Introduction

Reading is considered to be an essential academic competence. People are surrounded by and confronted with information in written form daily, which needs to be decoded and processed in order to be comprehensible. However, not all individuals reach a sufficient reading proficiency level, even after receiving educational instruction. Illiteracy costs account for more than $1 trillion U.S. dollars per year on a global level (Cree et al., 2022). The indirect costs have a much larger impact, because failing to reach a sufficient literacy level limits people from acquiring basic knowledge. Low literacy is therefore a major contributor to inequality in all domains, increasing the risk of various physical and mental illnesses as well as the likelihood of welfare dependency, which include substantial economic and social costs (Cree et al., 2022). In order to evade and hinder development of such disadvantages, relevant components of reading as well as reading development need to be identified (Castles et al., 2018; Tippelt & Schmidt-Hertha, 2018).

Numerous studies have shown that a variety of different cognitive and linguistic components are relevant for successful reading (e.g., Coltheart et al., 2001; Preßler et al., 2014). In this regard, various variables are considered to be important prerequisites of reading, such as vocabulary knowledge and naming speed (i.e., automatized retrieval of information; e.g., Clemens et al., 2017; Coltheart et al., 2001; Steinbrink & Lachmann, 2014). A growing number of studies has also focused on orthographic knowledge (i.e., the knowledge of conventions of a written language in an orthography) and have found orthographic knowledge to be a relevant component for reading (e.g., Cutting & Denckla, 2001).

The role of orthographic knowledge for basic and higher reading processes

Orthographic knowledge is defined as the knowledge of rules and conventions within a specific orthography (Conrad et al., 2013), consisting of a word-specific (lexical) and a general (sub-lexical) component (Apel, 2011). The word-specific component refers to the knowledge about stored mental representations of familiar words and word parts. It is usually assessed by words- and pseudohomophones decision tasks, where participants decide whether a presented stimulus is a real word or not by actively comparing it to the stored mental representations (Apel et al., 2018). The general component of orthographic knowledge refers to the knowledge about the permitted letter patterns in an orthography, particularly the rules concerning permissible letter positions and letter combinations (Apel et al., 2018). Tasks usually used to assess general component are word-likeness tasks. In those, knowledge of permissible letter sequences and/or letter position rules is measured by asking participants to choose the stimuli that resembles a real word the most (Apel et al., 2018).

Comprehension as the ultimate goal of reading requires accessing and constructing meaning from written text, as well as coordination of different cognitive components (Johnston et al., 2008). The different processes necessary for comprehension interact on word-, sentence-, and text-level (Gruhn et al., 2020; Ouden et al., 2019). Word identification enables sentence comprehension, and leads to establishing coherences between sentences (Perfetti et al., 2005; Vellutino et al., 2004a, 2004b). The word level as the basic level of reading includes decoding and understanding the meaning of single words (Karageorgos et al., 2019), requiring mostly lower-level processing skills, such as efficient phonological and orthographic processing (Wolf & Katzir-Cohen, 2001). Previous studies have shown that word-specific and general orthographic knowledge are significant predictors of word-reading skills (e.g., Georgiou et al., 2008; Rothe et al., 2015; Zarić, Hasselhorn, & Nagler, 2021; Zarić & Nagler, 2021). However, fewer studies focused on the role of orthographic knowledge on higher-level reading (sentence- and text-level).

Sentence-level reading is enabled through successful identification of words and their meaning as well as their interpretation in the context of the sentence (Lenhard & Schneider, 2006). The content of the sentence can be comprehended by parallel processing of semantic and syntactic elements (Lenhard & Schneider, 2006; Taraban & McClelland, 1990). Thus, sentence structure and word meanings are used to understand the meaning of the content of a sentence (Verhoeven & Perfetti, 2008). Text-level comprehension requires understanding the relationship between sentences and combining their meanings (Gough & Tunmer, 1986; Verhoeven & Perfetti, 2008). Therefore, information needs to be extracted, cross-references need to be established, and inference conclusion (i.e., reading between the lines) is required (Lenhard & Schneider, 2006).

