# Beyond phonemic awareness: The alphabetic principle predicts reading acquisition in a nationwide longitudinal study

Paul Gioia, Johannes C Ziegler, Jerome Deauvieau

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Paul Gioia, Johannes C Ziegler, Jerome Deauvieau. Beyond phonemic awareness: The alphabetic principle predicts reading acquisition in a nationwide longitudinal study. Cognition, 2026, 271, pp.106457. 10.1016/j.cognition.2026.106457. hal-05486039

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# Beyond phonemic awareness: The alphabetic principle predicts reading acquisition in a nationwide longitudinal study

Paul Gioia<sup>a</sup>, Johannes C. Ziegler<sup>a,*</sup>, Jerome Deauvieau<sup>b</sup>

## ARTICLE INFO

**Keywords:**

Phoneme awareness

Knowledge of the alphabetic principle

Phonics

Decoding

Reading

## ABSTRACT

Phoneme awareness (PA) is undoubtedly the most important and well-studied predictor of reading development. Yet, 20 years ago, Castles and Colheart made the provocative claim that there was no convincing evidence for the causal role of PA in learning-to-read because previous studies typically failed to control for pre-reading skills. In the present study, we leveraged a unique opportunity to analyze data from a large-scale longitudinal investigation of reading development conducted nation-wide among all first graders in France (i.e., *N* = 810,328 children). We estimated not only the direct effect of PA on reading fluency measured one year later, but also its interaction effects with letter-knowledge (LK), knowledge of the alphabetic principle (KAP), and oral comprehension (OC). Our results show that the direct effects of PA on later reading fluency are moderated by OC, LK and KAP. Specifically, PA contributes to later reading outcomes only among children with strong KAP, and good LK and OC. We highlight the central role of KAP as a key predictor that has often been acknowledged in theory but rarely measured in empirical research. These findings indicate that phoneme awareness supports reading development only in the context of sufficient alphabetic knowledge, challenging strong causal accounts of PA in early reading acquisition.

## 1. Introduction

Research on reading development has clearly established that variations in phonological skills are the major cause of variations in how well children are able to learn to read (Goswami & Bryant, 1990; Melby-Lervåg, Lyster, & Hulme, 2012; Snowling & Melby-Lervåg, 2016; Ziegler & Goswami, 2005). Among phonological skills, Melby-Lervåg et al. (2012) highlighted the “pivotal role of phonemic awareness” (p. 322), which reflects the ability to recognize, identify, or manipulate speech sounds at the phonemic level. The results of Melby-Lervåg et al.’s (2012) meta-analysis converged to suggest that phoneme awareness (PA) yielded the strongest correlation with individual differences in word reading ability across all alphabetic languages, regardless of cross-linguistic differences in orthographic transparency (see also Landerl et al., 2013; Ziegler et al., 2010). PA is thought to be such an important variable in learning-to-read alphabetic scripts because the awareness of phonemes facilitates the development of a basic decoding network (i.e., grapheme-phoneme correspondences), which is the fundamental self-teaching mechanism at the heart of learning-to-read alphabetic scripts (Share, 1995; Ziegler, Perry, & Zorzi, 2014).

In their seminal article, Castles and Colheart (2004) challenged the dominant view regarding the causal role of PA in reading acquisition. They reviewed more than forty articles and examined whether these studies adequately controlled for early literacy skills when assessing the link between PA and subsequent reading abilities. Their central argument was that early literacy skills might influence both PA and later reading outcomes simultaneously, thereby confounding the interpretation of a direct causal link between PA and reading. As none of the reviewed studies had properly accounted for early literacy skills, they concluded that “no single study has conclusively established that phonemic awareness training assists reading or spelling acquisition” (p. 101). A recent systematic review suggests that this issue remains largely unresolved, as most studies published since Castles and Colheart’s article still fail to control for early literacy skills and their interaction with PA (see Gioia, Ziegler, & Deauvieau, 2024).

Hypothetically, there are three potential ways in which phonemic awareness (PA) might influence learning to read. First, PA could exert a causal effect on later reading skills prior to the development of any early literacy skills (e.g., letter knowledge or basic understanding of the alphabetic principle). This is the scenario that Castles and Colheart

<footnote><sup>a</sup> Aix-Marseille University, CNRS, CRPN (UMR 7077), Marseille, France</footnote>

<footnote><sup>b</sup> École normale supérieure (ENS), Paris Science & Lettres (PSL), Centre Maurice Halbwachs (UMR 8097 CNRS/EHESS/ENS/INRAE), Paris, France</footnote>

<footnote>* Corresponding author at: CRPN, Aix-Marseille University, 3, place Victor Hugo, 13003 Marseille, France.
E-mail address: johannes.ziegler@univ-amu.fr (J.C. Ziegler).</footnote>
(2004) primarily addressed. Second, PA might have a direct causal effect on reading skills in the presence of early literacy skills, such that its influence on reading development is independent of the strength of those skills (i.e., whether they are strong, average, or weak). Third, the effect of PA on reading might depend on the level of early literacy skills. For instance, PA may facilitate reading acquisition only when early literacy skills are sufficiently developed, but not when they are weak—implying an interaction between PA and early literacy skills. To disentangle these possibilities, it is crucial to control not only for early literacy skills but also for their potential interaction with PA (see also Hulme, Caravolas, Malkova, & Brigstocke, 2005).

