1. Background
Language development is considered an essential part of mental development. Language is one of the main components of verbal reasoning as well as communicative and social interaction skills. Following the elegant expressions of [
1], from the first months of life, a child tries to ‘become a native speaker’ and ‘to be a proficient speaker’. ‘To become a native speaker’ means to learn the mother tongue, i.e., to acquire numerous language units and multiple rules and combine them for producing utterances following appropriate standards of phonology, vocabulary, and grammar. During this time, a child accumulates and elaborates a rich complex of declarative and procedural knowledge. ‘To become a proficient speaker’ means to master many complex and flexible skills and strategies for producing cohesive and coherent discourse texts according to multiple social and cultural traditions a child faces within his/her community. Despite the differences among numeral theories of speech/language development [
2,
3,
4,
5,
6,
7], scientists generally agree that during the first several years of life, a child makes many errors in the phonological, lexical, and grammatical domains. Along the second and third years of life, some children tend to use many frozen phrases and, thus, make fewer errors (i.e., the so-called expressive style of language development; see [
8,
9]). On the contrary, other children prefer to construct their utterances according to language rules they have deduced and make many more errors (i.e., so-called referential style of language development) [
8,
9]. According to a comprehensive longitudinal study based on the natural observation of native Russian language acquisition [
10], until the 7th year of life, typically developed (TD) children sometimes make grammatical or lexical errors. For example, by the age of 7 years, Russian speaking children usually have acquired noun morphology and select proper case forms (nominative, genitive, dative, accusative, instrumental or prepositional case) while speaking; however, Russian nouns fall under three declensions, and these are further divided into declension paradigms and their sub-types [
11]. The extremely complex system of noun declension provokes children to sometimes select incorrect declension forms (although the case form is usually selected correctly) even at the 6th–7th year of life [
9]. Besides incorrect declension forms, occasional omissions of functional words and production of neologisms may be also observed.
On the other hand, some errors made by children are obviously incidental and might be considered as slips of the tongue (SoT)—‘unintended, nonhabitual deviation(s) from a speech plan’ [
12] (p. 284). The phenomena of speech errors and SoT are usually explained differently. Speech error is usually recognized as a consequence of the temporary incomplete language competence [
13] or a result is the simplification processes in the programming of utterance inherent to children during language acquisition [
14]. Other explanations highlight the developmentally caused cognitive resource immaturity, which, in young children, underlies the inability to sustain error-free speech production [
15,
16]. There is considerable evidence that problem-solving activity and implicit learning are essential parts of language development [
17,
18,
19]. When a child is acquiring a native language, he/she tries to listen their caregivers and other communicative partners carefully to select the more informative grammatical, phonological, and semantical segments in the speech stream and try to attribute them to some extralinguistic events, objects, or features. Then, a child usually tries to repeat some piece of utterance and to control the concordance between the target word/phrase and his/her own production. Additionally, a child detects scaffolding from a child-directed speech containing positive or negative evidence [
20,
21]. This complex multimodal activity should be served by several cognitive abilities and skills, such as executive functions, selective auditory attention, working memory, self-monitoring, and strategy shifting [
14,
22]. Most of these cognitive resources are not completely mature until the 8th–11th year of life [
23,
24,
25]. The younger the child is, the more pronounced these limitations are. Later on, the maturity of the cognitive resources grows gradually along the preschool and school years [
14,
26,
27]. Though language competence and discourse skills develop rapidly, they remain incomplete until adolescence [
28]. Thus, in other words, children execute a complex work of learning a native language in the conditions of quite limited cognitive resources [
16]. In the majority of children populations, regular speech errors disappear before the 6th–7th year of life (although, in different languages, these milestones may differ) [
29].
However, let us look at the other direction of speech and language development, i.e., discourse development. It is well known that discourse production is loaded by some additional cognitive activities that depend on discourse genres.
