><p>rmsea</p></th><th align="left"><p>ci.lower</p></th><th align="left"><p>ci.upper</p></th></tr></thead><tbody><tr><td align="left"><p>ajusted</p></td><td align="left"><p>7.669</p></td><td align="left"><p>8</p></td><td align="left"><p>0.466</p></td><td align="left"><p>0.968</p></td><td align="left"><p>1.003</p></td><td align="left"><p>1.000</p></td><td align="left"><p>1.003</p></td><td align="left"><p>0.000</p></td><td align="left"><p>0</p></td><td align="left"><p>0.102</p></td></tr><tr><td align="left"><p>robust</p></td><td align="left"><p>9.259</p></td><td align="left"><p>8</p></td><td align="left"><p>0.321</p></td><td align="left"><p>0.956</p></td><td align="left"><p>0.991</p></td><td align="left"><p>0.995</p></td><td align="left"><p>0.991</p></td><td align="left"><p>0.032</p></td><td align="left"><p>0</p></td><td align="left"><p>0.105</p></td></tr></tbody></table> </ephtml> </p> <p>These findings provide a comprehensive assessment of the validity and reliability of the measurement instrument. Specifically, the results of the confirmatory factor analysis outlined above offer compelling evidence for the construct validity of our hypothesized model. Furthermore, the omega index, also detailed above, emphasizes the internal consistency and reliability of our instrument. We believe that these nuanced analyses, integrated with the specific results presented earlier, collectively strengthen the overall credibility and utility of our measurement instrument.</p> <p>The examination of gender invariance for the model yielded encouraging outcomes across multiple stages. During the configural invariance phase, the model demonstrated a robust fit, reflected by a nonsignificant chi-square (χ2), a high comparative fit index (CFI) of 0.975, and a root mean square error of approximation (RMSEA) of 0.077. This finding suggested that the fundamental structure of the model remains consistent across genders. Moving to metric invariance, where factor loadings are constrained to be equal, the model sustained a strong fit with a CFI of 0.982 and a marginally increased but nonsignificant RMSEA of 0.058. This finding indicates that not only are the measurement properties comparable across genders but also that the impact on fit is minimal. In scalar invariance, maintaining equality in factor loadings and intercepts did not compromise the model's integrity, with a CFI of 0.983 and an RMSEA of 0.052. The negligible change in fit indices suggested equivalence not only in measurement properties but also in item intercepts across gender groups. Finally, under strict invariance, where constraints are extended to residual variances, the model maintained a high CFI of 0.980 and an RMSEA of 0.050, further supporting the equivalence of error variances across genders. Table 5 shows the fit indices for the measurement invariance models by sex.</p> <p>Table 5 <emph>Invariance Model Fit Indices</emph></p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Model</p></th><th align="left"><p>χ2</p></th><th align="left"><p>df</p></th><th align="left"><p>p</p></th><th align="left"><p>CFI</p></th><th align="left"><p>RMSEA</p></th><th align="left"><p>CI lower</p></th><th align="left"><p>CI upper</p></th><th align="left"><p>χ2*</p></th><th align="left"><p>df*</p></th><th align="left"><p>Pr(>χ2*)</p></th><th align="left"><p>Δdf</p></th><th align="left"><p>ΔRMSEA</p></th><th align="left"><p>ΔCFI</p></th><th align="left"><p>ΔTLI</p></th></tr></thead><tbody><tr><td align="left"><p>configural</p></td><td align="left"><p>22.693</p></td><td align="left"><p>16</p></td><td align="left"><p>0.122</p></td><td align="left"><p>0.975</p></td><td align="left"><p>0.077</p></td><td align="left"><p>0</p></td><td align="left"><p>0.143</p></td><td align="left"><p>19.759</p></td><td align="left"><p>16</p></td><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left"><p>metric</p></td><td align="left"><p>24.260</p></td><td align="left"><p>20</p></td><td align="left"><p>0.231</p></td><td align="left"><p>0.982</p></td><td align="left"><p>0.058</p></td><td align="left"><p>0</p></td><td align="left"><p>0.129</p></td><td align="left"><p>24.051</p></td><td align="left"><p>20</p></td><td align="left"><p>0.573</p></td><td align="left"><p>4</p></td><td align="left"><p>-0.018</p></td><td align="left"><p>0.007</p></td><td align="left"><p>0.019</p></td></tr><tr><td align="left"><p>scalar</p></td><td align="left"><p>28.043</p></td><td align="left"><p>24</p></td><td align="left"><p>0.258</p></td><td align="left"><p>0.983</p></td><td align="left"><p>0.052</p></td><td align="left"><p>0</p></td><td align="left"><p>0.119</p></td><td align="left"><p>27.682</p></td><td align="left"><p>24</p></td><td align="left"><p>0.440</p></td><td align="left"><p>4</p></td><td align="left"><p>-0.007</p></td><td align="left"><p>0.001</p></td><td align="left"><p>0.006</p></td></tr><tr><td align="left"><p>strict</p></td><td align="left"><p>34.456</p></td><td align="left"><p>30</p></td><td align="left"><p>0.263</p></td><td align="left"><p>0.980</p></td><td align="left"><p>0.050</p></td><td align="left"><p>0</p></td><td align="left"><p>0.115</p></td><td align="left"><p>36.610</p></td><td align="left"><p>30</p></td><td align="left"><p>0.365</p></td><td align="left"><p>6</p></td><td align="left"><p>-0.001</p></td><td align="left"><p>-0.003</p></td><td align="left"><p>0.001</p></td></tr></tbody></table> </ephtml> </p> <p>Overall, these results suggest that the measurement model used in this study is invariant across genders, which provides evidence that gender differences in the construct are not due to differences in the measurement properties of the variables. These findings support the use of the instrument as a reliable and valid measure of the construct for both males and females.