Introduction

The ability to effectively communicate thoughts, ideas, and information is fundamental in our increasingly interconnected and information-rich society. With significant implications for academic success, future workplace experiences, and emotional well-being (Graham & Hall, 2015; Kim et al., 2015), proficient writing is a crucial skill for individuals at all stages (OECD, 2021). However, despite the profound importance of writing, it is often overlooked in educational research and policy, especially in comparison with areas like reading (Campbell et al., 2019; Clay, 2001). Additionally, a major limitation of existing research on writing skills is a prevailing focus on opaque orthographies (Arfé et al., 2016). Opaque orthographies where there is a less predictable relationship between phonemes and graphemes, such as in English are notably more complex. This complexity could potentially influence the development and execution of writing skills. This research bias has significant implications, as findings derived from opaque orthographies may not fully translate to transparent orthographies, where phoneme-grapheme correspondence is straightforward, such as in Spanish. Importantly, learning to write begins early in life, and in fact, early writing skills have been found to predict later academic achievement (Rohloff et al., 2022), including grades and standardized test scores (Kent et al., 2014). This connection further underscores the findings of the National Early Literacy Panel (2008), which emphasized the pivotal role of children’s early writing skills in predicting future academic success. Despite the relevance of early writing skills, research on this life stage remains scarce. In light of these considerations, it is imperative that we focus on the development of early writing skills especially in transparent languages. Kindergarten children display varied degrees of proficiency in writing skills (Puranik & Alotaiba, 2012; Tortorelli et al., 2022), making it paramount to investigate and comprehend the underlying mechanisms of early writing skills, such as oral language and transcription skills, and their ability to contribute to writing composition, which is the ultimate goal of writing.

Writing Skills in Kindergarten

Writing development, as seen through the lens of theoretical models, is a multifaceted process, involving a delicate interplay between numerous cognitive and linguistic factors (Berninger & Swanson, 1994; McCutchen, 2006). It is understood through two key theoretical models: the simple view of writing and the not-so-simple view of writing (Berninger & Winn, 2006; Juel et al., 1986). The simple view identifies transcription and text generation, or ideation, as the core components of writing. Ideation is the translation of ideas into oral language; thus, oral language is a proxy of ideation. Transcription involves converting sounds into written symbols, and encompasses spelling and handwriting. Meanwhile, the not-so-simple view extends this perspective by integrating working memory and self-regulatory processes into the writing construct, both of which are supported by empirical evidence (Graham et al., 2012; Hayes & Chenoweth, 2007; Kellogg et al., 2007; Limpo & Alves, 2013). These models coincide with the understanding that writing involves a broad set of skills in which transcription and text generation are crucial (Berninger, 1999; Berninger & Graham, 1998; Juel et al., 1986).

Transcription skills are pivotal to written composition as they free up cognitive resources for higher-order composition processes such as generating ideas and content (Graham, 1990; Graham et al., 1997; Graham & Harris, 2000; McCutchen, 1988, 2006; Scardamalia et al., 1982). Particularly for beginning writers, these transcription skills can be a bottleneck that constrains the generation of text due to their lack of automaticity (Bourdin & Fayol, 2000; Graham & Harris, 2000; McCutchen, 2000, 2006). However, as writers develop, they improve automaticity in spelling and handwriting which can release cognitive resources for higher-order writing tasks, such as generating ideas and arranging them logically (Berninger et al., 2008; Ehri, 2000; Graham et al., 2002; Kim et al., 2011; Puranik & Alotaiba, 2012; Treiman & Bourassa, 2000). Viewed from this perspective, the development of writing follows an anticipated and orderly progression. The ability to generate text, often gauged by oral language skills (e.g., Kent et al., 2014; Kim et al., 2018), is believed to emerge once transcription skills have been mastered; however, there is evidence that suggests that it is also possible for these to emerge in parallel development (Kirby et al., 2021). It is suggested that both transcription and oral language impact writing independently of grade level (Kent & Wanzek, 2016).