Following [
14], the development of discourse skills and cohesion devices ‘[…] involves two different but related problems: (1) the reorganization of stored linguistic representations so that they can form a system, and (2) the creation of a control process which constrains connected discourse as it is produced in real time’ [
14] (p. 62). The control process managed by the self-monitoring subsystem plays a very important role in discourse development. As verbal communication strategies and linguistic devices, the discourse genres are determined by particular cultural traditions, and a child should learn them properly. Hence, employing problem-solving strategy [
19,
30,
31], he/she acquires some procedural knowledge and elaborates a set of unique skills. For example, a child has to acquire procedural knowledge necessary for planning and producing narrative, descriptive and other genres’ passages while building coherent discourse, for using proper discourse markers, etc. A set of verbal communication skills includes, for example, skills of self-monitoring during narration or conversation, turn-taking skills necessary in a dialogue, pragmatic skills (e.g., manipulation with different registers of communication), and many other verbal behavior skills [
32,
33]. During this period, the abilities of speech behavior self-monitoring are essential to reach the social-communicative standards. The development of self-monitoring proficiency depends on age [
14,
34,
35,
36] and the maturity of cognitive resources [
34]. In a few psycholinguistic studies of cognitive demands of different discourse genres, some evidence was obtained that, for example, a conversation is less demanding, while an expository discourse is more cognitively demanding than a narrative one [
37]. For example, in narrative production, a child has to arrange the story structure and to verbalize intentions and goals, emotions, and other mental states held by characters [
38,
39,
40]. When producing a spontaneous (unprepared) narrative, one has to develop a structure of events and produce oral discourse almost in parallel. This activity demands high resources. The basic skills that a child must acquire are the following: plan a logically well-organized semantic design, transform it into a relevant propositional structure, generate a verbal and syntactically cohesive text, and narrate it fluently to a listener. This activity is cognitively more demanding than a conversation by means of, for example, a dialog. High cognitive loading in the conditions of limited mental resources may result in a trade-off effect [
17,
41,
42]. Suppose the child feels this conflict between the task demands and his/her available resources. In that case, it is possible to explore several strategies: (a) to simplify the lexical or syntactic structure of the utterances or (b) to reduce or simplify the content the child intends to express in the discourse text [
43]. For example, it has been found that, in DLD children, the number of noun tokens per word within a story correlated negatively with a story structure, episode completeness, and CL/CU quotient; in TD children, correlations between the given measures were not evidenced. Moreover, in DLD children, visual story complexity significantly increased the percentage of noun tokens (which should be recognized as a negative characteristic for narratives) and the total number of grammatical errors. The more complex a visual story (according to the number of protagonists, actions, and semantically relevant features) was, the higher the noun percentage (during narration, verbs are used quite frequently (since they express actions/events), while nouns are more typical for descriptive texts. On the so-called ‘narrativity index’, see [
44].) and the number of grammatical errors were. Presumably, a child sometimes does not feel a conflict between the task demands and the limitations in his/her language resources and, thus, try to verbalize too sophisticated content by too complex language structures. In such a case, a risk of incidence of speech errors his/her discourse may rise.
It is common knowledge that in some children, lexical and grammatical errors stay rather resistant despite the normal intelligence, hearing, and/or the absence of gross neurological disorders. Children cannot master sufficient language skills without the remedial treatment provided by a speech/language pathologist. This subpopulation is usually recognized as developmentally language-disordered (DLD) children (formerly known as specifically language-impaired—SLI—children) [
45,
46,
47]. Different models of the DLD have been suggested. In some of them, it has been proposed that children with the DLD are not sensitive to main language markers and cannot process some language units (inflections, suffixes, prefixes, etc.) properly [
48]. In these models, the DLD is treated as deviance of language development and its leading cause is defined as the domain-specific impairment. ‘For many years, this was seen as a consequence of a deficit either in perceptual processing or in underlying language representations, depending on one’s theoretical persuasion’ [
49] (p. 5). However, in some studies, it has been found that the DLD children made the same errors as the younger TD children [
50]. For example, some comparative studies of grammatical features between the DLD children and younger TD children with the same MLU rate did not reveal any significant distinctions [
51].
Moreover, to review the basic lexical and grammatical errors in DLD children, most of them can also be found in TD children at the early stage of their language development [
52]. Thus, DLD children are recognized as children with delayed language development [
45]. Adherents of the given view believe that slow and improper language development in DLD children is not caused by the inability to learn language rules or low perception of particular linguistic features. Instead, it is supposed that the main limitations preventing these children from typical language development are limited cognitive resources domain-general models [
52,
53].
On the other hand, several studies in DLD children have revealed some weaknesses of the executive functions (EF), such as working memory deficit, low cognitive flexibility, selective inhibition deficit, and impulsivity [
54,
55]. The more complex the speech programming activity is, the more essential high EF resources are required [
56,
57]. During the utterance programming, different cognitive actions (lexemes and word form selection, serial order lexical arrangement, inflectional morphemes selection, etc.) compete for the cognitive resources [
22,
58].
