TYPE Original Research PUBLISHED 06 January 2023 DOI 10.3389/fpsyg.2022.1052264 In a split second: Handwriting OPEN ACCESS pauses in typical and struggling writers EDITED BY Åsa Wengelin, University of Gothenburg, Sweden REVIEWED BY Mariona Pascual 1,2*, Olga Soler 3 and Naymé Salas 2 Olivia Afonso, Oxford Brookes University, 1 Research Center for Psychological Science (CICPSI), Faculdade de Psicologia, Universidade de United Kingdom Lisboa, Lisboa, Portugal, 2 Facultat de Ciències de l’Educació, Universitat Autònoma de Barcelona, Rui Alexandre Alves, Barcelona, Spain, 3 Facultat de Psicologia, Universitat Autònoma de Barcelona, Barcelona, Spain University of Porto, Portugal Introduction: A two-second threshold has been typically used when analyzing *CORRESPONDENCE Mariona Pascual the writing processes. However, there is only a weak empirical basis to claim mariona.penas@psicologia.ulisboa.pt that specific average numbers and durations of pauses may be associated SPECIALTY SECTION with specific writing processes. We focused on handwriting execution pauses, This article was submitted to Educational because immature writers are known to struggle with transcription skills. We Psychology, a section of the journal Frontiers in Psychology aimed to provide an evidence-based account of the average number and RECEIVED 23September 2022 duration of handwriting pauses in the mid-Primary grades and to identify ACCEPTED 09 December 2022 process-level markers of writing difficulties. PUBLISHED 06 January 2023 Methods: Eighty 3rd and 5th graders, with and without writing difficulties, CITATION Pascual M, Soler O and Salas N (2023) In a participated in the study. We examined pauses in a handwriting-only task, split second: Handwriting pauses in typical to be able to isolate those which could only be attributed to handwriting and struggling writers. processes. Letter features were considered, as well as children’s handwriting Front. Psychol. 13:1052264. doi: 10.3389/fpsyg.2022.1052264 fluency level. COPYRIGHT Results: The average duration of handwriting pauses was around 400ms, in © 2023 Pascual, Soler and Salas. This is an line with assumptions that transcription pauses would fall under the 2,000ms open-access article distributed under the terms of the Creative Commons Attribution threshold. We found that 3rd graders made more and longer pauses than 5th License (CC BY). The use, distribution or graders. Struggling writers made a similar number of pauses across grades reproduction in other forums is permitted, than typically-developing children, although they were significantly longer, provided the original author(s) and the copyright owner(s) are credited and that even after controlling for the effect of handwriting fluency. the original publication in this journal is cited, in accordance with accepted Discussion: Our findings provide an evidence-based account of the duration academic practice. No use, distribution or of handwriting pauses. They also suggest that children need fewer and shorter reproduction is permitted which does not handwriting pauses as they progress in automatizing transcription. However, comply with these terms. some young writers struggle with letter formation even after 3 to 5 years of instruction. KEYWORDS writing process, writing difficulties, pause analysis, handwriting, letters (alphabet), struggling writers 1. Introduction It is a well-established fact that writing development is best understood from a process perspective (Hayes and Flower, 1980; Berninger et al., 1996; Alamargot and Chanquoy, 2001; Graham et al., 2018). Much like speaking, when writing we only produce a number of words at a time, before needing to pause (Chenu et al., 2014). Frontiers in Psychology 01 frontiersin.org Pascual et al. 10.3389/fpsyg.2022.1052264 Writing pauses are defined as periods of graphic inactivity, and at which point may pauses be attributed to the execution of pausing time can account for up to half the time to compose a transcription or high-level writing processes. text (Strömqvist and Wengelin, 1999; Alamargot et al., 2007). Second, the vast majority of investigations examined pauses Despite the pervasive presence of pauses during written taking place during text composition, and made an assumption composition, the reasons why writers of different competence about what underlay different pause durations, instead of adopting levels pause are not well understood. a data-driven approach. For example, Prunty et al. (2014) defined Pauses during text production could be the result of four types of pauses, based on their duration, which were based immature transcription, such as difficulty to retrieve letter on previous literature: (1) between 30 to 250 ms, which were formation motor programs or spelling representations, or of assumed to indicate letter-formation processes; (2) between the execution of higher-level writing processes, like planning 250 ms to 2 s, considered to indicate between-letter pauses; (3) or revising (Olive et al., 2009; Alamargot et al., 2010). As between two to 4 s, signaling word-level pauses; and (4) above 4 s, children’s transcription becomes more fluent overtime, the which were considered to represent a higher level writing process duration and number of pauses, on average, decreases (Alves (generating ideas) or to indicate “fatigue or a lack of writing ideas” and Limpo, 2015; Palmis et al., 2017). This developmental (p. 2898). Notably, the pause duration range for handwriting trend points to the pivotal role of transcription skills in the execution was based on a study with only five participants, management of the writing process. For this reason, including school children and up to expert adult writers we examined pauses exclusively related