Kent and Wanzek (2016) conducted a meta-analysis of studies over the last 25 years, investigating the relationship between transcription skills (handwriting and spelling), oral language skills indicative of text generation, and reading in relation to students’ writing quality and writing production. They found moderate, positive correlations between students’ handwriting and the quality and quantity of their writing across all grade levels from K to 3 and above, but limited effect sizes prohibited further moderator analyses. The data also showed a moderate positive correlation between spelling ability and writing productivity and writing quality, consistent across grade levels. A weak to moderate positive correlation was identified between oral language skills and writing quality, while a weak correlation was found regarding writing productivity. Grade level did not moderate the correlation between oral language skills and either writing quality or productivity. However, due to the considerable between-study variance and significant heterogeneity in effect sizes across all explored relationships, interpretation of results should be undertaken with caution. Of this research, only four studies involved kindergarten children (Adams et al., 2013; Kim et al., 2011; Ritchey et al., 2010; White 2013). None of them measured both productivity and quality of writing, and only one included transcription skills and oral language (Kim et al., 2011). Ritchey et al. (2010) investigated the four most commonly used spelling scoring metrics in the early stages of writing acquisition: total words correct, correct letter sequences, correct sounds, and phonological coding scoring. They also assessed the relationship between children’s spelling performance, determined using these metrics, and students’ phonological awareness and writing abilities among other literacy skills. Their results suggest that these measures provide equivalent indices of spelling skills. They observed moderate relationships between each of these spelling scores and phonological awareness performance, thus confirming the idea that fluent spelling requires consolidated phoneme awareness (Apel & Masterson, 2001; Ehri, 2000), and configuring it as a precursor to transcription. Additionally, they found a moderate relationship between the spelling measures and achievement in the Contextual Writing subtest of the Test of Early Written Language. This test requires students to write a story based on one of two picture prompts. Responses are scored using a 14-point rubric that provides a qualitative performance assessment but does not involve productivity indicators. Kim et al. (2011) found that individual differences in writing are uniquely associated with proficiency in spelling and handwriting. They also found that variations in children’s oral language skills, which include vocabulary, grammatical knowledge, and sentence imitation, were weakly to moderately correlated with writing productivity at the end of kindergarten, even after accounting for spelling, letter-writing fluency, and reading. Notably, the contributions of spelling and handwriting were stronger than those of oral language. Adams et al. (2013) reaffirmed that, after accounting for background variables and reading, spelling made a significant, unique contribution to text production (β = 0.32); however, they did not find a significant effect of handwriting. Although Puranik and Al Otaiba’s study (2012) was excluded due to sample overlap with Kim et al. (2011), their findings remain pertinent. Their research parallels Kim et al. (2011), revealing that after controlling for cognitive-linguistic variables and student background characteristics, handwriting and spelling made unique contributions to kindergarten children’s written productivity. However contrary to Kim et al. (2011), they found no significant contribution of oral language to writing productivity after accounting for handwriting and spelling skills. Of the four mentioned, White (2013) is the only that include oral language skills and quality composition, and demonstrated that receptive language was associated (r = .27) with variance in children’s writing quality.