Comparably less studies have examined that role of orthographic knowledge on higher-level reading. In a study by Katzir et al. (2006), word-specific orthographic knowledge contributed significantly to sentence- and text-comprehension in English for reading impaired as well as typical readers. For German, a transparent orthography, orthographic knowledge was identified as a significant predictor for higher-level reading in poor (Zarić & Nagler,, 2021) and typical readers (Richter et al., 2013; Zarić et al., 2021). A sufficient level of orthographic knowledge is assumed to support fluent reading by enabling quick recognition of written words with little cognitive effort (Ehri, 2005), facilitating comprehension on sentence- and text-level. In turn, insufficient reading fluency might also be influenced by a lower level of orthographic knowledge. In terms of the Dual-Route-Model, the word-specific component is useful when a reader is confronted with familiar words and uses the lexical, more efficient route. However, when confronted with an unfamiliar word, with no stored mental representations, a reader uses the non-lexical, less efficient route. In this process, the general orthographic component can be useful (Castles, 2006; Grainger & Ziegler, 2011). It is assumed that both, word-specific and general orthographic knowledge, support efficient single word reading and processing, which leads to higher reading fluency, enabling sentence and text comprehension. In contrast, efficient word recognition and possibly insufficient orthographic knowledge can lead to low reading comprehension (Jenkins et al., 2003). Taken together, exposure to print and practice can foster efficient reading of words, leading to comprehension of sentences and text passages.

Vocabulary knowledge and naming speed as reading relevant components

For proficient reading, decoding accuracy alone is not sufficient, a certain level of automaticity is mandatory (Hudson et al., 2011). Various models of reading emphasize the importance of vocabulary knowledge for reading (Clemens et al., 2017; Quinn et al., 2015). It is a crucial component for understanding a language, necessary not only for spoken language, but also for text and reading comprehension (Joshi, 2005; Nation, 2005; Quinn et al., 2015). If words can be fluently decoded, but their meanings in a passage could not be identified, reading comprehension is not possible. Experimental studies have shown the importance of vocabulary size for reading, demonstrating that the knowledge of a particular word predicted its reading accuracy (Nation & Cocksey, 2009; Ricketts et al., 2016). Studies have shown that reading comprehension can be impaired, when as few as 2–5% of word meanings in sentences cannot be determined (Hsueh-Chao & Nation, 2000; Schmitt et al., 2011). Vocabulary can be divided into receptive and expressive knowledge, with the former including the distinctive features of the receptive language skills while listening and reading, and the latter including productive language skills while speaking and writing (Nation, 2022). It is suggested that receptive and expressive vocabulary might relate to reading measures differently. Expressive knowledge is considered to be more related to word identification than receptive knowledge, because expressive vocabulary knowledge includes phonological and semantic knowledge (Wise et al., 2007).

Naming speed is a basic cognitive component relevant for the development of reading speed (Moll et al., 2012). It is characterized by automatized and fast naming of familiar stimuli, such as colors, objects, letters and digits and is often operationalized through rapid automatized naming (RAN) tasks (Denckla & Rudel, 1976). Empirical findings suggest naming speed to be a significant predictor for reading skills (Bowers, 1995; Georgiou et al., 2008; Landerl & Wimmer, 2008; Moll et al., 2009) and to be one of the most robust correlates of reading difficulties (Landerl et al., 2013).

In summary, higher-level reading processes are mainly influenced by the input from basic reading skills, where the ultimate goal is to construct the meaning of every single word (Perfetti & Stafura, 2014). The efficient word-decoding and high-quality orthographic representation are crucial for reading comprehension (see for example the Lexical Quality Hypothesis; (Perfetti & Hart, 2002; Richter et al., 2013). Quick retrieval of these orthographic representations stored in the mental lexicon as well as understanding the meaning of the words are key components of reading comprehension (Elleman, 2017), mainly supported by orthographic knowledge, vocabulary knowledge, and naming speed.