The goal of the present study was to investigate the effects of early literacy variables —and their interactions—on subsequent reading skills, using data from a large-scale, longitudinal study of reading development conducted nationwide among all first graders in France (N = 810,328).

## 1.1. Early literacy skills and the overlooked role of alphabetic knowledge

Early literacy skills are undoubtedly among the strongest predictors of later reading development (Piquard-Kipffer & Sprenger-Charolles, 2013). This is hardly surprising, as one is essentially explaining future reading abilities using already existing or emerging reading-related skills. However, precise definitions of early literacy skills are crucial, particularly because some variables are highly intertwined, while others may be overlooked entirely.

We put forward the claim that knowledge of the alphabetic principle (KAP) is a key variable that is frequently either missing or subsumed under other constructs. We argue that KAP should be measured independently from other early literacy variables and should occupy a central role in the developmental trajectory from early skills to decoding.

KAP is typically defined as the understanding that “letters represent the phonemes in speech” (Ehri, 2015, p. 312). Although many scholars consider it a key stage in the “foundation of literacy” (Byrne, 1998; Ehri, 2015; Ehri & Soffer, 1999; Morais, 1994; Morais, 2015), it has often been treated as a marginal construct positioned between abilities that precede it (e.g., PA, letter knowledge) and those that encapsulate it (e.g., decoding). Remarkably, nearly all authors use similar wording when defining it, such as “discovering,” “mastering,” or “grasping” the alphabetic principle (e.g., Byrne, 1998, p. 20; Castles & Coltheart, 2004, p. 91). Referring to it as a “principle” may have inadvertently reinforced the notion that knowledge of the alphabetic principle is all-or-none.

Early experimental work by Byrne and colleagues (e.g., Byrne, 1998; Byrne & Fielding-Barnsley, 1989, 1990, 1991) provides the most detailed account of how children come to grasp the alphabetic principle. Through a series of training studies, they showed that explicit instruction in phoneme-grapheme mapping can lead children to “discover” the alphabetic principle, and that this insight, once attained, allows them to generalize beyond the specific items taught. Crucially, these studies revealed that phonemic awareness and letter-sound knowledge, although necessary, are not sufficient for this insight: many children with strong PA and LK still fail to demonstrate alphabetic understanding, whereas others show partial or position-dependent mastery (Byrne, 1998, p. 127; Byrne & Fielding-Barnsley, 1991, p. 320). Byrne's work thus established the causal pathway through which alphabetic insight enables reading, but it never directly quantified the predictive contribution of alphabetic knowledge to later reading outcomes. Moreover, the principle was treated as a binary discovery rather than a continuous dimension along which children differ in the strength of their understanding.

Although KAP has long been acknowledged as a crucial step toward decoding (e.g., Byrne, 1998; Ehri, 2015), its independent contribution to reading development has rarely been estimated directly, and it is often conflated with decoding itself (e.g., Goigoux, 2016). While decoding certainly presupposes knowledge of the alphabetic principle—since it requires understanding that graphemes represent phonemes—it clearly

goes well beyond that understanding. As Byrne and Fielding-Barnsley (1991) demonstrated, a child may have grasped the alphabetic principle yet still be unable to read a single word fluently. The present study extends Byrne et al.'s foundational work by testing, in a population-wide longitudinal dataset, whether the relationships Byrne observed experimentally hold at scale, and by modeling knowledge of the alphabetic principle (KAP) as a continuous variable that interacts with other early literacy skills.

In addition to these code-related skills, oral comprehension (OC) plays a critical role in learning to read. Oral language provides the conceptual and linguistic foundation upon which both decoding and reading comprehension are built (Hulme, Nash, Gooch, Lervag, & Snowling, 2015; Hulme, Snowling, West, Lervåg, & Melby-Lervåg, 2020; Snowling & Melby-Lervåg, 2016). Variations in children's oral language skills—including vocabulary, grammar, and narrative understanding—predict later differences in reading achievement and broader academic outcomes (Duff, Reen, Plunkett, & Nation, 2015; Schatschneider, Fletcher, Francis, Carlson, & Foorman, 2004). There is increasing evidence that weaknesses in oral language can constrain the development of decoding itself, especially during the earliest stages of literacy acquisition. Including oral comprehension in the present analyses therefore allows us to examine not only the contribution of code-related skills but also the influence of broader linguistic competence on reading fluency.

## 1.2. The present study

In the present study, we took a fresh look at the effects of phonemic awareness (PA), letter knowledge (LK), oral comprehension (OC), and knowledge of the alphabetic principle (KAP) on later reading fluency.

Our aim was not only to estimate the unique contribution of each variable while controlling for the others, but also to examine the potential interactions between these early literacy skills. The analyses are based on data from the French national evaluations conducted at the beginning of Grade 1 and again at the beginning of Grade 2, involving the entire population of first-grade students in France (N = 810,328). These evaluations assessed PA, LK, OC, and KAP at school entry, and then measured reading fluency one year later. This unprecedented dataset provides a unique opportunity to investigate the predictors of reading development and their interactions at an unmatched scale—not within a sample, but across an entire national cohort. Crucially, it allows us to test whether the effect of PA on later reading is direct or moderated by other pre-reading skills. In doing so, we aim to move the debate forward and determine whether PA is a robust predictor of reading acquisition or whether its impact is contingent upon other foundational skills.