to transcription (Alamargot et al., 2010). Similarly, the threshold assumed for processes; more specifically, to handwriting execution. word-level pauses (250 ms–2 s.) was adapted from findings for Hebrew-speaking children with or without a coordination disorder (Rosenblum and Livneh-Zirinski, 2008). In short, there 1.1. Methodological issues in the study of is only a weak empirical basis to support assumptions about which writing pauses processes are being executed during pauses. Because most investigations analyzed pauses within the context of a text writing Current research often reports diverging findings with regards task, it is virtually impossible to safely attribute pauses to one type to what do pauses reveal about the writing process. For example, of writing process (Olive et al., 2009). it is not clear whether more pauses indicate more or less writing competence. For example, Connelly et al. (2012) reported a negative correlation between the number of pauses and a measure 1.2. Previous research on handwriting of text quality, whereas a group of undergraduate students in pauses Alamargot et al.’s (2010) study paused more often than a group of 5th graders. In this sense, Ailhaud et al. (2016) found evidence To understand the duration of handwriting pauses, some that the activity during pauses may change as a function of the studies have measured the length of inter-letter or inter-syllable syntactic unit at hand in combination with the age and expertise intervals during handwriting execution. The values obtained in of participants. They found that pauses before T-units of text were these studies can be used as a guideline for establishing the longer for older students (Grade 9), while pauses before highly- thresholds for handwriting pauses. Studies on syllable governed clause constituents (e.g., subordinate clause) became programming by preschool children found inter-letter and inter- shorter with age. syllable intervals of a minimum of 1 second (Soler-Vilageliu and The conflicting findings in the literature on writing pauses Kandel, 2012), whereas a study with adults comparing inter-letter may be related to the fact that studies differ in how they define intervals in simple and complex syllabic structures reported pauses. A majority of studies have defined a pause as a period of average values of around 90 ms in simple syllables and of up to graphic inactivity of 2,000 ms or longer, which is assumed to 155 ms for complex syllables (Kandel et al., 2008). All in all, this be devoted to higher-level writing processes (Alves et al., 2019). body of evidence seems to indicate that pauses at or around Pauses under that threshold have been assumed to be due to the 100 ms are related to the motor execution of handwriting in adults, execution of transcription (i.e., lower level) processes (e.g., but children may require considerably longer pauses to deal with handwriting, spelling; Wengelin, 2006; Brizan et al., 2015; tracing letters and spelling out words. In this study we identified Medimorec and Risko, 2017). all handwriting pauses starting at 100 ms. A minimum of 100 ms However, there are at least two methodological issues with the has been found to be the lowest stroke-duration threshold for the “default” 2,000 ms threshold and what it entails. First, studies differ analysis of writing processes (Maarse et al., 1989; Plamondon, widely in their adoption of a pause threshold. A review of studies 1991; Schomaker, 1991; Van Galen, 1991; Kandel and Soler, 2010; that collected process data of texts written by hand (Table 1) shows Kandel and Perret, 2015). that some have looked at pauses starting below 100 ms (e.g., In addition, some properties of letters are likely to influence Chenu et al., 2014; Drijbooms et al., 2020), while others measured the nature of handwriting pauses. Letter case (i.e., uppercase v. pauses at or above 10,000 ms (Prunty et al., 2016a,b). Therefore, lowercase) and letter type (e.g., cursive v. print) are relevant factors there is great disparity in the very definition of what a pause is and that should be considered when studying written execution. Frontiers in Psychology 02 frontiersin.org Pascual et al. 10.3389/fpsyg.2022.1052264 TABLE 1 Summary of tools, thresholds and tasks in a selection of previous studies. Tool Age range Threshold Task Alamargot et al., 2010 Eye and pen 12 to 18 yo and adults 15 ms Narrative text Alamargot et al., 2021 Eye and pen 10 to 12 yo 20 ms Name writing Alphabet task Alves and Limpo, 2015 Handspy 7 to 13 yo. 2000 ms Narrative text Opinion essay Alves et al., 2016 Handspy 7 and 8 yo. 30 and 2000 ms Narrative text Handwriting tasks Alves et al., 2019 Handspy 7 and 8 yo. 30 and 2000 ms Narrative Text Handwriting task Beers et al., 2017 Inputlog Eye and Pen 9 to 15 yo. 2000 ms Narrative Text Handwriting task Copy Task Chenu et al., 2014 Eye and Pen 10 to 15 yo. 15 ms Narrative text Expository text Connelly et al., 2012 Eye and Pen 11 yo. 2000 ms Writing task “One day I had the best weekend ever..” Dockrell et al., 2019 Eye and Pen 8 and 11 yo. 2000 ms CBM Writing Task (McMaster and Espin, 2007) Drijbooms et al., 2020 Eye and Pen 11 yo and adults 35 ms Narrative text Maggio et al., 2012 Eye and Pen 7 to 15 yo. – Narrative Text Olive et al., 2009 Eye and Pen undergraduates >250 ms (writing) < 250 ms (copy) Narrative and copy task Prunty and Barnett, 2017 Eye and Pen 8 to 14 yo. 30 ms DASH (Barnett et al., 2007) Prunty et al., 2014 Eye and Pen 8 to 14 yo. 30 ms Free writing task (DASH; Barnett et al., 2007) Prunty et al., 2016a Eye and Pen 8 to 14 yo. 10,000 ms Free writing task (DASH; Barnett et al., 2007) Prunty et al., 2016b Eye and Pen 8 to 14 yo. 10,000 ms Free writing task (DASH; Barnett et al., 2007) Prunty