As for speech/language errors in DLD children, it is usually implicated that their language drawbacks in discourse production are the same as in sentence production. However, some studies have revealed limitations in the discourse production only, which is not a consequence of the low language competence [
59,
60,
61]. The majority of such limitations were revealed in story (re-)telling. DLD children produced less structured and cohesive texts with poor macrostructure and erroneous microstructure in comparison to their TD peers [
43,
62,
63,
64]. Among the different causes of the discourse drawbacks, scholars have highlighted the cognitive resource deficit found in DLD children [
65]. It was found that many DLD children have weak EF [
66] and a small volume of working memory [
67]. In the DLD population, more severe and persistent EF deficiency prevents children from developing proficient language performance skills. Due to the deficit of EF, the error rate in DLD children discourse usually rises [
45]. It was established that in discourse production, different genres have distinct procedural demands [
68] and, thus, can provoke speech/language errors to different extents [
69].
Several studies have revealed that the discourse genre significantly impacts the part-of-speech distribution both in the TD and in the DLD children [
70]. Thus, it is reasonable to expect an impact of the discourse genre on the error rate in children’s speech. It was hypothesized that children’s errors while producing a discourse might have different domain-specific (linguistic limitations) and domain-general (cognitive resource deficit) mechanisms. The former should result in more regular errors, while the latter should result in more incident errors. It seems reasonable to expect speech error distribution to be a rather variable measure. Both in TD and DLD children, speech error number and distribution might be influenced by multiple variables, such as age, language competence, level of discourse skills, individual cognitive resource, genre of discourse, and/or register of communication. Thus, the quantitative statistical measures of the error distribution should be informative to understand the nature of errors.
The aim of the current research was to test the hypothesis that the cognitive loading of discourse may differently provoke lexical and grammatical errors in TD (at different stages of age) children and in DLD children (in comparison to TD peers). The prediction was that different biological age, as well as different registers of communication and the (sub-)type of discourse genres differently impact the distribution of lexical and grammatical errors. In study 1, we aimed at assessing the impact of age on the lexical and grammatical error distribution in different discourse genres in TD children. In study 2, we presumed to reveal differences between the impact of genre on the lexical and grammatical error distribution between the TD and DLD children.
2. Materials and Methods
According to the main aim of the current project, two data sets were composed. Study 1 enabled us to assess longitudinally a group of TD children and to elicit discourse texts of different genres from the same children at four different age stages (
Table 1 and
Table 2). In study 2, two groups of children (DLD as the experimental and TD as the control group) were assessed cross-sectionally and the same discourse genres as in study 1 were elicited in slightly different semi-experimental conditions (
Table 3 and
Table 4).
2.1. Data Collection in the Study 1
2.1.1. Participants
Participants were monolingual Russian-speaking children attending stated kindergartens in Saint-Petersburg, Russia (
Table 1).
Table 1.
Sample characteristics of study 1.
Table 1.
Sample characteristics of study 1.
N | 12 |
Mean age | Wave 1 | Wave2 | Wave 3 | Wave 4 |
4 years 3 months | 4 years 8 months | 5 years 3 months | 5 years 9 months |
Language | Russian |
City of residence | Saint-Petersburg, Russia |
Language development | Typically developing |
Inclusion criteria | Normal non-verbal IQ |
Exclusion criteria | Hearing and/or visual disorders |
Neurological disorders |
Speech and/or language impairment |
Non-verbal IQ on Raven’s matrix below 84 |
In all participants, the nonverbal IQ (according to the Raven’s Colored Progressive Matrices Test) was at a normal range (M = 109.13, SD = 5.44).
Initially, 36 children were selected for the study from a large sample of 60 children previously screened by the speech-language pathologist and confirmed as as typically developed children without any speech/language disorder. The 36 children passed as many as possible of the designed assessment sessions within each of the waves; however, a few of the children were excluded from the study after the 1st, 2nd, or 3rd wave due to different reasons; moreover, not all the children participated in all the assessment sessions. Thus, finally, for the current study, we selected 12 children of the most similar age, who passed all the waves and all the assessment sessions within each of the waves.
2.1.2. Procedure
The data contained genres such as personal narrative, fictional story (telling and retelling mode), chat, and discussion, in each wave of the assessment (
Table 2). The given genres were different from the perspective of form (monologue vs. dialogue) and register of communication (peer-directed vs. adult-directed speech). The size (the total number of words) of the data is presented in
Table 2.
Table 2.
The data of study 1. The total number of words.
Table 2.
The data of study 1. The total number of words.