# 2. Methods

## 2.1. Sample and inclusion

The present analyses are based on the exhaustive national evaluations conducted in French first and second grades (Andreu et al., 2023). These standardized assessments have been administered annually since the 2018–2019 school year and aim to provide teachers with a detailed overview of their pupils' early academic skills. They are administered in all public schools and in private schools under contract with the French Ministry of Education, thereby covering virtually all children starting compulsory schooling in France in that particular year. Although no individual data on home language are collected in the national evaluations, the sample includes all children attending public and private schools under contract, including those who do not have French as their first language. The assessments are administered by each class teacher following standardized procedures, with practice items preceding each task to ensure that all pupils understand the instructions. Teachers are explicitly instructed to provide clarification if comprehension issues
arise during the practice phase.

Children were assessed on three occasions over two academic years: (1) at school entry in September of Grade 1 (weeks 3–4 of the 36-week school year), (2) mid-year in January (weeks 17–18), and (3) at the beginning of Grade 2 (again during weeks 3–4).

The evaluations are developed by the Statistical Department of the French Ministry of Education (Direction de l'évaluation, de la prospective et de la performance – DEPP) and include tasks in both French language and mathematics. All teachers follow standardized administration protocols (e.g., timing, instructions, classroom separation) to ensure uniform test conditions. While most assessments are conducted collectively (i.e., with the whole class), reading fluency tests are administered individually by teachers.

## 2.2. Ethics statement

This study did not require ethics approval, as it is an analysis of publicly available data collected by the Statistical Department of the French Ministry of National Education (DEPP) and did not involve the collection of new data from human participants. All legal and ethical procedures related to the statistical use of these data were reviewed and approved by the DEPP (Convention #2020-13).

## 2.3. Data and code availability

The national evaluations are conducted by the Statistical Department of the French Ministry of National Education (DEPP). Data collection and storage procedures comply with the General Data Protection Regulation (GDPR). Access to the data was granted through a research agreement between the Ecole Nationale Supérieure, the French Ministry of National Education, and the research team. Due to legal constraints, the dataset cannot be made available by us. However, access can be granted upon request through a licensing agreement with the DEPP. All analyses were conducted using R. The analysis code is available upon request.

## 2.4. Participants

The initial sample was comprised of 810,328 children tested in grade 1 (mean age at first assessment = 6.3 years). Attrition from first grade to second grade was 6.5% of the children evaluated in first grade (i.e., 52955 pupils). It was mainly due to children who left the public educational system or were absent during the tests. Children with learning difficulties were not excluded from the data. Information on the total sample is provided in Table 1.

To avoid including pre-readers in our analyses, we chose to exclude children who showed already proficient decoding skills upon school entry. As the September Grade 1 evaluation did not include a decoding task (i.e., word or pseudoword reading), we simply excluded the top 33% of children on the subtest assessing knowledge of the alphabetic principle (KAP; see “Tests” section below). These corresponded to the children who answered all KAP items correctly.<fnref n="1" /> The decision to exclude the top 33% of children is also in line with a representative study by Goigoux (2016; N = 2,507 children across 131 classes) who found that 20–30% of children entering first grade in France could already decode simple syllables. The number of children in the final sample is given in Table 1.

## 2.5. Tests and materials

### 2.5.1. Phoneme awareness (early first grade)

PA was assessed at the beginning of first grade using two subtests. The first subtest required children to identify words that began with the same phoneme as a target word, while the second subtest required them to identify words that ended with the same phoneme as a target word.

In each trial, children were presented with four response options, not in letters but in the form of illustrated drawings printed in a booklet. The target word and the four response options were named aloud by the teacher. Children were instructed to circle the drawing corresponding to the correct answer. The initial-phoneme subtest consisted of 8 items, and the final-phoneme subtest included 7 items. Both subtests began with a training item to familiarize the children with the task format. All test items are provided in the supplementary materials.

The total PA score was computed as the sum of correct responses across the two subtests (maximum score = 15). Given the four-alternative forced-choice format, the expected chance score was just under 4 correct answers. Internal consistency was satisfactory, with a Cronbach's alpha of 0.80 (see Table 1 for descriptive statistics).

### 2.5.2. Letter knowledge (early first grade)

Letter knowledge was assessed at the beginning of first grade through a visual letter-identification task. On each trial, teachers pronounced the name of a target letter aloud, and pupils were asked to locate that letter within a series of 18 letters printed in three different scripts (cursive, uppercase, and print) in their test booklets. Each series included exactly three instances of the target letter—one in each script.

While the original aim of this subtest was to assess script recognition, our focus was on letter knowledge rather than familiarity with different letter forms. Therefore, we recoded responses using a stricter criterion: pupils were awarded one point if they circled at least one of the three correct letters and made no incorrect selections.

The test comprised 7 items in total (3 vowels and 4 consonants), resulting in a maximum score of 7. Given the recoding and scoring rules, the expected score by chance was below 1. The test demonstrated good internal consistency, with a Cronbach's alpha of 0.78 (see Table 1 for descriptive statistics). All test items are provided in the supplementary materials.