et al., 2020 Eye and Pen 8 to 14 yo. – DASH (Barnett et al., 2007) Van Hell et al., 2008 OASIS 10 to 25 yo. – Narrative and expository tasks Different allographs may pose different cognitive and motor (Kim et al., 2011; Arfé et al., 2020). Moreover, this task has been demands, especially to young writers (see Pagliarini et al., 2015 for found to efficiently identify handwriting difficulties (Rosenblum a study where case was controlled across populations), but also and Livneh-Zirinski, 2008). Other types of tasks, such as copying adult writers seem to be affected by the type of letter they write. tasks, do not tap into the graphemic buffer, which is intrinsic to For example, Bourdin and Fayol (1994) showed that when adults any handwriting task (Alstad et al., 2015). As it happens, were told to remember a series of words using uppercase, cursive neuropsychological research has found that letter writing can letters they recalled significantly fewer words than when they used activate more neural systems than copying or passively recognizing a more familiar script. Finally, familiarity with a particular script letters, which do not require recruiting as many neural areas type and case may also be influenced by other factors. Teachers in (James and Gauthier, 2006). We focused on this type of pause Spain provide instruction on uppercase print writing to children because handwriting has been found to be one of the most in preschool but, from grade 1 onwards, children are taught to constraining processes in early writing development (Alves and write using cursive letters almost exclusively. Moreover, children’s Limpo, 2015). In addition, some studies have suggested that books are often written in cursive, and after an initial exposure to struggling writers show an alteration in the nature of their pause print uppercase, schools include cursive teaching in their curricula patterns (Sumner et al., 2013). Therefore, investigating the nature (Graham et al., 1998; Schwellnus et al., 2012; Bara et al., 2016). of handwriting processes should allow us to better understand key In order to contribute to clarifying these conflicting findings, drivers of development of writing and potential causes of in this paper we investigated the nature of a specific type of pause: writing difficulties. Those due exclusively to handwriting execution. We considered While there is a growing body of evidence suggesting that pauses the alphabet task (Berninger et al., 1992), given that it taps directly are sensitive to the expertise of the writer (although it is not clear into the retrieval of graphemes from memory and into the visuo- exactly how so, as pointed above), less is known about process-level motor integration skills required to reproduce letters in writing markers of writing difficulties. Some studies looking at writing Frontiers in Psychology 03 frontiersin.org Pascual et al. 10.3389/fpsyg.2022.1052264 pauses in children with sustained writing difficulties found no research question (2), we hypothesized that letters involving more differences with a group of typically-developing peers in their strokes and letters written in print would be associated with longer average pause time or number (Pascual, 2020). However, other pause durations, given that they increase the difficulty of tracing studies have found that dyslexic children pause more often (Sumner the letter, while the cursive-linking features entail fewer pen lifts et al., 2013, 2014; Beers et al., 2017, 2018) and that there is a rhythmic (Morin et al., 2012). Our hypothesis for research question (3) was constraint in children with dyslexia and dysgraphia that hinders their that 5th grade children would show shorter pause durations, and speed which, in turn, has a relationship with reading and language fewer pauses per letter on average, than 3rd grade children, as the development (Lam et al., 2011; Pagliarini et al., 2015). Alamargot former would have more automatized transcription processes et al. (2021) found that dyslexic children needed more time to than the latter (Alves and Limpo, 2015). Finally, with regards to produce letters and made more handwriting pauses (especially those research question (4) we expected struggling writers to have under 200 ms) than age-matched peers. However, they did not slower handwriting fluency, which would be reflected in longer consider pauses above 1,000 ms duration; thus, it is not clear whether average pause durations and more pauses per letter in comparison there could be longer pauses during handwriting execution. In this to typically-developing peers (Sumner et al., 2013). paper, we investigated whether a group of struggling writers showed differences in the nature of handwriting pauses in comparison with a group of age-matched, typically-developing students. 2. Materials and methods 2.1. Participants 1.3. This study Drawing from a larger study on literacy development, The present study aimed to provide an evidence-based we randomly selected a group of 83 students, of which 67 were account of the average number and duration of handwriting typically-developing (TD) students (34 boys) attending 3rd and pauses in a language with a semi-consistent orthography 5th grade (Table 2 shows participants’ distribution and (Catalan). Four main characteristics of the study make it an demographic characteristics), and 16 students (12 boys) struggled improvement over previous research on writing pauses: (1) it with handwriting. The families of all participants consented to examined pauses in a handwriting-only task (writing the alphabet their participation in the study. Children with handwriting letters continuously for a short period of time). In this way, difficulties (HWD) had been identified in a previous