Expanding on these findings, Kent et al. (2014) investigated the unique and shared roles of attention, transcription, reading, and oral language abilities in a developmental model of writing at the kindergarten level. Moreover, they conducted a longitudinal analysis to study the contribution of these skills from kindergarten to first grade. They found that early literacy skills in reading and spelling, as well as letter-writing fluency indicative of handwriting, were uniquely and positively related to students’ composition fluency in kindergarten. However, oral language did not demonstrate any significant relationship when other factors were accounted for. In addition, their study revealed that literacy skills gained in kindergarten positively influenced both the fluency and quality of writing in the first grade. Yet, letter-writing fluency in kindergarten showed no significant relation to either fluency or quality of writing in the first grade. Interestingly, while kindergarten oral language skills did not uniquely relate to first-grade compositional fluency, they did relate uniquely to the quality of writing in the first grade. This pattern aligns somewhat with a study by White (2013) and was reflected in Kim et al. (2015). The latter explored longitudinal relations of kindergarten transcription, oral language, word reading, and attention skills to writing skills in third grade. Children’s written compositions were evaluated in terms of writing quality, that is, the extent to which ideas were developed and presented in an organized manner. Findings revealed that kindergarten literacy skill, composed of six indicators of word reading, spelling, and oral language, consisting of vocabulary, grammatical knowledge, and sentence memory were positively and independently related to the narrative writing quality of the children’s writing in grade 3. For expository writing quality in grade 3, only literacy skill was uniquely related. In a more recent study, Pinto et al. (2015) analyzed the influence of oral language specifically, oral narrative competence in kindergarten on narrative writing quality in first grade. They found that the structure of the oral narrative was the sole predictive component of narrative competence in written productions. Notably, aspects of oral cohesion and coherence did not necessarily translate to the written format. The structure observed in oral narratives was discovered to predict not only the structure but also the coherence of written narratives.

In conclusion, the specific contribution of oral language to writing productivity is not uniformly established across research; while it is significant in some studies (Kim et al., 2011), others do not corroborate these results (Kent et al., 2014, Puranik et al., 2012). The relationship between writing quality and oral language seems to be more consistent, with all referenced studies identifying a significant relationship (White 2013; Kent et al., 2014; Kim et al., 2015, Pinto et al., 2015). The role of transcription and spelling skills in particular, appears to be reliably linked with both quality (Kent et al., 2014; Kim et al., 2015; Ritchey et al., 2010) and productivity (Adams et al., 2013; Kent et al., 2014; Kim et al., 2011; Puranik & Alotaiba, 2012). In sum, the considerable disparity in outcomes across these studies, coupled with the limited number of investigations focused on kindergarten-age children that incorporate both transcription skills and oral language, amplifies the need for further research in this domain. Notably, none of these studies were conducted in a transparent language context, further emphasizing the gap in this area of research. The present study will therefore examine the contributions of transcription skills and oral language as indicators of text generation to both writing quality and productivity in Spanish-speaking kindergarten children.

Method

Participants

The study involved 208 kindergarten children (102 boys and 106 girls; Mage = 69.45, SD = 5.23). However, 49 did not complete all tasks because not all children attended school consistently due to the COVID-19 pandemic. To address the missing data within our dataset, we used a listwise deletion approach, also known as complete case analysis. This decision was made following a thorough examination of the pattern and the extent of the missing data. Using the MICE package in R (van Buuren & Groothuis-Oudshoorn, 2011) we found that our data were Missing Completely at Random (MCAR). Listwise deletion is an appropriate method when data are MCAR. The technique excludes all cases with missing values for any of the variables. It is straightforward and does not distort the relationships between variables, as can happen with certain data imputation techniques. Consequently, the final sample comprised 159 children (74 boys and 85 girls; Mage = 69.81, SD = 3.32). These children attended seven public and private schools in urban areas, representing diverse socioeconomic backgrounds. The study did not include children with special educational needs, specifically those with sensory impairments, acquired neurological conditions, or other traditionally exclusionary criteria for learning disabilities.

Materials

Most of the tasks used are part of the Early Grade Writing Assessment for Kindergarten (EGWA-K) (Jiménez et al., 2024).

Transcription Measures

Picture Word Writing Task

A dictation-like task with visual support. The children were asked to transcribe the word that matches the image shown. The task included a collection of twelve images, each tied to regular, familiar words of varying length, both short and long. The task involved two scoring methods: one based on word accuracy, where each correctly transcribed word earns a point, and the other based on letter accuracy, where each correctly transcribed letter also earns a point. Neither orthographic irregularities nor differences between uppercase and lowercase letters were factored into the scoring. For the purposes of the present study, scores were determined based on the number of correctly transcribed letters (Cronbach’s α = 0.91).