### 2.5.3. Knowledge of the alphabetic principle (early first grade)

Knowledge of the alphabetic principle (KAP) was assessed using a subtest in which children were presented with a series of five letters on each trial (e.g., m, n, b, d, f) and asked to circle the letter corresponding to the initial phoneme of a word read aloud by the teacher. To succeed, children needed to identify the initial phoneme of a spoken word, retrieve its corresponding grapheme, and select it from a set of distractors. This task thus goes beyond simple letter knowledge, entailing some minimal phoneme identification skills and an understanding of the alphabetic mapping.

All target words began with consonants, making the task particularly challenging. In French, unlike vowels, the names of consonants provide little phonemic information, which prevents children from relying solely on letter-name knowledge. The test consisted of 10 trials, each with five response options. With this format, the chance level was 2 out of 10 correct responses. The internal consistency of the test was high, with a Cronbach's alpha of 0.84 (see Table 1). All test items are provided in the supplementary materials.

### 2.5.4. Oral comprehension (early first grade)

Oral comprehension was assessed at the beginning of first grade using an adapted version of the TROG (Test for Reception of Grammar) (Bishop, 2003) and its French counterpart, the ECOSSE (Épreuve de compréhension syntaxico-sémantique) (Lecocq, 1996). In this task, the teacher read aloud a sentence, and pupils were asked to select the picture that best matched the sentence from four response options

<footnote n="1">¹ Following the suggestion of one of the anonymous reviewers, we also added in the supplementary material a regression analysis in which we excluded the top 50% of children (i.e., those who answered either all KAP items correctly or nine out of ten). Extending the exclusion threshold from the top 33% of children to the top 50% constitutes a robustness test with an even more rigorous definition of pre-readers. The results remain unchanged.</footnote>
<table><caption>**Table 1**

Descriptive statistics of predictor and outcome variables.</caption><thead><tr><th>Variable</th><th>Sample</th><th>N</th><th>Mean</th><th>SD</th><th>Range</th><th>Cronbach's α</th><th>VIF</th></tr></thead><tbody><tr><td rowspan="2">Oral Comprehension</td><td>Whole population</td><td>795,650</td><td>12.1</td><td>2.4</td><td>0-14</td><td>0.75</td><td>1.27</td></tr><tr><td>No pre-readers</td><td>532,260</td><td>11.7</td><td>2.6</td><td>0-14</td><td></td><td></td></tr><tr><td rowspan="2">Letter Knowledge</td><td>Whole population</td><td>767,277</td><td>5.7</td><td>1.3</td><td>0-7</td><td>0.78</td><td>1.17</td></tr><tr><td>No pre-readers</td><td>509,006</td><td>5.5</td><td>1.4</td><td>0-7</td><td></td><td></td></tr><tr><td rowspan="2">Phonemic Awareness</td><td>Whole population</td><td>796,967</td><td>8.9</td><td>3.6</td><td>0-15</td><td>0.80</td><td>1.47</td></tr><tr><td>No pre-readers</td><td>538,719</td><td>7.8</td><td>3.4</td><td>0-15</td><td></td><td></td></tr><tr><td rowspan="2">Knowledge of the Alphabetic Principle</td><td>Whole population</td><td>796,520</td><td>7.5</td><td>2.7</td><td>0-10</td><td>0.84</td><td>1.47</td></tr><tr><td>No pre-readers</td><td>539,940</td><td>6.3</td><td>2.6</td><td>0-10</td><td></td><td></td></tr><tr><td rowspan="2">Reading Fluency</td><td>Whole population</td><td>757,373</td><td>54.2</td><td>43.1</td><td>0-300</td><td></td><td></td></tr><tr><td>No pre-readers</td><td>501,258</td><td>45.0</td><td>30.5</td><td>0-300</td><td></td><td></td></tr></tbody></table>

Source. French Ministry of National Education and Youth (MENJ), Directorate of Evaluation, Forecasting and Performance Monitoring (DEPP), national full-population assessments at the beginning of Grade 1 (September 2020) and the beginning of Grade 2 (September 2021).
Note. VIF = variance inflation factor. Cronbach's alpha was computed on the basis of the whole sample.

presented in their booklets.

Each set of images included plausible alternatives that shared lexical or thematic elements with the target sentence, ensuring that pupils had to process the full syntactic and semantic content in order to choose the correct answer. The test began with a training item (L'enfant jette la pomme [The child throws the apple]) to familiarize pupils with the task.

The test included 14 items in total. With four choices per item, the chance level was 3.5 correct answers. The internal consistency of the test was acceptable, with a Cronbach's alpha of 0.75 (see Table 1 for descriptive statistics).

### 2.5.5. Reading fluency (early second grade)

Reading fluency was assessed at the beginning of second grade using a 103-word text that pupils were asked to read aloud. The dependent variable was the number of words correctly read in one minute. The test was administered individually by the teacher with each child. Pupils were informed beforehand that they would be stopped after one minute.

Many children did not reach the end of the text within the allotted time. In these cases, the teacher recorded the number of correctly read words within the first 60 s. For pupils who completed the entire text in under a minute, teachers calculated the number of correctly read words per minute by dividing the total number of words by the number of seconds it took to read the text, then multiplying the result by 60. This approach ensured a standardized reading fluency score across participants, regardless of whether they completed the full text.