study by their we were able to isolate pauses which could only be attributed to consistent performance below -1SD (p < 0.001) across two handwriting processes and not to other lower- or higher-level handwriting tasks (Figure 1 shows initial differences per group writing processes, in contrast to most previous studies; (2) it and grade in the alphabet task; Pascual and Salas, 2021). This considered all pauses starting at 100 ms, and controlled for key initial identification, carried out when children were attending properties of letters (e.g., type of script, number of strokes per grades two or four, was further supported by a follow-up study letter); (3) it tested the effect of Grade (3rd, 5th) and Population 16 months later, where we found that their poor performance in (typically-developing v. struggling writers), thus allowing to handwriting tasks persisted, and it affected several text-based observe any developmental trends and to identify process-level measures, including text generation and spelling (Pascual, 2020). markers of writing difficulties; and (4) used a friendlier longhand Of the initial sample, three students were discarded for writing writing device (smart pen), rather than other, less ecological alternatives, such as a writing tablet or a keyboarding setting. TABLE 2 Demographic data and characteristics of participants across groups. Our research questions were as follows, TD WD 1. What is the average duration and number of pauses that are Grade 3 Grade 5 Grade 3 Grade 5 due to handwriting execution? M (SD) M (SD) M (SD) M (SD) 2. Which letter features (i.e., number of traces required, N (boys) 30 (14) 34 (19) 10 (8) 6 (4) cursive v. print) influence the average number and duration Mean age 8;8 (0;4) 10;10 (0;3) 8;8 (0;3) 10;10 (0;4) of handwriting pauses? 3. Do pause duration and number decrease as a function of HWF* 6.11 (1.92) 8.95 (2.75) 2.45 (0.82) 4.43 (0.54) schooling experience? Identification 4. Is pause duration or number of pauses a process-level Score marker of writing difficulties? ISEI Score 59.35(14.35) 65.39 58.86 60.38 (6.28) (16.76) (15.02) With regards to research question (1), we hypothesized that TD = typically developing group; WD = writing difficulties group; HWF = handwriting handwriting pauses would have an average duration under fluency (alphabet task); ISEI = International Socio-economic Index Score (Ganzeboom et al.,1992). *The data was collected when struggling students were identified a year 2,000 ms, in line with suggestions from previous research (Alves before the current study; that is, when the Grade 3 group was attending 2nd grade, and et al., 2007; Wengelin, 2007; Prunty et al., 2014). With regards to the Grade 5 children were attending 4th grade. Frontiers in Psychology 04 frontiersin.org Pascual et al. 10.3389/fpsyg.2022.1052264 In addition, we considered some letter properties. Although children had been instructed to use lowercase print letters, they did not always comply. Therefore, each letter production was coded for script type, distinguishing between cursive, print lowercase, or print uppercase, and this information was used in all analyses. In addition, the number of strokes needed to trace each letter (based on Soler and Kandel, 2009, who adapted Meulenbroek and Van Galen, 1990) was used as an independent variable in all analyses.1 2.3. Procedure The task was part of a larger test battery administered at the FIGURE 1 end of the school year (May–June) of 3rd and 5th grade in two Descriptive plots of the initial identification handwriting task, as sessions. Students were assessed in groups of five in a quiet place found in Pascual (2020). at the school across two 40-min sessions. The handwriting task was carried out last in session 1, preceded by an opinion essay writing task and a spelling task. letters as strings of cursive without lifting the pen between them The handwriting task was carried out using Neo Smartpens as indicated by the administrator. Thus, our final sample of TD ® ® M1 , writing on Neonotes Pads . Smartpens connect through students was of 64 participants (33 boys). infra-red cameras to record the coordinates of the writing strokes. Given the high variability in students’ proficiency with M1 pens weigh 17.4 g and are 149.6 mm long, being only slightly Catalan, which is both the language of instruction but also a ® heavier than a regular pen. The sheets on N idea pads are ruled minority language, it was important to ensure that our participants line sheets with micro-dotted patterns (NcodeTM technology), belonged to a context in which Catalan was frequently used, not which allow pens to record the coordinates of the stroke, just within schools, but particularly outside the school setting. recognizing the spatial–temporal traces on a specific page. This Therefore, students were recruited from three public primary ® recording is then paired to the Neonotes app, from which data is schools in medium-high socioeconomic districts in Barcelona, a transferred via Bluetooth to a tablet. bilingual Catalan-Spanish community in Spain. Usage of Catalan is linked to skilled occupation and to higher academic achievement in adults (Idescat, 2015). Moreover, we administered 2.4. Data analyses sociolinguistic questionnaires to assess the Socio-Economic Status, using Ganzeboom et al. (1992) International Socio- The output from the Neonotes app was analysed using Economic Index (ISEI). The average ISEI score was 62.5 ® Handspy , a software specifically developed to assess online (SD = 11.34); therefore, on average, these students’ families ranked writing processes (De Sousa and Leal, 2013; Monteiro and Leal, in the 70th percentile of the ISEI (a detailed ISEI score per group 2013; Alves, 2019). Each page