Emergent literacy refers to the foundational knowledge and skills that precede formal reading and writing instruction, including phonological awareness, morphological awareness, orthographic awareness, and oral vocabulary. Researchers often divide these precursors into code-related skills, such as alphabet knowledge and print concepts, and meaning-related skills, such as vocabulary and listening comprehension. Because these early abilities reliably predict later reading fluency and comprehension, identifying where autistic children diverge from their peers has become a pressing question for educators and clinicians alike.

Most previous studies of emergent literacy in autism have been conducted in English-speaking or other alphabetic-language contexts. Chinese presents a fundamentally different challenge for young readers. Unlike alphabetic letters, which map onto phonemes, each Chinese character represents a tonal syllable and a unit of meaning. Characters are visually complex, built from stroke patterns, and many are semantic-phonetic compounds containing a radical that hints at meaning and another that suggests pronunciation. Learning to read Chinese therefore places heavy demands on visual memory and on the ability to perceive and process morphological structure.

The research team, led by Zhuo Chen of Shaanxi Normal University together with colleagues at Texas A&M University, recruited children from four inclusive kindergartens serving working-class families. The autistic and typically developing groups were closely matched in age and nonverbal reasoning as measured by Raven’s Colored Progressive Matrices. Autism diagnoses were confirmed with the Autism Diagnostic Observation Schedule, and all participating autistic children could produce short sentences, understand oral instructions, and use spoken language for basic communication. None of the kindergartens provided formal literacy instruction, so the skills measured reflected spontaneous early development rather than classroom teaching.

Each child completed a battery of assessments covering working memory, inhibitory control, rapid automatized naming, phonological awareness through a syllable deletion task, morphological awareness through a compounding construction task, orthographic awareness through tasks distinguishing real characters from pseudo-characters and legal stroke patterns from illegal ones, character recognition, and receptive and expressive vocabulary. The researchers then applied independent-sample t-tests with Bonferroni correction and hierarchical regression models to compare groups and identify predictors of character recognition and vocabulary knowledge.

The results revealed a strikingly uneven profile. Children with autism performed significantly worse than their peers on phonological awareness, morphological awareness, orthographic awareness, and both receptive and expressive vocabulary. They also showed weaker working memory and inhibitory control. Yet on character recognition and rapid automatized naming, the two groups were statistically indistinguishable. The authors suggest that a detail-focused cognitive processing style, long documented in autism, may help these children extract the visual patterns of Chinese characters with unusual precision, laying a foundation for successful decoding despite broader language difficulties.

Regression analyses showed that autism severity, nonverbal reasoning, inhibitory control, rapid naming, phonological awareness, and orthographic awareness together predicted character recognition among the autistic children, with the full model explaining roughly 87 percent of the variance. For typically developing children, working memory and morphological awareness emerged as additional unique predictors. Notably, orthographic awareness, the understanding of legal stroke patterns and positional rules governing how characters are assembled, contributed significantly to character reading in both groups, underscoring the importance of visual-orthographic discrimination in Chinese literacy acquisition.

The predictors of oral vocabulary told a different story. For autistic children, autism severity, nonverbal reasoning, rapid naming, and morphological awareness significantly predicted receptive vocabulary, while expressive vocabulary depended heavily on receptive vocabulary itself. For typically developing children, morphological awareness predicted both receptive and expressive vocabulary. The authors interpret this asymmetry cautiously: morphological awareness appears strongly tied to word meaning across both groups, but expressive language development in autism likely involves additional factors beyond emergent literacy skills, and the field’s findings on receptive-expressive gaps in autism have been mixed.

Why do autistic Chinese children lag specifically in phonological awareness? The study’s syllable deletion task required children to manipulate sound units mentally, a process demanding complex cognitive and linguistic control. Earlier work suggests autistic children fare better on simpler phoneme isolation tasks than on blending and deletion, and difficulties with social interaction and language comprehension may compound the challenge in Chinese, where syllable awareness develops largely through language exposure. Similarly, delays in orthographic awareness may reflect differences in visual processing and limited exposure to written Chinese during the preschool years.