## 2.6. Analysis methods

The data were analyzed using multilevel fixed-effect models to investigate the effects of PA, LK, OC and KAP and their interactions on subsequent reading fluency. The coefficients were estimated using the lme4 package version 1.1–32 of the R software (Bates, Mächler, Bolker, & Walker, 2015). To obtain the most accurate estimates of individual-level coefficients, class fixed effects were included (Clark & Linzer, 2015; Snijders & Bosker, 2011). This allows to account for and control for all class-level variations, ensuring that our estimates only capture within-class differences. We also controlled for age (a continuous variable going from 1 for children born in January to 12 for children born in December). All pre-reading skills (PA, OC, KAP and LK) were measured in the first weeks of grade 1, while reading fluency was measured one year later in the first weeks of grade 2. We compared the two statistical models specified below. Both models are composed of the same dependent and independent variables. However, the first model (1) contained only main effects, while the second model (2) included the interactions between the independent variables.

(1) Reading fluency<sub>i</sub> = β0 + β1 PA<sub>i</sub> + β2 LK<sub>i</sub> + β3 KAP<sub>i</sub> + β4 OC<sub>i</sub> + β5 age<sub>i</sub> + γ classroom + ε<sub>i</sub>

(2) Reading fluency<sub>i</sub> = β0 + β1 PA<sub>i</sub> + β2 LK<sub>i</sub> + β3 KAP<sub>i</sub> + β4 OC<sub>i</sub> + β5 age<sub>i</sub> + β6 PA<sub>i</sub> * LK<sub>i</sub> + β7 PA<sub>i</sub> * KAP<sub>i</sub> + β8 LK<sub>i</sub> * KAP<sub>i</sub> + β9 PA<sub>i</sub> * OC<sub>i</sub> + β10

LK<sub>i</sub> * OC<sub>i</sub> + β11 KAP<sub>i</sub> * OC<sub>i</sub> + β12 PA<sub>i</sub> * LK<sub>i</sub> * KAP<sub>i</sub> + β13 PA<sub>i</sub> * LK<sub>i</sub> * OC<sub>i</sub> + β14 PA<sub>i</sub> * KAP<sub>i</sub> * OC<sub>i</sub> + β15 LK<sub>i</sub> * KAP<sub>i</sub> * OC<sub>i</sub> + β16 PA<sub>i</sub> * LK<sub>i</sub> * KAP<sub>i</sub> * OC<sub>i</sub> + γ classroom + ε<sub>i</sub>

# 3. Results and discussion

## 3.1. Descriptive statistics

The descriptive statistics and distributions of the predictor variables measured at the beginning of Grade 1 and the outcome variable (reading fluency) measured at the beginning of Grade 2 are presented in Table 1. The Variance Inflation Factors (VIFs) for all predictor variables were well below 5 (see Table 1), indicating that multicollinearity was not a concern in our dataset (Akinwande, Dikko, & Samson, 2015).

Regarding phonemic awareness (15 items), the distribution shows that the test is well calibrated for children entering first grade. Half the children pass half the items, and scores decline in a linear way across deciles: 14 (9th decile), 12 (8th decile), 11 (7th decile), 10 (6th decile), 9 (5th decile), 8 (4th decile), 7 (3rd decile), 6 (2nd decile) and 4 (1st decile). Between 20% and 30% of French children entering first grade obtained less than 7 and could therefore be considered as having modest to weak PA.

Regarding knowledge of the alphabetic principle (KAP – 10 items), more than half of French children enter first grade with very high KAP. Nevertheless, the distribution is not saturated with the first deciles obtaining low scores in the task, that is, between 20% and 30% of the pupils who enter first grade can indeed be considered to have modest to weak KAP (scoring 5 or less).

Regarding oral comprehension (14 items), French pupils enter first grade with overall strong oral comprehension skills. The test creates a saturated distribution with the vast majority of pupils obtaining high scores. More than 50% of them obtain 13 or 14 and more than 90% obtain at least 9 correct responses. This very high success rate generates a small variance for that variable. French pupils also display high letter knowledge (7 items) when they enter first grade: the mean is 5.7, the median is 6, and more than 87% of pupils obtain 5 or more.

Regarding reading fluency in early second grade, the results show that many French pupils are slow readers. Indeed, according to the French Ministry of Education, at the end of first grade, pupils should be able to read at least 50 words per minute (French Ministry of National Education, 2019). As can be seen in Table 1, half of the French students at the beginning of grade 2 did not reach the official objective of 50 words per minute that they were supposed to have reached a couple of months before, at the end of first grade.

The correlations between the five variables are presented in Table 2. OC is positively correlated with PA (r = 0.43) and KAP (r = 0.39) but it is less correlated with LK (r = 0.30) and reading fluency measured one year later (r = 0.23). This is in line with other studies (e.g., Fricke, Szczerbinski, Fox-Boyer, & Stackhouse, 2016). PA is positively
<table><caption>**Table 2**
Correlations among early literacy predictors and later reading fluency.</caption><thead><tr><th>Variables</th><th>1</th><th>2</th><th>3</th><th>4</th><th>5</th></tr></thead><tbody><tr><td>1. Oral Comprehension</td><td>-</td><td></td><td></td><td></td><td></td></tr><tr><td>2. Letter Knowledge</td><td>0.30</td><td>-</td><td></td><td></td><td></td></tr><tr><td>3. Phonemic Awareness</td><td>0.43</td><td>0.33</td><td>-</td><td></td><td></td></tr><tr><td>4. Knowledge of the Alphabetic principle</td><td>0.39</td><td>0.40</td><td>0.59</td><td>-</td><td></td></tr><tr><td>5. Reading fluency</td><td>0.23</td><td>0.24</td><td>0.36</td><td>0.36</td><td>-</td></tr></tbody></table>

Source. French Ministry of National Education and Youth (MENJ), Directorate of Evaluation, Forecasting and Performance Monitoring (DEPP), national full-population assessments at the beginning of Grade 1 (September 2020) and the beginning of Grade 2 (September 2021).