is transformed through the XML and grade can be found in Table 2). No significant statistical markup language to a protocol, which displays the strokes and differences were found between groups on ISEI score, F (2, pauses in different logs. Pause duration is automatically displayed, 70) = 0.807, p = 0.372. as well as stroke duration. Before analyzing the measures, protocols were cleaned to account only for the pause duration and pause number within the task and thus eliminate registries that 2.2. Tasks and measures did not reflect task execution time (e.g., writing down the name, pre-task pausing time, post-task pausing time). Alphabet task. Students had 60 s to write the alphabet as We ran cross-classified multilevel models (CCMLM) in MPlus many times and as they could and as quickly as possible. To obtain version 8 (Muthén and Muthén, 2017). CCMLM allowed a an estimate of handwriting fluency, we counted the number of thorough analysis of within-letter pausing data, as well as well-written letters within the first 15 s (after Berninger et al., between-letter and between-student differences (Van den 1992). To explore pause duration and pause number, we identified Noortgate et al., 2003; Fielding and Goldstein, 2006). This type of all pauses starting at 100 ms. Each pause log was assigned to the corresponding letter to be able to compute the number of pauses per letter, and we also recorded each pause duration (in 1 Adaptation of the strokes per letter required for each letter-case of milliseconds). Reliability (ICC) between the first author and an Soler-Vilageliu and Kandel (2012) can be found in Figure A1 of the RA on 20% of the handwriting tasks was.884. Supplementary material. Frontiers in Psychology 05 frontiersin.org Pascual et al. 10.3389/fpsyg.2022.1052264 modelling has been already found useful in previous studies that that factor loadings were fixed to one. This level of analysis allowed conducted letter-feature analyses across both letters and students us to determine which letter characteristics affected pause (e.g., Kim et al., 2010; Piasta and Wagner, 2010), due to its ability duration or number during letter formation. The strokes and the to consider “participants as raters of similar items” (Kim et al., script-type latent factors were regressed on the within-letter 2010, p. 315), which in this case are letters, nesting pause duration pause factor. and number not only within letters but also within participants. At level 2 we distinguished two sub-levels to account for In other words, CCMLM enables within-item, between-item, and differences between letters (level 2a) and between students (level between-participant level interaction, controlling for each 2b). Similarly to level 1 above, in the between-letters level, coefficient’s standard error (Shi et al., 2010). we estimated a latent factor of the pause duration/number per letter, another latent factor of the number of strokes per letter, and latent factors for the two dummy variables reflecting contrasts 3. Results between script types. All latent factors reflected the actual observed value. By creating pseudo-latent factors, we could run Descriptive statistics of pause duration and pause number, as analyses across levels. In the between-subjects sublevel (2b), well as the handwriting fluency score, by group and grade, are we estimated a latent factor of pause duration/number, which was reported in Table 3. In grade 3, pauses lasted for 414 ms on average fixed to 1. This factor was regressed on Grade, the handwriting for the typically developing group (SD = 360 ms). For the WD fluency score, and on Group (that is, whether students had writing group, average pause duration was 536 ms (SD = 302 ms). Pausing difficulties or not). Final model results can be found in Table 5. rate was around 1.8 pauses per letter for both groups. In grade 5, Before conducting the final analyses we identified outliers at handwriting pauses lasted around 360 ms across groups, and 1.42 each level of analysis and for each dependent variable. For the pauses were made, on average, for each letter, also in both the TD pause duration analyses, at level 1 we excluded pauses that were 3 and the WD groups. SDs above the mean (i.e., ≥ 2.030 ms), resulting in a loss of 92 data Our CCMLM models used Bayesian (MCMC) estimation points (0.02% of data). Of these data, 42% was from WD children, (1,000 iterations) to assess both pause duration and pause number and 58% was from TD children. At level 2a we excluded 8 considering two levels. The variables included in each level are instances of children writing the letter “ñ,” which does not belong depicted in a multilevel diagram in Table 4 (following Monsalves to the Catalan alphabet (but to the Spanish one); therefore, at this et al., 2020). At level 1, which tested variance within letters, level the cluster was reduced from 27 to 26 items. At level 2b one we estimated a within-letter pause latent factor, a within-letter child was excluded due to her performance in the handwriting strokes latent factor, and two within-letter script-type latent fluency task, which was well outside normalcy parameters (i.e., > factors which included a dummy coding of the possible script 22 letters within the first 15 s of the task or 5.7 SDs). Therefore, 92 types (the latent factor Script1 reflected the contrast between data points were removed, and the size of the 2b level cluster went cursive and both low and uppercase print; the Script2 latent factor from 80 subjects to 79. Overall the total loss of data was 3.31% of reflected the contrast between lowercase print and both cursive observations (from 5,793 pauses logged to 5,601 pauses). and uppercase print). All latent factors were pseudo-factors, such In