The findings carry practical weight for educators. Rather than treating autistic children solely through the lens of deficit, the authors recommend building on their apparent strength in character recognition to expand vocabulary knowledge, using naturalistic teaching, peer activities, and digital tools that make language visually concrete. Because the study was cross-sectional and involved a relatively small sample of verbally fluent children in one region, the authors caution that causal conclusions cannot yet be drawn, and they call for longitudinal research including minimally verbal autistic children. Still, the work marks an important step toward literacy interventions tailored to autistic learners in non-alphabetic languages, where the road to reading is charted by strokes and radicals rather than letters and sounds.

Subject of Research: Emergent literacy development and its contribution to character recognition and oral vocabulary in Chinese-speaking kindergarteners with autism spectrum disorder.

Article Title: The Contribution of Emergent Literacy Skills to the Development of Character Recognition and Oral Vocabulary Knowledge Among Children With Autism Spectrum Disorder: The Case of Kindergarteners in China

Article References: Chen, Z., Kuo, L.-J., Dixon, L. Q., Han, C.-L., & Ma, Y. (2026). The Contribution of Emergent Literacy Skills to the Development of Character Recognition and Oral Vocabulary Knowledge Among Children With Autism Spectrum Disorder: The Case of Kindergarteners in China. Journal of Autism and Developmental Disorders. https://doi.org/10.1007/s10803-026-07514-x

Image Credits: AI Generated

DOI: 10.1007/s10803-026-07514-x

Keywords: autism spectrum disorder, emergent literacy, character recognition, oral vocabulary, phonological awareness, morphological awareness, orthographic awareness, Chinese language, kindergarten, rapid automatized naming, inhibitory control, working memory

The research, conducted by Jin-long Liang and Xin-ling Cui of the College of Education Sciences at Northwest Normal University in Lanzhou, China, drew on caregiver-reported data from the KIT longitudinal study, formally known as the Kids in Taiwan: National Longitudinal Study of Child Development and Care. The analytic sample comprised 1,694 children, each assessed at approximately 36, 48, 60, and 72 months of age. By tracking the same children at four points across three years, the researchers could ask a question that single-snapshot studies cannot answer: does memory at one age predict literacy skills a year later, above and beyond what the child’s literacy level already suggested?

Emergent literacy, the construct at the heart of the study, refers to the precocious skills that precede formal reading instruction. In this dataset, it was measured with six caregiver-rated items capturing a child’s understanding of common signs and pictorial symbols such as traffic lights, the ability to orient a book correctly, awareness that a picture book’s cover carries information such as the title and author, knowledge of where print begins on a page, the capacity to recognize simple Chinese characters such as one’s own name, and the ability to express ideas through drawings or written symbols like drawing diaries or object lists. Memory, by contrast, was assessed with a broader 18-item scale that included pretend play, recalling and stating personal details such as age, birth month, and telephone numbers, counting accurately to 21 and later to 100, identifying previously seen storybooks, and distinguishing living from nonliving things.

At the simplest descriptive level, the results confirmed what developmental scientists would expect: average scores on both constructs climbed steadily with age, and children who scored high on memory at any given wave also tended to score high on emergent literacy at that same wave, and at every other wave. But the study’s real contribution lies in how it disentangled the direction of these associations over time. The researchers employed two complementary statistical frameworks. The first, a traditional cross-lagged panel model, or CLPM, estimates overall longitudinal associations between the two constructs across the four waves. The second, a random-intercept cross-lagged panel model, or RI-CLPM, is a more recent refinement that separates stable, trait-like differences between children from time-specific deviations within each child, a distinction that has become central to modern longitudinal methodology.

The traditional CLPM told a strikingly consistent story about memory. In all three one-year intervals, memory scores prospectively predicted subsequent emergent literacy scores, even after accounting for prior literacy levels. Emergent literacy showed the reverse pattern in two of the three intervals, prospectively predicting later memory. In other words, when the two constructs were analyzed with the conventional approach, the pathway running from memory to literacy appeared somewhat more robust than the pathway running from literacy back to memory, though both directions were present in the data.