</p> <hd id="AN0183535474-15">Diagnostic accuracy</hd> <p>The ROC curve analyses were conducted using both factors (transcription and narrative competence) from the EGWA-K by calculating an overall score. The criterion measure used was free letter writing (FWL). Furthermore, the diagnostic accuracy of the EGWA-K was also analyzed by examining the ROC curve based on the TR as the criterion measure.</p> <p> <bold>FWL</bold>. When the criterion score of Pc10 was used as the cutoff point, the ROC curve analysis showed an AUC of 87.6% (95% CI: 76.7-98.5%) (DeLong), with a sensitivity of 0.90 and specificity of 0.71. These results indicate that the EGWA-K successfully identifies 90% of individuals who were truly at risk while accurately identifying 71% of individuals who were not at risk. (see Fig. 2).</p> <p>Graph: Fig. 2 Receiver operating characteristic curve (ROC) for EGWA-K predicting Risk vs. Non-Risk based on the Free Writing Letter as criterion measure</p> <p> <bold>TR</bold>. By utilizing a criterion score of Pc10 as the classification threshold, the ROC curve analysis demonstrated an AUC of 75.34% (95% CI: 62-88.7%) (DeLong), with a sensitivity of 0.79 and specificity of 0.70. These results indicate that when TR is used as the criterion measure, the EGWA-K identifies 79% of individuals who were truly at risk. Moreover, the specificity was 0.70, indicating that the EGWA-K accurately recognizes 70% of individuals who were not at risk.</p> <p> <bold>FWL + TR</bold>. When utilizing the Pc10 criterion score as the classification threshold, the analysis of the ROC curve yielded an AUC of 88.59% (95% CI: 79.4-97.8% (DeLong), indicating a strong ability to discriminate between the two groups. The sensitivity was determined to be 0.77, and the specificity was 0.77.</p> <p>The EGWA-K demonstrated the highest diagnostic accuracy when utilizing the align="left"s (FWL) criterion variable. This model successfully identifies a higher percentage of individuals truly at risk (true positives) while keeping the rate of falsely identifying individuals as at risk (false positives) at a reasonable level. In this scenario, the instrument achieved a notable sensitivity of 90% and a specificity of 71%, indicating a strong ability to identify individuals at risk of writing difficulties while accurately recognizing those not at risk. Therefore, the FWL criterion appears to be the most effective at maximizing the diagnostic precision of the EGWA-K. Nevertheless, the comparison of AUCs indicated no statistically significant differences between the FWL and TR criterion measures, yielding D = 1.39, df = 235, <emph>p</emph> = 0.17; FWL + TR and FWL, D = 0.14, df = 235, <emph>p</emph> = 0.89; and FWL + TR and TR, D = 1.6, df = 217, <emph>p</emph> = 0.11. These results collectively suggest that the diagnostic assessment employed in this study, specifically the EGWA-K, is a reliable and valid measure for identifying individuals at risk of the target outcome. The elevated AUC value underscores the effectiveness of the diagnostic tool in discriminating between individuals at risk and those not at risk. Furthermore, the sensitivity and specificity values provide additional evidence of its accuracy. These findings have substantial implications for the development of interventions designed to mitigate the risk of the target outcome, indicating that the EGWA-K can accurately identify individuals who stand to benefit from such interventions.</p> <hd id="AN0183535474-16">Discussion</hd> <p>The current study aimed to investigate the technical adequacy of a Spanish-language writing screening instrument for kindergarten students. Overall, the correlations between TR and oral storytelling skills were slightly lower than those for FWL. In fact, a noteworthy positive correlation was observed between FWL and both early writing skills and oral storytelling skills, with the exception of phoneme segmentation. Overall, the results exhibit similarities to prior studies conducted in kindergarten settings, wherein the observed correlations tend to fall within the moderate range (e.g., Coker & Ritchey, [<reflink idref="bib16" id="ref117">16</reflink>]). Furthermore, an initial analysis was undertaken to explore the factorial structure of the EGWA-K. Both exploratory and confirmatory factor analyses revealed the presence of two factors, and the measurement model used in this study proved to be invariant across genders. One factor included the number