the pause number analysis, at level 1, 120 data points were excluded because the number of pauses within-letter was above 3 TABLE 3 Descriptive statistics of HWF score, pause number and SDs (i.e., letter executions which required four or more pauses per duration by group and grade. letter were excluded). This corresponded to 3.40% of all letter executions (3,528). Because we had included a letter-ID index TD WD variable, identifying the 26 letters of the Catalan alphabet, no data Grade 3 Grade 5 Grade 3 Grade 5 were excluded at level 2a. Last, at level 2b we excluded the same M (SD) M (SD) M (SD) M (SD) outstanding student due to her handwriting fluency score (cluster HWF 11.99 (3.65) 17.61 (7.17) 8.6 (4.49) 11.9 (3.07) size = 79). Unless otherwise specified, we report unstandardized score coefficients. Mean 414.15 ms 358.52 ms 536.11 ms 360.68 ms pause (359.97 ms) (282.37 ms) (301.98 ms) (301.98 ms) duration 3.1. Pause duration per letter (ms) Results showed that, at the within-letter level, pause duration Mean 1.84 (0.90) 1.43 (0.67) 1.7 (0.83) 1.42 (0.68) was not significantly explained by the number of strokes, pause b = −0.04 (PSD = 0.16), p = 0.496, or script (i.e., lowercase print, number uppercase print, or cursive), b = 0.19 (PSD = 0.17), p = 0.213, for per letter the contrast between cursive and both low and upper-case print, TD = typically developing group; WD = writing difficulties group; HWF = Handwriting and b = 0.09 (PSD = 0.11), p = 0.048, for the contrast between Fluency Score (no. of letters written). lowercase print and both cursive and uppercase print. At the Frontiers in Psychology 06 frontiersin.org Pascual et al. 10.3389/fpsyg.2022.1052264 TABLE 4 Multilevel diagram in table format. 3.2. Pause number Level Level Variables in Variables in cluster pause pause At the within-letter level, the average number of pauses was number duration not significantly explained by the number of letter strokes, 1 Within same- Pause Number Pause duration b = 0.23 (PSD = 0.51), p = 0.275. However, letter type did have a letter level within letter significant effect on the average number of pauses within letters. Strokes per letter Strokes per letter Children who wrote letters using cursive made overall fewer Case Contrast (1) Case Contrast (1) pauses than those who used print, b = −0.84 (PSD = 0.57), Case Contrast (2) Case Contrast (2) p < 0.001. Similarly, children who wrote using lowercase print made overall fewer pauses than children who used either cursive 2-a Between Pause number per Pause duration per or uppercase print, b = −0.50 (PSD = 0.20), p = 0.013. At the different-letter letter letter between-letter level, neither the number of strokes, b = 0.04 level Strokes per letter Strokes per letter (PSD = 0.42), p = 0.453, or the script type, b = −0.15 (PSD = 0.67), Case Contrast (1) Case Contrast (1) p = 0.414 (cursive v. print), b = 0.22 (PSD = 0.45), p = 0.314 Case Contrast (2) Case Contrast (2) (lowercase print v. cursive and uppercase print), significantly 2-b Between- Pause number per Pause duration per affected the number of pauses between letters. Finally, at the subject level letter per subject letter per subject between-student level, Grade had a significant impact on the Grade Grade average number of pauses, b = − 0.13 (PSD = 0.06), p = 0.017, such that younger children made more pauses per letter, on average. Group Group Students’ handwriting fluency score also influenced the average Score in Hw Score in Hw pause number significantly, b = −0.03 (PSD = 0.01), p < 0.001, Fluency Fluency such that more fluent handwriting was associated with overall fewer pauses. However, Group did not have a significant effect on the average number of pauses per letter, b = −0.07 (PSD = 0.07), between-letter level, the number of strokes did not correlate p = 0.115, indicating that children with writing difficulties made significantly with within-letter pause duration, b = −0.01 a similar number of pauses per letter, on average, as typically- (PSD = 0.07), p = 0.447. Script type did not have a significant effect developing students. As with the pause duration results, we reran either, on the average between-letter duration, b = 0.02 the analysis excluding the handwriting fluency score, to (PSD = 0.11), p = 0.447, for the cursive v. print contrast; and determine whether this variable was suppressing an effect of b = 0.004 (PSD = 0.10), p = 0.489, for the lowercase print v. cursive Group on the number of pauses. Our second analysis indicated + upper-case print contrast. that this was not the case, as Group was not a significant predictor At the between-student level, Grade did not have a significant of number of pauses either, b = 0.07 (PSD = 0.05), p > 0.05, while impact on the average pause duration, b = −0.03 (PSD = 0.02), the effect of Grade remained significant also in this second p = 0.089. Moreover, children with writing difficulties tended to analysis, b = −0.27 (PSD = 0.03), p < 0.05. The model explained a make pauses that were similar in length to typically-developing considerable proportion of the variance at the between-student students, b = 0.01 (PSD = 0.03), p = 0.414. In contrast, students’ level, R2 = 0.728 (PSD = 0.13), p < 0.001. handwriting fluency score did influence pause duration significantly, b = −0.12 (PSD = 0.003), p < 0.001, such that more fluent handwriting was associated with overall shorter pauses. 