The longitudinal perspective

Previous studies examining the role of vocabulary and naming speed on reading comprehension have shown that both components contribute significantly to reading skills (Georgiou et al., 2008; Joshi, 2005; Quinn et al., 2015). Recent research has focused on the role of orthographic knowledge as well, showing that it plays an important role for basic, as well as higher-level reading processes (Richter et al., 2013; Zarić et al., 2021; Zarić & Nagler, 2021). However, previous studies only concentrated on the immediate influence of these variables on reading by applying regression models where both, reading and reading relevant components, were assessed at the same time point. While the results of these models can be useful in investigating the contribution of reading relevant components to reading skills, they cannot provide information about whether or not these components also influence the acquisition/growth of reading comprehension.

In order to understand individual trajectories in reading acquisition, a longitudinal perspective is necessary to disentangle effects on performance from effects on growth. By investigating differences in effects of component skills between outcome measures taken at the same or at a later timepoint, we can approach potential causal interpretations. Designing instruction that is aimed at preventing deficits in component skills from hindering the development of reading comprehension also critically hinges on information about which of these component skills actually are related to the growth of reading comprehension.

To our knowledge, only one study examined the relationship between orthographic knowledge and reading on basic and higher levels in a longitudinal design from kindergarten to second grade in German transparent orthography (Ise et al., 2014). However, in their study, Ise et al. (2014) only reported nonsignificant correlations between orthographic knowledge and reading skill and did not include any regression models. Therefore, it still remains unclear whether orthographic knowledge can contribute significantly to explaining differences in the longitudinal development of reading, over and above vocabulary and naming speed.

Present study

The present study aimed to close this gap by taking a longitudinal perspective on the influence of orthographic knowledge on reading acquisition. Since prior cross-sectional work has identified differential effects of orthographic knowledge on different levels (word-, sentence- or text-level) of reading comprehension (e.g., Richter et al., 2013; Zarić & Nagler, 2021), we also looked at those three levels separately.

This led us to the following exploratory research questions:

  1. (1)

    Are differences in orthographic knowledge systematically related to differences in reading proficiency on the word-, sentence-, and text-level at same timepoint?

  2. (2)

    Do these differences also predict the development of reading proficiency over the course of a schoolyear?

Beside orthographic knowledge, we also included measurements of vocabulary and naming speed.

We expected word-specific and general orthographic knowledge to contribute significantly to reading on word-, sentence- and text-level, above and beyond vocabulary and naming speed. Furthermore, we were interested in examining the role of orthographic knowledge in the reading development over the school year. We hypothesized that the quality of orthographic representations (i.e., orthographic knowledge) would contribute significantly to reading development over the schoolyear. More precisely, higher level of orthographic knowledge with its two components should be helpful in storing new representations of words acquired during reading lessons over the schoolyear, and therefore be useful during the reading acquisition process.

Method

Participants

325 German children (mean age = 8.35 years, SD = 0.57; 49% girls) in the federal states of Hesse and Lower Saxony participated in the study. Parental consent was obtained for each child. The study was approved by a research ethics board.

Materials

Reading at word-, sentence-, and text-level

For measuring reading performance, the analog version of a standardized German reading test was used (Ein Leseverständnistest für Erst bis Sechstklässler– ELFE 1–6 [A reading comprehension test for first- till sixth-graders]; Lenhard & Schneider, 2006) once at the beginning and again at the end of a schoolyear. The three subtests measure reading at word-, sentence-, and text-level with a time-limitation. At word-level, reading is assessed through 72 items consisting of a picture and four-word alternatives, where the word corresponding to the picture needs to be chosen. Reading at sentence-level consists of 28 sentences which need to be completed by choosing one out of five possible word alternatives. Text-level reading is measured through 20 items, where participants need to process a connected text and a corresponding multiple-choice question. The authors report high internal consistency (word-level α = 0.97, sentence-level α = 0.93, and text-level α = 0.97). The sample used in this study had a slightly lower average reading comprehension level (T = 45.91) and slightly higher variance (SD = 11.49) compared with a norm sample.