of accurately spelled words generated from the pictures, the number of accurately spelled words written without visual support, and the number of accurately segmented phonemes in one minute. This first factor is related to TS (i.e., handwriting fluency and spelling), and it has been considered a necessary component skill for writing (Berninger, [<reflink idref="bib5" id="ref118">5</reflink>]; Graham et al., [<reflink idref="bib25" id="ref119">25</reflink>]). The underlying factor is the ability to write alphabet letters accurately with speed within a specified time and with phonological awareness (Kim et al., [<reflink idref="bib44" id="ref120">44</reflink>]). In fact, previous research offers substantial evidence of the pivotal role played by transcription skills, which include spelling and phonological awareness, in predicting both the writing quality and productivity of kindergarten children. Studies specifically conducted within kindergarten settings have consistently illustrated the impact of spelling skills on both writing quality (e.g., Kim et al., [<reflink idref="bib44" id="ref121">44</reflink>]; Ritchey et al., [<reflink idref="bib62" id="ref122">62</reflink>]) and writing productivity (e.g., Kent et al., [<reflink idref="bib39" id="ref123">39</reflink>]; Kim et al., [<reflink idref="bib42" id="ref124">42</reflink>]; Puranik & Al Otaiba, [<reflink idref="bib56" id="ref125">56</reflink>]). The second factor included the number of unique words and T-units in the oral narrative and narrative structure. This second factor is related to narrative competence and has also been demonstrated to be a strong predictor of writing development in early childhood (Pinto et al., [<reflink idref="bib55" id="ref126">55</reflink>]). As students acquire lower-level transcription skills, they also develop higher-order oral language skills, which are necessary for text generation. In this sense, the development of oral narrative language should also contribute to the development of written narrative skills.</p> <hd id="AN0183535474-17">Diagnostic accuracy of the EGWA-K</hd> <p>In the present study, we also examined whether the two-factor solution (i.e., transcription skills and narrative competence) of the EGWA-K could predict the risk status of writing at the end of kindergarten. Overall, there has been limited empirical inquiry into the technical adequacy of writing screening instruments for young children, with only a few exceptions found in the English language (e.g., Coker & Ritchey, [<reflink idref="bib17" id="ref127">17</reflink>]; Justi et al., [<reflink idref="bib36" id="ref128">36</reflink>]; Keller-Margulis et al., [<reflink idref="bib37" id="ref129">37</reflink>]; Puranik et al., [<reflink idref="bib59" id="ref130">59</reflink>]) and no available research in the Spanish language, to the best of our knowledge. Drawing upon the insights of Coker and Ritchey ([<reflink idref="bib17" id="ref131">17</reflink>]), the use of scientifically validated instruments for identifying students at risk of developing writing difficulties and monitoring their learning progress is of paramount importance. Early identification of such students is likely to engender more favorable outcomes in terms of their resistance to improvement compared to delayed intervention strategies. A notable debate exists in the literature regarding whether the diagnostic precision of such instruments is improved when the teacher's evaluation is used as the criterion (Coker & Ritchey, [<reflink idref="bib17" id="ref132">17</reflink>]). Therefore, we investigated whether the inclusion of teacher ratings could enhance the prediction of risk status.</p> <p>When analyzing the diagnostic accuracy of the factorial structure of the EGWA-K using criterion measures based on letter performance and teacher rating, we found greater accuracy when using the standardized writing task as the criterion. An essential aspect of preschoolers' writing proficiency involves the ability to accurately produce individual letters (Puranik et al., [<reflink idref="bib57" id="ref133">57</reflink>]). Therefore, the choice of this criterion measure is justified because children's proficiency in forming alphabet letters not only indicates their developing understanding of orthographic principles (Ritchey, [<reflink idref="bib61" id="ref134">61</reflink>]) but also demonstrates strong predictive power for their early-stage writing fluency, spelling, and composition skills (Graham et al., [<reflink idref="bib25" id="ref135">25</reflink>]). In line with the findings of recent related research, researchers have explored screening approaches to identify writing challenges or early writing proficiency in children at risk for literacy-related issues, particularly in kindergarten populations. The study of Thomas et al. serves as a notable example of this research approach. When comparing the findings of the current study to those of Thomas et al., some similarities were observed. Thomas et al. reported that at-risk children exhibited less sophisticated name writing, lower letter writing, and invented spelling scores, as did a reduced association between written and verbal responses in story composition. Similarly, our study identified similar challenges, emphasizing the importance of transcription skills and narrative competence in the early writing development of kindergarten-aged children.