4. Discussion Notably, the correlations between the handwriting fluency score with Grade and with Group were r = 0.55 and r = −0.45, This study aimed to examine to identify and characterize the respectively. This, in addition to the fact that the handwriting nature of pauses that are due to handwriting processes during a fluency score is on a larger scale, in comparison with both Grade handwriting task. Moreover, we aimed to ascertain the potential and Writing-difficulty status, which are binary variables, could effect of a series of letter properties (e.g., number of strokes be suppressing the “real” effect of our variable of interest. required, letter type) on the duration and number of handwriting Therefore, we reran the analysis, excluding the handwriting pauses. Finally, we intended to understand how schooling affects fluency variable. This analysis showed that both Grade and Group these pauses and whether pause number and/or pause duration did have a significant impact on average pause duration, b = −0.08 could be a marker of writing difficulties. For these purposes, (PSD = 0.02), p < 0.05 (Grade); b = 0.06 (PSD = 0.02), p < 0.05 we collected handwritten productions and analysed them (Group): younger children and children with writing difficulties thoroughly, identifying within and between-letter factors. Critical made longer pauses, on average. The model explained a to the study design was that pauses should be safely attributed to considerable proportion of the variance at the between-student handwriting execution and not to other writing processes, such as level, R2 = 0.795 (PSD = 0.12), p < 0.001. spelling, planning, or revising. Frontiers in Psychology 07 frontiersin.org Pascual et al. 10.3389/fpsyg.2022.1052264 TABLE 5 Pause duration and pause number cross classified multilevel model per levels and the proportion of variance explained by the regression per level (R2). Estimate Post. S.D p 95% C.I R2 [95% CI] L 2,5% U 2,5% Within-letters level variables Pause Duration within letters 0.24 [0.10–0.41] Strokes −0.038 0.164 0.496 −0.240 0.252 Script1 0.191 0.171 0.213 −0.220 0.331 Script2 0.092 0.108 0.048 −0.010 0.320 Pause Number within letters 0.44 [0.11–0.75] Strokes 0.227 0.514 0.275 −0.414 1.467 Script1 −0.837 0.566 0.000* −1.828 −0.127 Script2 −0.500 0.197 0.013* −0.771 −0.097 Between-letters level variables Pause duration between letters 0.44 [0.04–0.97] Strokes −0.008 0.074 0.447 −0.154 0.154 Script1 0.015 0.113 0.447 −0.266 0.235 Script2 0.004 0.100 0.489 −0.222 0.200 Pause number between letters 0.54 [0.08–0.91] Strokes 0.036 0.416 0.453 −0.832 0.881 Script1 −0.154 0.670 0.414 −1.256 1.276 Script2 0.219 0.451 0.314 −0.634 1.161 Between subjects level variables Pause duration between subjects 0.74 [0.48–1.00] Grade −0.026 0.021 0.089 −0.069 0.016 Group 0.006 0.027 0.414 −0.040 0.065 Score in HWF −0.012 0.003 0.000* −0.017 −0.006 Pause number between subjects 0.78 [0.54–0.97] Grade −0.133 0.056 0.017* −0.238 −0.009 Group −0.071 0.067 0.115 −0.212 0.056 Score in HWF −0.033 0.005 0.000* −0.045 −0.025 CI = confidence interval; L = lower; U = upper; Script1 = contrast between cursive vs. lower and upper case; Script2 = contrast between lower case vs. cursive and upper case; HWF = handwriting fluency (Alphabet task). *p < 0.05. 4.1. The nature of handwriting pauses in and Alves, 2017), we have found the need to also account and mid-primary better define transcription pauses, which will be crucial for understanding early writers text’s composition. We provided sound evidence that the overall average duration In this sense, beyond a within-automatization task pause of a handwriting pause, at least in the mid-primary grades in a duration, transcription pauses may undergo significant changes semi-consistent orthography, is around 400 ms. Our depending on the task at hand. The cognitive effort that has to methodological design allowed us to safely attribute pauses to be devoted to composing texts changes between genres and handwriting execution of letters, given that it was the only process schooling level (Olive et al., 2009; Beauvais et al., 2011), and required by the task. This is a major change over most previous handwritten automatisation plays a determinant role in the research on the topic, which has, for the most part, made amount of cognitive resources available to devote to higher-level assumptions about the high-level processes underlying pauses writing processes such as organizing ideas, translating ideas into during writing and had overlooked establishing a data-driven language, or revising (McCutchen, 2000). Studies that explore threshold for transcription pauses. If transcription processes are within-text pause should consider the idiosyncrasies of the task at considered as moderators or predictors of writing quality (Limpo hand, given that speed, pause duration and increase or decrease of Frontiers in Psychology 08 frontiersin.org Pascual et al. 10.3389/fpsyg.2022.1052264 pausing patterns are linked to syntactic constructs (clauses, possibility that orthographic depth or consistency levels might sentences, paragraphs; van Hell et al., 2008; Ailhaud et al., 2016). impact handwriting execution (Kandel and Soler, 2010). Minor Our finding about the average duration of handwriting pauses nuances aside, our study has contributed to narrowing down the conflicts with previous research in English with 9-year-old range in the number of pauses that mid-primary children require students, which reported an average pause duration during the for handwriting in a semi-consistent orthography (Catalan). alphabet writing task of 722.25 ms (SD = 261.33 ms; Sumner et al., 2013, p. 998). However, it has been suggested that orthographic depth may have an impact on handwriting execution (Kandel and 4.2. Letter features that affect Soler, 2010). All in all, however, our findings and those of Sumner handwriting execution et al.’s (2013) should be reassuring to researchers who considered that transcription pauses were on the shorter end of the The present study was innovative in considering the effect of continuum, in