Free Word Writing

In this task, children were instructed to write words of their choosing, including a word they can write confidently, a short word, and a long word. Two scoring criteria were applied: one focuses on word-level accuracy, where a point is awarded for each correctly transcribed word, and the other on letter-level accuracy, with a point given for each correctly transcribed letter. Words were considered correct if all the letters were included and arranged in the right sequence. Spelling errors, as well as inconsistencies in the use of uppercase and lowercase letters, were not considered in the scoring. The interclass correlation coefficient (ICC) was calculated for this task to determine inter-rater reliability. This measure of written words has demonstrated a high ICC (0.99).

Phoneme Segmentation

The student was asked to articulate the sounds of each pseudoword, thereby assessing their ability to segment the pseudoword phonemically. The set of 20 pseudowords was organized according to level of difficulty, based on syllabic structure, progressing from simple to complex. As such, it was crucial to maintain the prescribed order of presentation. The student’s phonemic accuracy within the first minute was recorded, with a point assigned for each phoneme accurately identified within that time frame (Cronbach’s α = 0.97).

Oral Language Skills

Grammar Knowledge

In this task, children listened to a sentence being read aloud and were required to determine whether it is grammatically correct or incorrect. The task included 16 items that focus on noun-adjective agreement, specifically pertaining to gender and number (e.g., “la tortuga es lentas” representing a mismatch between singular noun and plural adjective; “la comida es malo” illustrating a mismatch between feminine noun and masculine adjective). Performance was evaluated by the number of sentences correctly identified as grammatically accurate or inaccurate (Cronbach’s α = 0.80).

Oral Story Retell

For this task, the examiner read a passage aloud to the participants who were instructed to listen attentively as they would be asked to retell the story in their own words. Participants were provided with as much time as needed to complete their retelling. Children’s retellings were recorded using a standard audio recorder. Later, the examiner scores the retellings by listening to these recordings. The task generated three distinct measures. The first was macro-organization or structure, where children received a score of 0, 1, or 2 points for each dimension of the story structure defined in the rubric, including title, opening, characters, main event, problem, emotion, resolution and closure. The second measure was cohesion, which considered the count of causal and temporal linguistic connectives. All connectors, whether collective or individual, were accounted for. The final measure was productivity, gauged by the total number of words used by the students. For the purpose of this study, the total number of words was the selected measure.

Oral Narrative Task

Children were asked to narrate a story based on an illustration provided. The image depicted an ice cream cart with a vendor and two additional characters: a child who had dropped his ice cream on the ground and an adult who was purchasing an ice cream. The evaluation covered various aspects: (a) Macro-organization: children were scored 0, 1, or 2 points for each story structure component outlined in the rubric (title, opening, characters, main event, problem, emotion, resolution and closure); (b) Cohesion: the count of causal and temporal connectives; (c) Productivity: the number of words, propositions, and sequences of correctly used words; (d) Lexical diversity: the count of unique words; (e) Accuracy: the tally of correct words, with phonetic articulation errors not penalized; (f) Fluency: the number of correct words produced within a minute; (g) Grammaticality: the number of grammatical errors, along with the syntactic complexity of the discourse (number of sentences of varying complexity), and T-units (total number of T-units). For the purpose of this study, scoring was based on the total number of words used.

Writing Composition

Narrative Text Composition

This task was designed to evaluate children’s text composition skills, using a picture prompt. The same picture from the oral narrative task was shown to the children, but in this task, they were encouraged to write the narrative text. Three minutes after the start of the task, the examiner marked the last word written by the child in order to evaluate the different dimensions covered within that interval during the scoring process. The mark was made without interrupting the child’s writing process. The total time taken by the child to complete their writing was also recorded. This task was administered following the oral narrative task. Several dimensions, similar to those in the oral narrative task, were assessed: (a) Macro-organization: children were scored 0, 1, or 2 points for each component of the story structure as per the rubric (title, opening, characters, main event, problem solutions, emotions resolution and closure); (b) Cohesion: the count of causal and temporal connectives; (c) Productivity: the number of words, propositions, and correct word sequences; (d) Lexical diversity: the tally of unique words; (e) Accuracy: the total number of correct words, with spelling errors not penalized; (f) Fluency: the number of correct words produced within three minutes; (g) Grammaticality: the total number of grammatical errors and the usage of punctuation marks, along with the syntactic complexity of the discourse (number of sentences of varying complexity), and T-units (total number of T-units). For the purposes of this study, our focus remained on the total word count as a reflection of productivity—a standard in the field— and macro-organization as an indicator of quality, as in other studies (e.g. Cabell et al., 2022; Puranik et al., 2020).