Note. Reading fluency was measured at the beginning of Grade 2. All other variables were measured at the beginning of Grade 1. Correlations are based on the full sample (N = 810,328). All correlations are statistically significant at *p* < .001.

<table><caption>**Table 3**
Multilevel fixed-effects linear models predicting standardized reading fluency (whole population without pre-readers).</caption><thead><tr><th>Effect</th><th>Model 1: Main effects (Estimate)</th><th>p</th><th>Model 2: Interactions (Estimate)</th><th>p</th></tr></thead><tbody><tr><td>Phonemic awareness (PA)</td><td>0.057</td><td>&lt; 0.001</td><td>-0.034</td><td>&lt; 0.001</td></tr><tr><td>Letter knowledge (LK)</td><td>0.069</td><td>&lt; 0.001</td><td>-0.004</td><td>0.535</td></tr><tr><td>Knowledge of the alphabetic principle (KAP)</td><td>0.070</td><td>&lt; 0.001</td><td>-0.013</td><td>0.167</td></tr><tr><td>Oral comprehension (OC)</td><td>0.017</td><td>&lt; 0.001</td><td>-0.036</td><td>&lt; 0.001</td></tr><tr><td>Age</td><td>-0.003</td><td>&lt; 0.001</td><td>-0.003</td><td>&lt; 0.001</td></tr><tr><td>PA × LK</td><td>-</td><td>-</td><td>0.007</td><td>&lt; 0.001</td></tr><tr><td>PA × KAP</td><td>-</td><td>-</td><td>0.009</td><td>&lt; 0.001</td></tr><tr><td>LK × KAP</td><td>-</td><td>-</td><td>0.014</td><td>&lt; 0.001</td></tr><tr><td>PA × OC</td><td>-</td><td>-</td><td>0.007</td><td>&lt; 0.001</td></tr><tr><td>LK × OC</td><td>-</td><td>-</td><td>0.009</td><td>&lt; 0.001</td></tr><tr><td>KAP × OC</td><td>-</td><td>-</td><td>0.007</td><td>&lt; 0.001</td></tr><tr><td>PA × LK × KAP</td><td>-</td><td>-</td><td>-0.002</td><td>&lt; 0.001</td></tr><tr><td>PA × LK × OC</td><td>-</td><td>-</td><td>-0.001</td><td>&lt; 0.001</td></tr><tr><td>PA × KAP × OC</td><td>-</td><td>-</td><td>-0.001</td><td>&lt; 0.001</td></tr><tr><td>LK × KAP × OC</td><td>-</td><td>-</td><td>-0.002</td><td>&lt; 0.001</td></tr><tr><td>PA × LK × KAP × OC</td><td>-</td><td>-</td><td>0.000</td><td>&lt; 0.001</td></tr><tr><td>R<sup>2</sup></td><td>0.288</td><td></td><td>0.296</td><td></td></tr><tr><td>Number of observations</td><td>470,222</td><td></td><td>470,222</td><td></td></tr></tbody></table>

Source. French Ministry of National Education and Youth (MENJ), Directorate of Evaluation, Forecasting and Performance Monitoring (DEPP), national full-population assessments at the beginning of Grade 1 (September 2020) and the beginning of Grade 2 (September 2021).

Note. Dependent variable: standardized reading fluency. Predictors were entered in their original scales. All models include classroom fixed effects (54,026 classrooms). PA = Phonemic awareness; LK = Letter knowledge; KAP = Knowledge of the alphabetic principle; OC = Oral comprehension.

correlated with LK (0.43), KAP (0.59) and with reading fluency measured one year later (0.36), while LK is also less correlated with reading fluency (0.24). Interestingly, the correlation with fluency is exactly the same for KAP and PA (0.36).

## 3.2. Regression analyses

The two core models are described above (see Analysis methods). The results of the main effects model (Model 1) and the interaction model including the interactions between PA, OC, LK, and KAP (Model 2) are presented in Table 3.<fnref n="2" /> The dependent variable (reading fluency) was standardized prior to analysis, whereas the predictors were retained in their original scale. Accordingly, the coefficients represent the change in standard deviation units of reading fluency associated with a one-unit increase in a given predictor, accounting for the other predictors and their interactions.

In the main effects model (Model 1), all four predictors – oral comprehension (OC), phoneme awareness (PA), letter knowledge (LK), and knowledge of the alphabetic principle (KAP) – had significant effects on reading fluency, even when controlling for the influence of the other

variables. KAP and LK had comparable effect sizes (~7% of a standard deviation) while PA was slightly weaker (5.7% of a standard deviation). OC had the smallest effect (~1.7% of a standard deviation) on subsequent reading fluency.