Genre | Register | Wave 1 | Wave 2 | Wave 3 | Wave 4 |
---|
Personal narratives | Peer-directed speech | 1526 | 1869 | 3030 | 3164 |
Fictional stories (telling) | Peer-directed speech | 544 | 484 | 706 | 743 |
Fictional stories (telling) | Adult-directed speech | 576 | 541 | 557 | 868 |
Fictional stories (retelling) | Adult-directed speech | 593 | 674 | 618 | 794 |
Chats | Peer-directed speech | 1356 | 2406 | 3910 | 3216 |
Discussions | Peer-directed speech | 1332 | 1670 | 1932 | 1859 |
The conversational map methodology [
38] was modified by the authors of the paper to elicit peer-directed chats and personal narratives. During individual sessions, a child was given a doll (whose name was ‘the same as the child’s name’ and whose age was also ‘the same as the child’s age’), and then he/she was involved in a chat with another doll (the experimenter’s doll). In the flow of conversation, the experimenter’s doll told a personal narrative about some of his/her experience and then asked the child’s doll whether she/he has had a similar experience. In response to the given prompts, the children usually told personal narratives about similar experiences (events that had happened with the child or his parents/grandparents/siblings/friends, etc.). While a child was telling his/her narrative, the experimenter tried to minimize her impact, i.e., she did not help the child, did not ask any questions, and did not make any corrections. The only allowed prompts were neutral remarks, such as ‘Uh-huh’, or a repetition of the exact previous words of the child. In each of the waves, three personal narratives were elicited from each child. The experimenter introduced the following topics in the prompt narratives: shopping in a supermarket, visiting a doctor, a journey to a zoo, swimming in a lake, and some others familiar for children of the given culture and lifestyle. Moreover, the children were allowed to tell personal narratives on any topic they offered.
To elicit adult-directed fictional stories, the children were asked to tell and retell a story according to different picture sequences. In each of the waves, we used two picture sequences consisting of six colored pictures each; the protagonists of the picture sequences were animals quite familiar for children of the given culture and lifestyle (e.g., cats, dogs, mice, crawls) but one of the stories was always more complex than another one. The pictures were designed by the authors of the paper and painted by a professional artist, Ms. Unė Kurtinaitytė. During the assessment, the experimenter first placed the pictures in the correct sequence in a single, horizontal row in front of a child. Then, the child was allowed to look at the pictures to get the gist of the story (the time was unlimited). Next, the child was asked to tell a story according to the pictures (for the telling mode) or to listen to the story read by the experimenter and then to retell it (for the retelling mode). During the telling/retelling process, the pictures were still on the table and, thus, a child had a possibility to look at them all the time of assessment. The order of the tasks was counterbalanced regarding story complexity (easier story vs. more complex story) and task mode (telling vs. retelling). Sessions of the 1st and 2nd tasks were separated by a few minutes of chat between the experimenter and a child.
To elicit peer-directed fictional stories and discussions, we used the same dolls for stimulating the personal narratives and chats. At the beginning of the assessment, the experimenter’s doll demonstrated hand-made his/her ‘favorite book with pictures inside’ and offered the child to look at them. Then, the experimenter’s doll ‘accidentally‘ dropped the book, and the images spilled on the table (the images were not stuck initially to the pages of the book). The experimenter’s doll asked the child’s doll for help and they both tried to place the pictures to repair the picture sequence. During this activity, the experimenter’s doll offered erroneous versions of the picture sequence, asked many provoking questions, and, thus, involved the child in a discussion.
2.2. Data Collection in the Study 2
2.2.1. Participants
Participants were 10 monolingual Russian-speaking children with DLD and 14 TD peers (see
Table 3).
Table 3.
Sample characteristics of study 2.
Table 3.
Sample characteristics of study 2.
| Experimental Group (DLD) | Control Group (TD) |
---|
N | 10 | 14 |
Mean age | 6 years 5 months |
Language | Russian |
City of residence | Saint-Petersburg, Russia |
Language development | Primarily impaired | Typically developing |
Inclusion criteria | Normal non-verbal IQ | Normal non-verbal IQ |
Clinically referred DLD | |
Exclusion criteria | Language comprehension disorders | Speech and/or language impairment |
Hearing and/or visual disorders |
Neurological disorders |
Non-verbal IQ on Raven’s matrix below 84 |
DLD children were clinically referred and received a two-year course of speech therapy (five sessions a week) at the kindergarten; nevertheless, various phonetic, lexical, and grammatical errors still occurred in their speech data. Before the experiment, all the children were assessed by a speech-language pathologist by means of Russian language assessment tools [
50] in order to confirm the TD vs. DLD status and to exclude children with language comprehension disorders from the experiment. (Children with language comprehension disorders were excluded to escape the non-relevant variable impact and to highlight the discourse production features related to the expressive language limitations.) Thus, the experimental group in our study may be characterized as DLD children with language expression but not comprehension difficulties. Nonverbal IQ (according to Raven’s Colored Progressive Matrices Test) was at a normal range in both groups (
M = 113.25,
SD = 3.15 in the DLD;
M = 121.00,
SD = 4.90 in the TD).