The RI-CLPM, however, is where the study delivers its most technically important insight. When the model separated each child’s stable overall standing from their wave-specific deviations, the correlation between the stable between-child components of memory and emergent literacy was a remarkable 0.81. Children who are generally stronger in memory relative to their peers are, to an extraordinary degree, also the children who are generally stronger in emergent literacy. This single statistic captures the substantial overlap between the two capacities at the level of stable individual differences, and it suggests that much of the association reported in earlier cross-sectional work may reflect this shared underlying profile rather than dynamic developmental influence.

Yet the within-child results demonstrate that the story does not end with stable traits. At the within-child level, deviations in memory were positively associated with subsequent deviations in emergent literacy across all three intervals, and deviations in emergent literacy were likewise positively associated with subsequent deviations in memory across all three intervals. This means that when a child performed better than their own typical level in memory at one assessment, they tended to perform better than their own typical level in emergent literacy at the next assessment, and vice versa. The bidirectional relationship, in other words, is not merely an artifact of some children being generally more advanced than others; it unfolds dynamically within individual developmental trajectories.

One temporal detail stands out. The largest estimated coefficient for the pathway from emergent literacy to memory appeared in the interval from 60 to 72 months, spanning the transition from age five to age six. This is precisely the period during which many children begin encountering formal or semi-formal literacy instruction, and the finding hints that as children’s print-related skills consolidate, they may increasingly feed back into the memory processes that support learning more broadly. The authors note that the prospective association from memory to emergent literacy was more consistent across the two modeling approaches than the reverse pathway, suggesting that memory may serve as the somewhat more reliable developmental engine during this age window, even as literacy skills exert their own growing influence.

Methodologically, the study is a textbook demonstration of why the choice of longitudinal model matters. Had the researchers relied solely on the traditional CLPM, they might have overinterpreted cross-lagged paths that partly reflect stable trait-level covariation. Had they relied solely on the RI-CLPM, they might have dismissed genuine within-child dynamics. By running both models on the same four-wave dataset, Liang and Cui were able to show that the longitudinal relation between memory and emergent literacy involves both stable between-child differences and time-specific within-child variation, a dual conclusion that neither model alone could have delivered. The analysis used full information maximum likelihood to handle missing data and robust estimation procedures, and the work was supported by research funding from the College of Education Sciences at Northwest Normal University.

The practical implications reach into homes, preschools, and early intervention programs. If memory skills reliably foreshadow literacy growth from age three onward, then activities that exercise young children’s recall, sequencing, and symbolic reasoning, from pretend play to storybook recognition, may pay dividends in later reading readiness. Conversely, the feedback loop from emergent literacy to memory suggests that early exposure to books, print conventions, and symbolic expression is not merely preparation for reading but an active contributor to broader cognitive development. Because the study relied on caregiver reports and secondary analysis of an existing cohort, the authors are careful to frame the findings as associations rather than causal proof, and they call for continued work with direct assessments and additional populations. Still, for parents and educators wondering whether the toddler memorizing songs and the preschooler scribbling a drawing diary are on connected journeys, this research offers a resounding answer: the two journeys are woven together, each one helping to pull the other forward through the critical years before formal schooling begins.

Subject of Research: Bidirectional longitudinal associations between memory and emergent literacy in preschool children aged 3 to 6 years.

Article Title: Longitudinal associations between memory and emergent literacy from 3 to 6 years of age: a four-wave random-intercept cross-lagged panel study

Article References: Liang, J.-L., & Cui, X.-L. (2026). Longitudinal associations between memory and emergent literacy from 3 to 6 years of age: a four-wave random-intercept cross-lagged panel study. BMC Psychology. https://doi.org/10.1186/s40359-026-05598-9

Image Credits: AI Generated

DOI: 10.1186/s40359-026-05598-9

Keywords: memory, emergent literacy, early childhood, longitudinal study, cross-lagged panel model, random-intercept CLPM, cognitive development, language development, preschool children, KIT study, child development, developmental psychology