Data Analysis

The analyses were carried out using the R statistical software (R Core Team, 2021), with the support of the ULLRToolbox (Hernández & Betancort, 2018). The data analysis strategy utilized was Structural Equation Modeling (SEM) using the “Lavaan” package in R (Rosseel, 2012). Latent variables were created for constructs, transcription, and text generation. The outcome measures writing productivity and writing quality were treated as observed variables.

To address the research question, structural equation models were fitted. The model fits were evaluated using multiple indices such as Chi-square statistics, Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA), and Standardized Root Mean Square Residuals (SRMR). It is generally accepted that an excellent model fit is indicated by RMSEA values below 0.08, CFI and TLI values equal to or greater than 0.95, and SRMR equal to or less than 0.05 (Hu & Bentler, 1999). CFI and TLI values greater than 0.90 are also considered acceptable (Kline, 2011).

Prior to the structural equation analysis, the univariate and bivariate distributions were checked, and multinomial normality for the confirmatory factor analysis and structural equation modeling was examined and confirmed. Measurement models were examined to ensure their accuracy and precision.

Results

Descriptive statistics (i.e., means, standard deviations, minimum and maximum scores) and correlations among observed variables are presented in Table 1. According to the recommendations of Gravetter et al. (2020), all skewness and kurtosis values fall within an acceptable range (-2, 2), confirming that the variables are normally distributed for the purpose of structural equation modeling. In terms of the size of the correlations among variables, strong positive correlations were observed between phonological awareness (PA) and Picture Word Writing (Word_Picture) (r = .525), and between Word_Picture and productivity (r = .550), suggesting substantial relationships among these variables. Moderately strong correlations were found between Free Word Writing (Word_Free) and Productivity (r = .379), and between Grammar Knowledge (Syntax) and Macro-organization (quality) (r = .316). These correlations indicate a noteworthy connection between these pairs of variables. Lower but still statistically significant correlations were noted between Syntax and the number of words in the Retell task (Word_Retell) (r = .166), and between Word_Retell and the number of words in the Oral Narrative Task (Word_Narrative) (r = .328), implying weaker but non-negligible relationships. Overall, the correlation matrix demonstrates a range of relationships among variables, which warrants further investigation through more complex analytical methods such as structural equation modeling.

Table 1 Descriptive statistics and correlations between variables
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In order to examine the contribution of transcription skills and oral language skills to productivity and quality in narrative writing, a Structural Equation Model (SEM) was fitted. The fit indices indicated that the proposed structural equation model provided a suitable representation of the underlying data. The chi-square test, which directly tested the difference between observed and predicted covariance matrices, had a non-significant p-value: χ2(28) = 23.972, p = .090. This suggested that there was no substantial difference between the observed data and the values predicted by the model. Additional fit indices further reinforced the model’s adequacy: CFI = 0.973; TLI = 0.953; RMSEA = 0.056. The 90% confidence interval for RMSEA, ranging from 0.000 to 0.100, corroborated this interpretation. However, the upper bound hints at possible room for model refinement. The SRMR value was 0.046.