</p> <p>While the EGWA-K demonstrated a high sensitivity in identifying individuals truly at risk of writing difficulties (90%), its specificity was 71%, which may be perceived as relatively lower than sensitivity. This finding suggested that the instrument might have a greater risk of identifying false positives. It is important to acknowledge that an accuracy of 71% in identifying those not at risk raises questions about the instrument's robustness in this respect. Nevertheless, in the context of assessments conducted in kindergarten-age children, concern regarding the number of false positives should be contextualized within the framework of early detection. Given the early developmental stage of the children being assessed, a certain level of false positives may be anticipated. This is because young children are still in the process of acquiring and refining various skills, and their performance on assessment tasks may vary. As such, some level of overidentification can be expected, and this may not necessarily indicate a fundamental flaw in the screening tool. Instead, the findings underscore the need for careful consideration and interpretation of assessment results, considering the developmental stage and potential variations in performance typical of kindergarten-age children.</p> <p>In contrast, when TR was used as the criterion, the specificity and AUC were lower. These results differ from those obtained by Coker and Ritchey ([<reflink idref="bib17" id="ref136">17</reflink>]), where writing measures were more accurate when TR was used as the criterion. However, there are some differences between the study presented here and that conducted by those authors. For example, screening measures were administered in the winter of their preschool year to predict risk status in the spring. The authors suggested that measures such as letter writing, which has been shown to be a good predictor of writing (Ritchey, [<reflink idref="bib61" id="ref137">61</reflink>]), would likely be a measure with greater diagnostic accuracy if they are administered in the fall, as it is a fundamental writing skill. Additionally, the Letter Name Fluency measure could be a better predictor if it were administered in the fall rather than in the winter. Finally, because sentence writing involves transcription and composition skills, it could be a more accurate predictor of risk if it was administered in the spring of preschool or even in the fall of first grade. In the present study, the test was administered in the spring at the end of the kindergarten year. The fundamental reason for this timing is that the curriculum in Spain does not require students to start writing but instead allows educational centers to decide autonomously. However, due to pressure from families for their children to start literacy, it is usually common for all schools to introduce writing letters and words during this stage of schooling. Additionally, another important difference between the cited studies (i.e., Coker & Ritchey, [<reflink idref="bib17" id="ref138">17</reflink>]) and the present study is the use of linguistic measures that were not used in those studies. However, our results suggest that an approach for universal screening of writing difficulties may encompass measures not only of transcription skills but also of oral language skills, such as oral narrative proficiency.</p> <hd id="AN0183535474-18">Limitations and directions for future research</hd> <p>This study, however, is not without limitations. It is important to acknowledge these limitations and highlight potential directions for future research to advance our understanding of writing screening research. First, given the limited amount of research on writing screenings, especially in the Spanish language, these findings present a significant initial stride. However, future research on writing screens should investigate whether other writing measures and oral language skills may also improve the classification. For instance, as suggested by Coker and Ritchey ([<reflink idref="bib17" id="ref139">17</reflink>]), vocabulary or syntax should also be investigated as screening measures given the relationship between oral language and writing development. Second, it is important to replicate these findings in different samples since the children in this cohort experienced a few months of school closure due to the COVID-19 pandemic. Third, this study used the composite score, but future research should examine the different measures within the EGWA-K. Fourth, two criterion measures were utilized in this study to estimate students' writing and risk status. The criterion measures of free letter writing and TR revealed a weak correlation (0.28), implying that they captured a similar yet not identical range of skills. In fact, the scores of the "teacher