In the interaction model (Model 2), the main effects were qualified by significant interactions between all predictor variables, indicating that the effect of any one variable depended on the levels of the others (an *F*-test model comparison showed that the interaction terms were statistically significant at *p* < .0001). Because the model includes higher-order interactions (up to four-way), neither the main effects nor the lower-order interaction coefficients can be interpreted in isolation. The sign and magnitude of these coefficients represent conditional effects that depend on the values of other predictors involved in higher-order interactions. Therefore, a positive or negative coefficient for a two-way interaction does not indicate a universally strengthening or weakening effect, but only the direction of the effect when all other inter-

acting variables are at their reference levels. To obtain substantively meaningful interpretations, we examine fitted values and marginal effects, focusing on theoretically relevant combinations of predictors.

To illustrate the interaction between PA and KAP – our two main variables of interest – we present predicted levels of reading fluency as a function of different PA and KAP levels in Figs. 1 and 2. Both figures display the same data but in complementary orientations: in Fig. 1, PA is plotted on the x-axis and KAP on the y-axis, while Fig. 2 reverses these axes. For both figures, we fixed age at the sample mean and assigned maximum scores for LK and OC. This decision is justified both theoretically and empirically. Some level of LK and OC is necessary to perform well on PA and KAP tasks. Thus, setting these variables to their maximum values allows us to isolate and examine the effects of PA and KAP under meaningful conditions. Moreover, this scenario is empirically plausible, as a substantial proportion of French pupils (15%) enter first grade with perfect scores on both LK and OC tasks.

The results presented in Fig. 1 can be interpreted as follows: PA does have a positive effect on reading fluency one year later, but it is almost entirely conditional upon strong scores of KAP. When KAP is low, the fluency curves as a function of PA are almost flat (see bottom line in Fig. 1). That is, even when OC and LK are at ceiling, increasing PA does not substantially improve reading fluency if KAP is low. For instance, when KAP is low (2/10), and OC and LK are at their maximum (14/14 and 7/7, respectively), increasing PA from 3/15 to 15/15 leads only to a modest improvement in reading fluency: from 25.1 to 30.2 words per

<footnote n="2">² The results of the regression analysis in which we excluded the top 50% of children are identical to the ones presented in Table 3 (see Table S1 in the supplementary material).</footnote>
<figure><img src="image_2.png" /><figcaption>**Fig. 1.** Predicted reading fluency (words per minute) for the interaction model as a function of PA (on the abscissa). Maximum levels were set for letter knowledge (LK = 7 out of 7) and oral comprehension (OC = 14 out of 14), and average level for age.</figcaption></figure>

<figure><img src="image_3.png" /><figcaption>**Fig. 2.** Predicted reading fluency (words per minute) for the interaction model as a function of knowledge of the alphabetic principle (on the abscissa). Maximum levels were set for letter knowledge (LK = 7 out of 7) and oral comprehension (OC = 14 out of 14), and average level for age.</figcaption></figure>

minute.

Fig. 2 shows a complementary pattern: KAP has a strong positive effect on reading fluency one year later, and its effect is less dependent on PA levels. For example, when PA is quite good (12/15), going from very low KAP (2/10) to a high KAP (9/10) substantially increases reading fluency a year later: from 28.9 words per minute to 55.5 words per minute. Even when PA is low (4/15), going from very low KAP (2/

10) to a high KAP (9/10) also substantially increases reading fluency: from 25.5 words per minute to 42.0 words per minute.

In sum, the results show that when interactions are taken into account, PA, OC, and LK alone are not reliable predictors of subsequent reading skills. While they are necessary, they remain insufficient: among pupils entering first grade with perfect PA, OC, and LK but a modest KAP (4/10), nearly half experience severe reading difficulties one year later.
Specifically, 43% read fewer than 30 words per minute, the official threshold below which children are considered in difficulty (Depp, 2024).

On the contrary, KAP is by far the strongest predictor of later reading skills. Even though KAP partially encapsulates PA and is empirically also linked to OC and LK, it does not need high levels of PA to guarantee good reading levels of beginning readers. Among students who enter first grade with modest PA (7 out of 15) but with strong KAP (and with strong OC and LK), only 17% fail to reach an acceptable reading level one year later (i.e., pace above 30 words per minute). What is more, the results show that KAP is a continuous rather than a binary ability. Its effect on ulterior reading levels is linear: each additional point on the test substantially improves future reading fluency.

## 4. General discussion

While phonemic awareness (PA) is often considered a key precursor to reading, our results show that its predictive power is heavily dependent on the child's knowledge of the alphabetic principle (KAP). In contrast, KAP is independently and robustly associated with later reading fluency, even when PA is low. Children with high KAP tend to become fluent readers even when PA is initially low, whereas children with high PA but low KAP often struggle. This suggests that KAP is not only a more reliable predictor of reading development than PA but may also function as a foundational skill that supports children to effectively leverage their phonemic awareness during reading acquisition.

This conclusion is directly grounded in our empirical findings. In the main regression analyses (Model 1), both KAP and letter knowledge (LK) showed the strongest unique associations with later reading fluency. When higher-order interactions were included (Model 2), the analysis revealed that increases in KAP were consistently associated with gains in reading fluency across all levels of PA, whereas the reverse pattern was not observed. In other words, the positive effect of PA on later reading emerged only when KAP was high, while KAP continued to predict reading outcomes even when PA was low. These conditional effects form the empirical basis for our conclusion that KAP is the more reliable and independent correlate of reading development.