The study revealed significant associations between observed measures and their latent constructs for both factors: Transcription and Oral Language. All factor loadings were positive and statistically significant for each factor, with values at or exceeding 0.30 (λ range: 0.30–0.49 for Oral Language; λ range: 0.58–0.90 for Transcription), as presented in Fig. 1. Regarding regression, the Transcription factor powerfully predicted both writing quality and productivity. Conversely, while the Oral Language factor was a robust predictor for quality, its predictive capacity for productivity was not statistically significant. A noteworthy observation is the pronounced covariance between the Transcription and Oral language constructs, indicating that elevated scores in Transcription often aligned with higher scores in Oral Language.

Fig. 1
figure 1

Standardized factor loadings for oral language and transcription latent variables, and regression coefficients for writing productivity and quality outcomes. Note: Synt = Grammar Knowledge; Wnar = number of words in Oral Narrative Task; Wret = number of words in Retell task; PA = Phonological Awareness; Wfree = Free word writing; Wpic = Picture Word Writing; OralL = Oral language skills; Trancp = Transcription skills; Prod = Productivity; Qual = Quality

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In summary, the model fit the data well, with all fit indices suggesting a good to excellent fit. The latent constructs of transcription and oral language were significantly represented by their respective observed variables. Transcription showed a significant relationship with both quality and productivity in writing, while Language showed a significant relationship only with quality. The two constructs, transcription and oral language, were also significantly related.

Discussion

The present study set out to explore the contribution of transcription skills and oral language to writing quality and productivity among Spanish-speaking kindergarten children. This was against a background of scarce similar studies conducted in transparent language contexts, as well as a lack of consistency in the findings of previous studies focused on English-speaking populations. Employing Structural Equation Modeling (SEM) for analysis, the study established some crucial findings that not only corroborate but also expand on prior research in intriguing ways.

One of the most striking findings of our study is the prominent role played by transcription skills—including spelling and phonological awareness—in predicting both writing quality and productivity in kindergarten children. This aligns with previous research that has shown that both quality (Kim et al., 2015; Ritchey et al., 2010) and productivity (Adams et al., 2013; Kent et al., 2014; Kim et al., 2011; Puranik & Alotaiba, 2012) are predicted by spelling skills. Our findings are also consistent with those of Kent et al. (2014), which is the only study to have measured both quality and productivity, focusing particularly on compositional fluency. Kent et al. (2014) demonstrated that early literacy skills in reading and spelling, along with letter-writing fluency, were notably linked to both composition fluency and quality in kindergarten and first grade. Our study not only reaffirms these findings but also broadens the scope of Kent et al.‘s research, emphasizing the sustained importance of transcription skills across varied measures of writing performance in a transparent language environment like Spanish. This prominence of transcription in early stages of literacy in transparent orthographies such as Spanish is noteworthy. However, studies with older children in other transparent orthographies, like Italian and Turkish, suggest that the importance of transcription diminishes from the first grade onward (Arfé et al., 2016; Babayiǧit & Stainthorp, 2010).

Our study offers further clarity on the somewhat divergent findings regarding the role of oral language skills in early writing. The specific contribution of oral language to writing productivity remains a contentious point in the literature. Intriguingly, the main disparity in these findings centers on divergent results between Kim et al. (2011) on one hand, and Kent et al. (2014) and Puranik et al. (2012) on the other. Kim et al. (2011) found a significant relationship between oral language and writing productivity, while Kent et al. and Puranik et al. did not support this association. Notably, Kim et al. (2011) and Puranik et al. (2012) drew from the same sample, yet reported different findings. This divergence could be attributable to the different statistical methodologies employed: while Puranik et al. utilized a hierarchical regression analysis with observed variables, Kim et al. conducted a Structural Equation Modeling (SEM). The contrasting conclusions drawn from identical datasets highlight the pivotal influence of methodological decisions on research outcomes. Our findings are more closely aligned to those of the latter authors, indicating that oral language skills did not significantly contribute to writing productivity in kindergarten children when other factors were accounted for. However, oral language did significantly impact writing quality, consistent with studies by White (2013), Kent et al. (2014), Kim et al. (2015), and Pinto et al. (2015). Thus, our research complements the work of Kent et al. (2014) by further delineating the specific contributions of oral language to writing quality and accentuates the need for more targeted research to resolve the inconsistencies surrounding its role in writing productivity.