Naming speed

For measuring naming speed, the RAN-matrix for letter naming (f, k, r, s, t) is used (see Denckla & Rudel, 1976). Participants are instructed to name the presented stimuli as fast and as accurately as possible. For further statistical analyses, the sum of correctly named items was used.

Vocabulary

For measuring vocabulary, the short version of a standardized German expressive and receptive vocabulary test was used (Wortschatz- und Wortfindungstest für 6- bis 10-Jährige—WWT 6–10; [Vocabulary and word retrieval test for children from the age 6 to 10 years], Glück, 2011). The participants are asked to name the 40 items (verbs, adjectives or nouns) presented on a computer screen. The authors report high internal consistency (α = 0.88). For further statistical analyses, the sum score of correctly answered items was used.

Orthographic knowledge

For measuring orthographic knowledge, item sets applied in previous studies by Zarić and colleagues (see Zarić et al., 2021; Zarić & Nagler, 2021; Nagler, Zarić, Kachisi, Lindberg, & Ehm, 2021) were used in a pen and paper version. For measuring orthographic knowledge, an orthographic choice task was used, where participants are asked to decide which of the two presented alternatives resembles a real German word the most. For assessing word-specific orthographic knowledge, 18 items were used, consisting of item-pairs of real words and their pseudohomophones (i.e., words with the same pronunciation as existing words, spelled incorrectly; e.g., word: rain, pseudohomophone: rane; internal consistency α = 0.79). For measuring general orthographic knowledge, 24 items were used, consisting of item-pairs of two pronounceable pseudo-words. One of the pseudo-words contains a double-consonant in a legal position (end position: e.g., dagikk central: e.g., hovvon,), whereas the other contains a double-consonant in an illegal position (e.g., bbitol); internal consistency α = 0.86).

Procedure

This study used data from the iLearn project (Schmitterer, Tetzlaff, Hasselhorn, & Brod, 2023; Tetzlaff, Edelsbrunner, Schmitterer, Hartmann, & Brod, 2023). The main aim of the iLearn project was to investigate effects of formative assessment in the context of third grade German lessons and it was funded by the German ministry of education and research. The project was run in 2 cohorts, one in the year 2018/19, the other in the year 2019/20. It consisted of a pretest at the beginning of the schoolyear and a posttest after the summer holidays. At both of these occasions, all students took part in a pen and paper test battery, comprising measures of reading comprehension administered to the whole class at once. At the beginning of the schoolyear, the orthographic knowledge of students was also assessed in a group setting.

In addition to the above-mentioned tests, a teacher-nominated subgroup of students (up to 8 per class in Hesse, all children in Lower Saxony) also participated in computerized 1-on-1 testing sessions where their vocabulary (WWT, Glück, 2011) and their naming speed (RAN, see Denckla & Rudel, 1976) was assessed.

Teachers in Hesse were asked to nominate students for these tests based on perceived reading difficulties and fill the remainder of the 8 slots with students they deem representative of their class. In Lower Saxony these computerized testing sessions were conducted with all students. This led us to a sample of 100 children for whom all relevant measures were collected. To ensure that our results are not based only on peculiarities of the teacher-nominated sample, we ran the same models without controlling for vocabulary and naming speed and put the results in the supplementary materials (see Tables 5 and 6).

Data preparation/analyses

For further analyses, multiple regression in hierarchical models with random intercepts were conducted using the lme4 package in R, since the students were nested in classes. Separate models for reading on word-, sentence- and text-level were calculated. For longitudinal models, we controlled for the reading comprehension at the beginning of the schoolyear (for an overview of advantages and disadvantages of controlling for the pretest vs. using change scores see Köhler et al., (2021).

Results

Table 1 contains descriptive statistics of the sample regarding the variables examined in this study at 1st and 2nd measurement time point.