evaluation" variable included in the analysis provide information about not only writing proficiency but also phonological awareness and communicative abilities. Instead, the second criterion is focused only on writing proficiency. Fifth, only concurrent validity was assessed. In future research, it would be beneficial to explore the predictive validity of this scale by examining children's scores on actual writing tasks beyond Grade 2. Finally, while the present study employed a universal screening framework, it is important to note that the data collection was conducted at a single time point and included only those students whose parents provided consent. To enhance the technical validity of early writing measures and assess their capacity to estimate growth and respond to instruction in kindergarten, future research should explore the utilization of these measures across multiple screening time points.</p> <hd id="AN0183535474-19">Implications for practice</hd> <p>Assessing early writing risk can help practitioners make informed instructional decisions to better support foundational writing skills. The utilization of the EGWA-K as a screening tool for identifying early writing difficulties offers several benefits for practitioners. Considering the widespread implementation of response to intervention (RtI) models, educators and school administrators require robust screening instruments that can effectively identify students who may be at risk of encountering early writing challenges. Teachers may choose to screen all students and then continuously monitor some students (e.g., 10%) more frequently than others. Currently, there are no well-validated screening assessments for early writing in the Spanish language. The results of this study reveal that transcription and narrative competence show considerable promise as a part of universal screening for writing difficulties in kindergarten.</p> <hd id="AN0183535474-20">Conclusions</hd> <p>To summarize, this research on the technical adequacy of early writing assessment for screening purposes contributes to the limited body of research conducted on early screening measures in writing (for a systematic review, see Balade et al., [<reflink idref="bib4" id="ref140">4</reflink>]). The primary conclusion drawn from this study is that the EGWA-K demonstrates considerable effectiveness in identifying and distinguishing kindergarten children at risk for writing difficulties. The use of norm-referenced writing tests indicates the tool's strong capability in accurately identifying individuals at risk. Furthermore, incorporating teacher ratings as a criterion measure also reflects positively on the EGWA-K's ability to discern at-risk individuals, albeit with slightly less precision compared to the norm-referenced tests alone. The combination of norm-referenced writing tests and teacher ratings notably enhances the tool's discriminative power, emphasizing its robustness in distinguishing between the two groups. These findings suggest that it may be possible to accurately identify which students may be at risk for writing difficulties within the kindergarten setting. The results of this study further support the limitations of existing studies that suggest that measures of early writing and oral language skills are promising in kindergarten.</p> <hd id="AN0183535474-21">Acknowledgements</hd> <p>The authors would like to thank all the participant schools, teachers, students, and families.</p> <hd id="AN0183535474-22">Funding</hd> <p>Grant PID2019-108419RB-100 funded by MCIN/AEI/10.130.39/501100011033, with the PI as the first author and Co-IP as the second author.</p> <p>Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature.</p> <hd id="AN0183535474-23">Data availability</hd> <p>Not applicable.</p> <hd id="AN0183535474-24">Code Availability</hd> <p>Not applicable.</p> <hd id="AN0183535474-25">Declarations</hd> <p></p> <hd id="AN0183535474-26">Conflict of interest</hd> <p>We have no known conflict of interest to disclose.</p> <hd id="AN0183535474-27">Publisher's Note</hd> <p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p> <ref id="AN0183535474-28"> <title> References </title> <blist> <bibl id="bib1" idref="ref41" type="bt">1</bibl> <bibtext> Abbott RD, Berninger VW. 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  Data: <searchLink fieldCode="AR" term="%22Juan+E%2E+Jiménez%22">Juan E. Jiménez</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-7466-8340">0000-0002-7466-8340</externalLink>)<br /><searchLink fieldCode="AR" term="%22Cristina+Rodríguez%22">Cristina Rodríguez</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0001-9929-9767">0000-0001-9929-9767</externalLink>)<br /><searchLink fieldCode="AR" term="%22Jennifer+Balade%22">Jennifer Balade</searchLink> (ORCID <externalLink term="https://orcid.org/0009-0005-4917-7506">0009-0005-4917-7506</externalLink>)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Reading+and+Writing%3A+An+Interdisciplinary+Journal%22"><i>Reading and Writing: An Interdisciplinary Journal</i></searchLink>. 2025 38(2):397-424.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 28