2.2.2. Procedure
The data contained genres such as fictional story (telling and retelling) and discussion (
Table 4). The given genres were different from the perspective of the form (monologue vs. dialogue) but belonged to the same register of communication (adult-directed speech). The size (the total number of words) of the data is presented in
Table 4.
Table 4.
The data of study 2. The total number of words.
Table 4.
The data of study 2. The total number of words.
Genre | Register | DLD | TD |
---|
Fictional stories (telling) | Adult-directed speech | 520 | 1130 |
Fictional stories (retelling) | Adult-directed speech | 314 | 1156 |
Discussions | Adult-directed speech | 6249 | 8687 |
The children were asked to tell and retell a story according to different picture sequences to elicit fictional narratives. The order of the tasks was counterbalanced regarding story complexity (as in study 1, one of the stories was easier, while another one was more complex) and task mode (storytelling vs. retelling). The methodology has been previously presented in several publications [
43,
71].
To elicit discussions, the ‘nonsense picture method’ [
72] was employed. An experimenter demonstrated a child a picture with an unrealistic scenario (e.g., a cow sitting on a tree, a pig flying in the sky, etc.) and asked the child to evaluate its plausibility. During the conversation, the experimenter asked the child as many as possible provoking questions and tried to involve the child in a discussion [
72].
2.3. Development of the Corpus of Russian Children’s Language
The data (audio-records of the sessions) were transcribed orthographically using CHAT tools [
73]. Two experts double-checked the transcriptions independently and extended them by encoding for language errors and linguistic dysfluencies to perform automated analysis using CLAN tools [
73]. The data analyzed comprised, in total, 45, 942 words without mazes.
2.4. The Analyzed Variables
Russian is a highly inflective and morphologically rich language with many grammatical categories. First, Russian nouns are specified as animate vs. inanimate. Furthermore, as mentioned above, Russian nouns fall into three declensions related to the gender form and may be further divided into different declension paradigms; moreover, nouns involve two number forms and six case forms. Each Russian verb is specified for perfective vs. imperfective aspect; the given forms of aspect are differentiated by prefixation, suffixation (or a combination of them), and root alternation (suppletion). Verbs are also specified for reflexive vs. non-reflexive form, they involve three tense forms (past, present, and future tense) and three mood forms (indicative, imperative, and conditional). There are five participles different in passive vs. active form and in perfective vs. imperfective aspect. Participles are declined as adjectives; the two indeclinable adverbial participles are often called gerunds. In Russian, nouns agree with their modifiers in gender, case, and number; verbs agree with nouns and pronouns in gender, person, and number. Word order in Russian is syntactically flexible and determined by pragmatics [
11]. The most common syntactic structure ‘subject-predicate-object may have up to 30 possible word order variants, including six with the subject omission [
74]. In addition, subordination using participles and gerunds instead of relative and adverbial clauses is common in Russian.
A significant number of studies in Russian child language has been devoted to grammar acquisition [
10,
75,
76], and, thus, the qualitative features of morphological errors in the early noun, verb, pronoun, and adjective production are well-studied; however, quantitative studies have been carried out much rarely, especially at the later stages of language acquisition. Similarly, the qualitative features of lexical and derivational errors have been widely analyzed [
77,
78], however, we still lack knowledge about their quantitative features. Therefore, this study analyzed both qualitative and quantitative features of the following types of language errors, as exemplified below.
Lexical errors were considered as cases in which the child referred to something by another name. In our corpus, lexical errors fell into (a) hyponyms replaced by hyperonyms (e.g., ‘mouse’s house’ instead of ‘mouse’s hole’), (b) hyperonyms replaced by hyponyms (e.g., ‘chicken’ instead of ‘baby-bird’), and (c) incorrect selections within words of the same semantic group (e.g., motion terms ‘to go’, ‘to run’, and ‘to fly’).