It is important to note that in our full model (Model 2), the inclusion of higher-order interactions prevents direct interpretation of main effects. Therefore, our conclusions are based on the conditional effects derived from the interactions rather than on main effects alone. These analyses showed that when KAP was fixed at the highest level, variations in PA had only marginal effects on later reading fluency, whereas when PA was fixed at the highest level, increases in KAP produced substantial, linear gains in reading fluency. This pattern highlights KAP's pivotal role in explaining individual differences in reading acquisition once the interdependence among early reading skills is taken into account.

A possible objection is that KAP may simply encapsulate PA – after all, successful KAP performance requires identifying the first phoneme of a spoken word and mapping it to its corresponding letter(s). However, our data suggest that KAP is not reducible to PA. For instance, 83% of students with modest PA but strong KAP at school entry became good readers one year later, whereas 43% of students with high PA, high LK, and high OC but low KAP became poor readers. These patterns highlight the distinct explanatory power of KAP.

This apparent dissociation between KAP and PA is consistent with Byrne and Fielding-Barnsley's (1989, 1991) findings showing that children can acquire the alphabetic principle even when their explicit phonemic awareness remains limited. Thus, children with relatively modest PA but strong KAP have already developed a functional understanding of grapheme-phoneme correspondences, even if their explicit, decontextualized PA is not yet fully developed. This distinction helps explain why KAP tends to relate to reading outcomes more strongly than PA, and why phonological training without print exposure often yields limited benefits.

Our findings call for a conceptual refinement of KAP. Traditionally

treated as a binary skill (e.g., Byrne, 1998; Castles & Coltheart, 2004; Ehri & Soffer, 1999), our data show that KAP functions as a continuous variable. Each additional point on the KAP scale is associated with better reading outcomes one year later.

We propose two stages in the development of KAP and its contribution to reading acquisition. In the first stage, children grasp that written language encodes speech at the phoneme level – a foundational insight that can emerge before full mastery of letter-sound correspondences, but is progressively deepened by each new mapping acquired. This stage does not necessarily involve decoding. In the second stage, as KAP strengthens, children learn to combine letter-sounds into syllables and understand the context-sensitive nature of some correspondences (e. g., digraphs and trigrams). This progression supports decoding and, ultimately, lexical development (Ziegler et al., 2014).

Importantly, our results do not contradict the phonological-deficit hypothesis of dyslexia (Hulme et al., 2015; Snowling & Melby-Lervåg, 2016). PA remains necessary – children need at least minimal PA to build KAP – but it is not sufficient. Many children with high PA but low KAP still become poor readers. Thus, while low PA may help identify children at risk, high PA alone does not guarantee successful reading acquisition.

Finally, our findings challenge the widely held belief that PA is the best predictor and that training it in isolation leads to better reading outcomes. This belief has been tempered by the phonological linkage hypothesis (Hatcher, Hulme, & Ellis, 1994), which proposes that PA instruction is most effective when explicitly integrated with letter-sound training. Subsequent studies have confirmed this view (e.g., Schneider, Roth, & Ennemoser, 2000), showing that children benefit most when phonological and orthographic information are taught jointly. Orthographic knowledge, that is, children's understanding of the written code, including letter patterns, positional constraints, and grapheme-phoneme regularities, acts as the structural support that allows PA to translate into efficient decoding.

Future research could further clarify the developmental dynamics among these skills by examining the mediating as well as the moderating roles of phonemic awareness. While the present study focused on interaction effects, longitudinal mediation analyses could help determine whether PA serves as a mechanism through which letter knowledge and early exposure to print foster the acquisition of the alphabetic principle and subsequent reading fluency.

In conclusion, it is essential for teachers and educators to recognize that alphabetic writing systems are fundamentally grapho-phonemic. Knowledge of the alphabetic principle (KAP) appears to be a pivotal component of early reading development, not as a stand-alone instructional target, but as an explicit focus embedded within high-quality phonics instruction. Systematic approaches that help children notice, articulate, and generalize the principle that graphemes represent phonemes are likely to support early reading acquisition. A clearer, evidence-based understanding of the respective roles of phoneme awareness, letter knowledge, and especially KAP can therefore inform and refine early reading instruction and intervention strategies.

### CRediT authorship contribution statement

**Paul Gioia:** Writing – review & editing, Writing – original draft, Visualization, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. **Johannes C. Ziegler:** Writing – original draft, Visualization, Validation, Supervision, Resources, Project administration, Methodology, Investigation, Funding acquisition, Conceptualization. **Jerome Deauvieu:** Writing – review & editing, Validation, Supervision, Resources, Project administration, Methodology, Investigation, Formal analysis, Conceptualization.

### Funding

This research was supported by the eFRAN program (France 2030),
operated by the Agence Nationale de la Recherche (ANR; grant ANR-22-FRAN-0004), the Institute for Language, Communication and the Brain (ILCB; ANR-16-CONV-0002), the Excellence Initiative of Aix-Marseille University A*MIDEX (ANR-11-IDEX-0001-02), and the pilot center for research in education and teacher training AMPIRIC (France 2030).

## Acknowledgements

The authors thank AMPIRIC, the Aix-Marseille Center of Excellence for Research in Education and Teacher Training (France 2030), and the École Normale Supérieure (ENS) for their continued support. We also thank our colleagues at the Scientific Council of the Ministry of Education (CSEN) and at the Statistical Department of the Ministry of Education (DEPP) for their collaboration and support.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.cognition.2026.106457.

## Data availability

The authors do not have permission to share data.

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