Table 1 Means and standard deviations of all measures for T1 and T2
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The cross-sectional analyses

Table 2 contains the outputs of the cross-sectional analyses for all three reading levels (word, sentence, and text). The cross-sectional analyses revealed word-specific orthographic knowledge (ß = 3.21, p ≤ 0.001) and naming speed (ß = 1.70, p ≤ 0.05) to be significant predictors for reading on the word-level. On the sentence-level, similar results were found for word-specific orthographic knowledge (ß = 1.66, p ≤ 0.001) and naming speed (ß = 1.54, p ≤ 0.001). On the text-level, only naming speed (ß = 1.29, p ≤ 0.001) was identified as a significant predictor.

Table 2 The results of the cross-sectional analyses
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The longitudinal analyses

The results of the longitudinal analyses (see Table 3) revealed that both, word-specific (ß = 1.29, p ≤ 0.05) and general orthographic knowledge (ß = 1.62, p ≤ 0.05) are significant predictors for reading on word-level at the end of the schoolyear (second measurement time point), as well as the initial word-level reading at first measurement time-point (ß = 9.80, p ≤ 0.001). On sentence-level, only the initial reading at sentence-level (ß = 6.21, p ≤ 0.001) was a significant predictor for reading on sentence-level at the second measurement time point. On the text-level, word-specific orthographic knowledge (ß = 0.93, p ≤ 0.05), vocabulary (ß = 0.85, p ≤ 0.05), naming speed (ß = 0.65, p ≤ 0.05) and the initial reading on text-level (ß = 3.04, p ≤ 0.001) were shown to predict reading on text-level at second measurement time-point at the end of the schoolyear. Furthermore, we added interaction-terms to the models to test whether the influence of orthographic knowledge on the development of reading over the schoolyear (at second measurement time point) depends on the initial reading proficiency (at first measurement time point) on word-, sentence-, and text-level. None of those interaction-terms were significant predictors of the respective outcome variables (see Supplements, Table 4).

Table 3 The results of the longitudinal analyses
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Discussion

The following section entails discussion of the results of the present study. The findings from the cross-sectional and longitudinal analyses will be discussed separately.

The cross-sectional analyses

The results of the cross-sectional analyses have shown that word-specific orthographic knowledge and naming speed contributed to reading on word- and sentence-level. However, only naming speed was identified as a significant predictor to reading on text-level. Vocabulary and general orthographic knowledge were not identified as significant predictors to reading on word-, sentence-, and text-level when naming speed and word-specific orthographic knowledge were included in the model. These results indicate that the knowledge of specific word-representations and their quick retrieval from the memory play an important role for word- and sentence-reading performance, thus supporting previous findings (e.g., Zarić & Nagler, 2021). However, the findings regarding naming speed as a sole predictor for reading on text-level are not in line with previous results (Zarić & Nagler 2021), where only phonological awareness was a significant contributor to reading on text-level. The present study did not include a measurement of phonological awareness, thus the quick and fast retrieval out of the mental lexicon is identified as a sole crucial predictor for higher-level reading processes. In addition, Zarić and Nagler (2021) included only poor readers, while in the present study, an unselected, though with slightly under the average reading proficiency level, sample was examined. It is possible that for poor readers, phonological awareness might play a more important role in text-reading, while in slightly under the average readers, naming speed is an important skill for understanding text-passages.

The longitudinal analyses

The results from the longitudinal analyses have revealed that on the word-level, both word-specific and general orthographic knowledge significantly predicted word-reading at the end of the schoolyear, when controlled for the initial level of word-reading. The word-specific orthographic representations are, therefore, not only used to read words as single units (Conrad et al., 2013), but are also important for the reading development processes. More interestingly, general orthographic knowledge was not identified as a significant predictor for reading on word-level in the cross-sectional analyses, however, it was identified as a significant contributor in the longitudinal analyses. This indicates that general orthographic knowledge might not be important for word-level reading, however, it has an important influence for the word-level reading acquisition processes. General orthographic knowledge—including the knowledge about recurring letter patterns, consistencies, and regularities—might be helpful in memorization of specific letter combinations and units necessary to establish word-specific representations in memory during reading development (Conrad et al., 2013). Therefore, general orthographic knowledge can be considered as being a necessary prerequisite for making use of word-reading instruction, more so than for word-reading process itself.