Morphological errors were considered as cases in which the child selected an inappropriate form for marking the case, declension paradigm, gender, number, person, tense, aspect, mood, or other morphological categories. Typical examples of morphological errors were as in the following:
(1) Tam byla [= byl] poni. ‘There was:FEM [= was: MASC] a ponny: MASC.’
(2) Koshka zabiralasj [= zabralasj] na derevo. ‘The cat was climbing [= climbed] up the tree.’
In the case (1), the child used a feminine form for the word ‘was’ instead of a masculine form, while the noun ‘ponny’ falls to the masculine gender. In the case (2), the child used incorrectly an imperfect aspect form instead of the proper perfect form.
Syntactic errors were divided into (a) the agreement errors, (b) the government errors, (c) the incorrect prepositional constructions, (d) the omissions of functional words, (e) the incorrect word order, and (f) other ’messy sentences’. Typical examples of the syntactic errors were as in the following:
(3) Ona stala zalezatj k derevu [= na derevo]. ‘She started climbing to [= up] the tree.’(4) Ptica ne mozhet letatj s vodoj [= v vode]. ‘A bird cannot fly with [= in] a water.’
In both cases (3,4), the child used incorrect preposition (although the government of the preposition on the noun case form was correct). The given syntactic errors (3,4) not only destructed the sentence but also involved inappropriate semantics.
Derivational errors fell into (a) the incorrect prefixation, (b) the incorrect suffixation, and (c) the incorrect compounding. Usually, derivational errors were occasional word-forms constructed by a child (e.g., a diminutive form of ‘a pet’ or ‘a swing’ that are possible theoretically but do not exist in Russian).
During statistical analysis, the quotient for each type of error was estimated by dividing the number of errors of the given type by the total number of words in the corpus. Thus, four different quotients were estimated: (1) the lexical error QL, (2) morphological error QM, (3) syntactic error QS, and (4) derivational error QD. The statistical difference between the measures was calculated by means of the ANOVA (in the case of normally distributed variables) or by the Mann–Whitney U criterion (in the case of non-normally distributed variables). The MANOVA (general linear model—GLM) was applied to estimate the determinants’ impact on the dependent variables.
4. General Discussion on the Study 1 and Study 2
Our two studies evidenced that the correctness of speech production in the same children is not a constant measure. The high variability of error scores was significantly influenced by the genre of discourse and the age of participants. Thus, our prediction about the impact of the genre on the error rate was confirmed. This may be explained by the different cognitive loading of different genres. These data are congruent with our previous studies where the genre impact on the distribution of phonological structures (types of syllables with different complexity) [
71] and on the part-of-speech profile [
70] was evidenced.
It should be noted that the distribution of the percentage of different types of errors was very similar between the TD and DLD children. However, the latter made significantly more lexical errors.
According to the traditional attitudes of speech/language pathology, low language competence is the main distinction between language disorders and TD children. The development of language competence is usually equated to the score of correct responses in language battery tasks (the proper response is considered the response without errors). Thus, it is implicitly suggested that typically developed children do not make any errors. However, this suggestion is not true. Both adults and children make errors and slips of the tongue in their colloquial speech [
2,
86]. While there are plenty of psycholinguistic studies of errors in colloquial speech in adults, scarce data are available regarding colloquial speech and errors in children. From the psycholinguistic and psychological perspective, speech is some kind of behavior consisting of multiple skills. From this perspective, procedural knowledge acquisition in speech development is in close relation to mastering relevant skills.
In linguistic studies of children’s language, speech errors are recognized as a sign of limited language competence. However, language competence is usually rather stable, and its limitations are expected to manifest approximately similar to different speech acts.
Like many other skills, each new speech skill passes through a stage of unstable, variable execution, and automation. The less mature and automated the skill is, the more variable it is, and the more mistakes are made [
87,
88]. The number of errors the subject makes is a manifestation of the skill’s instability. From the perspective of this regularity, speech errors mark the weak chains in a particular speech/language subsystem. In the scope of this suggested model, higher rates of lexical and morphological errors, compared to syntactic and derivational errors, mean that the syntactic and derivational subsystems, in 4–5-year-old children, are more matured and automated and, therefore, children make fewer errors. For the same reason, the syntactic and derivational errors were less sensitive to age and genre.
The main limitations of our study were relatively small size of the sample and quite narrow range of cognitive assessments. In the framework of the ongoing investigation, we are replicating the longitudinal study (with an application of all methods and approaches employed in the given study 2) in DLD children. This will enable us to compare a process of discourse acquisition between the TD and DLD children from different perspectives, including error analysis.