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2025
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Audience
  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Early+Childhood+Education%22">Early Childhood Education</searchLink><br /><searchLink fieldCode="EL" term="%22Elementary+Education%22">Elementary Education</searchLink><br /><searchLink fieldCode="EL" term="%22Kindergarten%22">Kindergarten</searchLink><br /><searchLink fieldCode="EL" term="%22Primary+Education%22">Primary Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Kindergarten%22">Kindergarten</searchLink><br /><searchLink fieldCode="DE" term="%22Writing+Evaluation%22">Writing Evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Writing+Skills%22">Writing Skills</searchLink><br /><searchLink fieldCode="DE" term="%22Functional+Literacy%22">Functional Literacy</searchLink><br /><searchLink fieldCode="DE" term="%22Writing+Difficulties%22">Writing Difficulties</searchLink><br /><searchLink fieldCode="DE" term="%22At+Risk+Students%22">At Risk Students</searchLink><br /><searchLink fieldCode="DE" term="%22Spanish+Speaking%22">Spanish Speaking</searchLink><br /><searchLink fieldCode="DE" term="%22Ability+Identification%22">Ability Identification</searchLink><br /><searchLink fieldCode="DE" term="%22Test+Reliability%22">Test Reliability</searchLink><br /><searchLink fieldCode="DE" term="%22Test+Validity%22">Test Validity</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1007/s11145-024-10518-7
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0922-4777<br />1573-0905
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The main aim of this study was to evaluate the Early Grade Writing Assessment for Kindergarten (EGWA-K), which is grounded in foundational literacy skills, for its validity and diagnostic accuracy in identifying children at risk of developing early learning disabilities in writing (LDW). To the best of our knowledge, no such tool exists for Spanish-speaking children. A sample of 363 Spanish kindergarten children aged 4.7 to 6.6 years was selected for this purpose. The EGWA-K protocol, comprising four tasks (i.e., phonological awareness, writing words from pictures, free writing of words, and oral narrative), was administered to the sample. Additionally, two criterion tasks based on free letter writing and teacher ratings were included for validation purposes. First, an exploratory factor analysis (EFA) was conducted using parallel analysis to determine the dimensionality of the EGWA-K, which was confirmed by a confirmatory factor analysis (CFA) yielding two factors (one related to transcription ability and the other to narrative competence). Additionally, measurement invariance was confirmed at the configural, metric, scalar, and residual levels by gender. The EGWA-K had an acceptable area under the ROC curve (AUC in the 0.87 range), particularly when free letter writing was utilized as the criterion measure, with adequate sensitivity (0.90) and specificity (0.71) indices. Therefore, a reliable and construct-valid screening tool such as the EGWA-K is now available for the early identification of LDW in Spanish kindergarten children.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2025
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1461752
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1461752
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s11145-024-10518-7
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 28
        StartPage: 397
    Subjects:
      – SubjectFull: Kindergarten
        Type: general
      – SubjectFull: Writing Evaluation
        Type: general
      – SubjectFull: Writing Skills
        Type: general
      – SubjectFull: Functional Literacy
        Type: general
      – SubjectFull: Writing Difficulties
        Type: general
      – SubjectFull: At Risk Students
        Type: general
      – SubjectFull: Spanish Speaking
        Type: general
      – SubjectFull: Ability Identification
        Type: general
      – SubjectFull: Test Reliability
        Type: general
      – SubjectFull: Test Validity
        Type: general
    Titles:
      – TitleFull: Identifying Kindergarteners At-Risk of Writing Difficulties Based on Foundational Literacy Skills
        Type: main
  BibRelationships:
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          Name:
            NameFull: Juan E. Jiménez
      – PersonEntity:
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            NameFull: Cristina Rodríguez
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            NameFull: Jennifer Balade
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            – D: 01
              M: 02
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 0922-4777
            – Type: issn-electronic
              Value: 1573-0905
          Numbering:
            – Type: volume
              Value: 38
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: Reading and Writing: An Interdisciplinary Journal
              Type: main
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