Reading development on the sentence-level was not significantly predicted by orthographic knowledge, naming speed, or vocabulary knowledge. These results are contrary to our expectations based on the previous findings (Ise et al., 2014; Zarić et al., 2021; Zarić & Nagler, 2021). Orthographic knowledge was shown to have an important influence on sentence-level reading in the cross-sectional design, showing that orthographic representations facilitate the reading process. We thus expected it to also be related to development in sentence-reading. The fact that this was not the case implies that the influence of orthographic knowledge on sentence-level reading is already fully realized at the beginning of Grade 3 and its relevance diminishes for the acquisition of higher levels of proficiency (where other factors such as syntactic knowledge might play a bigger role). Previous studies have examined separate components for reading at different levels (i.e., word, sentence, and text; Abbott et al., 2010; Berninger et al., 2002). The findings suggest that there are intraindividual differences across these different levels of language (word, sentence, and text) for reading (e.g., Vellutino et al., 2004a, 2004b), suggesting that children could be adequate at decoding but not at sentence-level reading comprehension. In the present study, the examined sample has shown slightly lower than average reading proficiency and higher variance compared with a norm sample, indicating that there are higher interindividual differences between children. It is possible that the intraindividual differences between decoding and sentence-level reading might influence the reading development over the course of a schoolyear, demanding more individual material during the reading instruction. Since no similar findings were reported to our knowledge, we emphasize that further research is necessary in order to better understand the processes of sentence-level reading development over time.

Word-specific orthographic knowledge, naming speed, and vocabulary were all identified as significant predictors for the development of text-level reading over the course of one schoolyear. This indicates that word-specific representations, although not important to text-level reading examined in the cross-sectional context, significantly influences text-level reading development over time, measured in this case at the end of the schoolyear. It is possible that during the reading process, newly read and unknown words are memorized in the mental lexicon and over time, they support automatized recognition and reading of single words, thus, enabling their quick processing, and by doing so, more free resources are available for understanding the content of text passages. Similar results were shown for a sample of typical readers in a cross-sectional design (Zarić et al., 2021). General orthographic knowledge was not identified as a significant contributor, which is in line with previous findings (e.g., Zarić et al., 2021), showing that when both components were entered in the model, only word-specific orthographic knowledge remains a significant predictor. It seems that word-specific representations might play a more important than role than the knowledge about recurring letter patterns, not only for the reading process, but especially for the development of reading over a schoolyear (or for making use of reading instruction), while the latter supports word-reading development over time, as shown by the present results.

The results of the longitudinal analyses differed from the cross-sectional analyses, indicating that there might be differences between the influence of different reading relevant components for the process of reading and for reading development. At a general level, there are several potential explanations for these differences, two of which will be explained here: (1) different proficiency levels of the outcome measure might require different component skills. If the influence of a specific reading component skill is already fully realized at first measurement time point, it might be a significant predictor for the direct, first measurement time point reading performance. However, it will not offer additional explanatory power, if first measurement time point performance is controlled for when predicting second measurement time point reading performance. (2) Some components might not contribute to reading comprehension performance directly, but might be necessary to make sense of reading instruction—or at least specific forms of reading instruction (e.g., Tetzlaff et al., 2023). This would result in those components not being strong predictors for reading comprehension at first measurement time point, but offering additional explanatory power for reading comprehension at second measurement time point.

Naming speed, vocabulary knowledge and reading development

The results suggested that quick access to the stored mental representations (i.e., naming speed) facilitates reading of single words and understanding of the text-passages not just for the present, but also for reading development over time. These results are in line with previous findings, showing that naming speed is a strong predictor of present reading as well as reading development (Cardoso-Martins & Pennington, 2004; de Jong & van der Leij, 1999; Kirby et al., 2003; Poulsen et al., 2015).