Our findings offer nuanced contributions to existing theoretical frameworks on early writing development, particularly the simple and not-so-simple views of writing. In line with the simple view, we found that transcription skills significantly predicted both writing quality and productivity, reaffirming their foundational role in the writing process. However, our study introduces additional complexity by revealing the significance of oral language skills, especially in writing quality. Importantly, both transcription and oral language skills had similar impacts on writing quality, challenging the conventional notion of transcription as a ‘bottleneck’ that constrains cognitive resources for higher-order writing tasks (Graham, 1990; McCutchen, 2000).

In our exploration of early writing development, the Structural Equation Model we employed unveiled a significant covariance between oral language and transcription skills among kindergarten-aged children. This intertwining supports the ‘not-so-simple’ view of writing, suggesting it’s a multifaceted skill shaped by multiple cognitive and linguistic processes. Our results resonate with Cabell et al. (2022), emphasizing that early oral language development has a substantial impact on subsequent spelling and written composition skills. This aligns with the moderate relationship between oral language and spelling as outlined by the National Early Literacy Panel (2008). Our research, however, underscores the particular significance of this relationship during the initial stages of literacy development, challenging the conventional bottleneck theory. It underscores that both oral language and transcription are fundamental, closely intertwined skills. Consequently, equal weight should be assigned to both in early education to holistically nurture writing proficiency.

Our study, along with the recent work by Kirby et al. (2021), has significant practical implications for early childhood education curricula. Kirby et al.‘s intervention highlights the potential of targeted oral narrative instruction to improve writing quality in kindergarteners. Given our own findings that both transcription skills and oral language play a nuanced role in writing development, it would be prudent for educators to design balanced literacy programs. These programs should not only emphasize transcription skills like spelling and handwriting but also integrate focused oral language activities that are geared toward enriching narrative structure and vocabulary. Such a comprehensive approach could serve to holistically develop both writing quality and productivity from an early age, setting the foundation for more advanced literacy skills.

Limitations and Future Directions

While our study makes a valuable contribution, certain limitations must be acknowledged. One notable limitation is our focus on transcription skills, which in this study encompassed spelling skills and phonological awareness, but did not include measures of handwriting skills. Handwriting, especially in the early stages of writing skill acquisition, is closely interrelated with spelling, making them interdependent. Thus, future studies should consider incorporating assessments of handwriting skills to gain a comprehensive understanding of transcription skills in young learners. Additionally, the sample size could be enhanced to obtain more robust and generalizable findings. Another constraint is our reliance on observed variables for outcomes, rather than latent variables, which may affect the accuracy of our results. Our cross-sectional design also limits our ability to deduce causal links or investigate the developmental trajectories of these relationships longitudinally. For future research, it would be beneficial to incorporate other pertinent variables, such as executive functions, as highlighted by the “not-so-simple” view of writing. Inclusion of such variables would offer a more precise understanding of the myriad factors that affect early writing development and provide a richer framework for interpretation of the complex interrelationships found by the present study.

Conclusion

Our study offers a detailed understanding of the foundational skills that contribute to early writing development, specifically focusing on kindergarten-aged children. One significant contribution of our research is the revelation of a notable covariance between oral language and spelling skills. This supports the “not-so-simple” view of writing and affirms that these foundational elements are intimately linked, especially in the early stages of literacy development. Furthermore, our results provide empirical evidence that both oral language and transcription skills—such as spelling—play pivotal roles in writing composition. Oral language was a significant predictor of writing quality, but not productivity, thereby challenging simplified views of oral language as having a less critical role in early writing development. On the other hand, transcription skills were found to be a strong predictor for both writing quality and productivity, reinforcing the assertion of their foundational importance in the writing process. In light of these findings, our study suggests that both oral language and transcription should receive equal emphasis in early education settings. The aim should be to facilitate a more holistic development of writing skills, covering both productivity and quality aspects of writing.