The results of the present study revealed that vocabulary knowledge was not a significant predictor for the reading process, however, it played a significant role in the development of the text-level reading over the schoolyear. These results were not entirely contrary to previous findings. On the one hand, vocabulary was shown to be associated with word reading (Nation & Snowling, 1998; Taylor et al., 2015). Lindsey et al. (2003) could show that expressive vocabulary measured at the beginning of kindergarten contributed significantly to word identification skills at the end of the 1st grade, suggesting that early expressive vocabulary is important for later word identification abilities. It was shown that receptive vocabulary knowledge accounted for a significant amount of unique variance in reading comprehension, however, since listening comprehension and word identification skills were not included, it remains unclear whether the strength of this contribution would remain the same if word identification skills had been included in the analyses. Chiappe et al. (2004) could also show that expressive vocabulary knowledge was more strongly related to reading skills than receptive vocabulary knowledge. This might be a result of developmental differences across the examined sample (1st, 2nd, and 3rd grade).

On the other hand, Metsala’s (1997) analyses have shown that receptive vocabulary knowledge did not significantly predict word identification skills. Furthermore, it is assumed that listening comprehension contributes more to reading comprehension than vocabulary knowledge (Hagtvet, 2003). In this study, we used a short version of both, expressive and receptive vocabulary, and did not include them separately in the analyses. It is possible that a combination of receptive and expressive vocabulary measure did influence the results of the cross-sectional analyses, indicating that word specific orthographic-knowledge and naming speed, when included together with vocabulary, account more for reading on word-, sentence- and text-level and, therefore, reduce the influence of vocabulary. Similar effects were shown for longitudinal analyses for word-level reading. However, when considering reading development on the text-level, vocabulary knowledge was shown to be a significant predictor. As these different levels of reading build upon each other, these results are also in line with Tetzlaff et al. (2023), showing a positive effect of vocabulary-focused instruction on reading comprehension only for those students who already possessed a high level of reading proficiency. In addition, previous findings suggest a longitudinal, predictive role of vocabulary for reading comprehension development (Roth et al., 2002; Share & Leikin, 2004). Taken together, this evidence implies that vocabulary knowledge significantly facilitates and enables the acquisition of higher reading processes and text-passage comprehension, while not being as important for the acquisition of word- and sentence-level reading proficiency.

Limitations

This study explored whether the differences in orthographic knowledge were related to reading differences at the same timepoint, as well as whether they predict the reading proficiency development over time. There are some limitations worth mentioning. We did not include some reading relevant components, such as morphological knowledge and awareness or listening comprehension, which were shown to be important for reading processes (e.g., Verhoeven & van Leeuwe, 2012; Volkmer et al., 2019). Future studies should include more components to better understand their contribution to reading processes and development. In our study, we used a sample of German-speaking third graders with slightly below average reading proficiency level and higher variance than the norm sample. Therefore, the results cannot be generalized to other languages, age groups and reading proficiency levels. Future studies including different age groups and different reading proficiency levels are necessary in order to better understand the reading development and its influencing factors.

Summary and outlook

The results of the present study show that orthographic knowledge not only supports present reading processes, but also the acquisition of reading comprehension over the course of a schoolyear. The absence of significant interaction effects between orthographic knowledge and prior reading comprehension indicates that orthographic knowledge is relevant for reading development, independent of prior reading proficiency. In order to establish and strengthen causal interpretations, future research might focus on manipulating orthographic knowledge (e.g. via an intervention) and observing the effects of this manipulation on reading processes and reading development. The results also indicate that different levels of reading can be influenced by different components, and that these influences might vary through the reading acquisition process. Therefore, since orthographic knowledge does not only influence reading processes, but also reading development on different levels of reading, it should be considered in reading instruction at school and during reading related interventions.