comparison with other writing pauses, such as key letter features, such as the number of strokes required per planning (e.g., Alves et al., 2008; Olive et al., 2009). Conversely, letter (based on Soler and Kandel, 2009, who adapted Meulenbroek some studies that investigated handwriting execution pauses and Van Galen, 1990), as well as the type of script used by children specifically may have underestimated their average duration. For during the task, despite the fact that they were all instructed to use example, Prunty et al. (2014) used literature to classify “within- lowercase print letters. Contrary to our expectations, pause letter” pauses as those occurring under 250 ms, while “between- duration was unaffected by either letter feature, while the average letter” pauses were estimated to occur within a 250–2,000 ms number of pauses by letter differed as a function of the type of range. The present paper warns against these types of assumptions, script used by children: Cursive letters required fewer pauses than often based on measurements that cannot be unmistakably lowercase print letters, and these, in turn, fewer than uppercase attributed to a specific writing process. Future studies should print letters. Cursive script is composed by ‘joined-up letters, attempt to isolate spelling-related pauses, in order to ascertain the continuous movement and few pen lifts’ (Bara et al., 2016, p.89). pause-duration range for transcription processes. An interesting educational implication may be derived, then, from As for the average number of pauses per letter, our study these findings, such that handwriting fluency could be facilitated, showed that children made about 1.5 pauses per letter, when they to some extent (i.e., requiring fewer pauses), by using cursive performed the alphabet task. Contrary to pause duration, there are script. Nevertheless, more research is needed to determine what no widely used thresholds of what a reasonable or unreasonable other facets of handwriting fluency –a crucial factor in the number of pauses should be, or whether certain processes are development of writing and tightly associated to writing quality associated with a higher or smaller number of pauses. However, and productivity throughout most of obligatory education (e.g., our findings are relatively well aligned with those reported Graham et al., 1997; Salas and Silvente, 2020) – are impacted by recently by Alamargot et al. (2021), who investigated handwriting these and other letter features. execution pauses in dyslexic French-speaking children, and compared them to groups of age- and spelling-skill-matched controls. The authors obtained pauses using a name+surname 4.3. Schooling effects on handwriting writing task, and an alphabet-writing task, thus focusing solely on pauses handwriting execution. Pauses were divided into five categories: P1 = 20–199 ms; P2 = 200–399 ms; P3 = 400–599 ms; Another aim of the study was to determine if handwriting P4 = 600–799 ms; and P5 = 800–1,000 ms (Alamargot et al., 2021, pause duration and number would be influenced by children’s p. 168). If we consider the average number of pauses reported schooling level. We hypothesized that 5th grade children would across categories, typically-developing, 11-year-old children made show shorter pause durations and fewer pauses per letter, on about 1.6 pauses per letter in the alphabet task, while both control average, than the 3rd grade children, as the former would have groups made significantly more pauses of the shortest kind, but more automatized transcription processes than the latter (Alves did not differ in the rate at which they made other types of pauses. and Limpo, 2015). As expected, schooling level was significantly Importantly, the shortest pause type (under 200 ms) was, by far, involved in explaining individual differences in pause number and the most frequent across groups and tasks, suggesting that duration between students. This was not surprising, given the handwriting execution may be exerting demands at a very low abundant evidence that handwriting abilities are key factors in level, which appears to be impaired for some groups of children. learning to write and pose major constraints to the development One could argue that the children in our study should be making of writing (e.g., Kim et al., 2011, 2014; Wagner et al., 2011; more handwriting pauses, on average, given that they are slightly Dockrell et al., 2019). Handwriting requires a substantial amount younger than the age-matched TD children in Alamargot et al.’s of writing resources to young and struggling writers, as it has been (2021) study. However, note that they (1) started counting pauses reported in investigations that explored written products at 20 ms (while we did so at 100 ms); and (2) are users of French, (Berninger et al., 1992; Bourke et al., 2014; Kim et al., 2014; Kandel a considerably more inconsistent orthography (e.g., Caravolas and Perret, 2015; Kim and Schatschneider, 2017) and processes et al., 2020). In this sense, we have already mentioned the (Connelly et al., 2012; Alves et al., 2016, 2018; Beers et al., 2017, Frontiers in Psychology 09 frontiersin.org Pascual et al. 10.3389/fpsyg.2022.1052264 2018; Medimorec and Risko, 2017; Limpo and Alves, 2017). and with children matched to dyslexic peers on spelling skills Therefore, the reduction in pause duration and number at the (Sumner et al., 2013). Thus, it would appear that difficulties with letter level may indicate a developmental integration of handwriting processes could be at the root of struggling writers’ transcription skills. problems to compose text. Similarly, to the Grade effects reported Although the schooling effect on handwriting pauses was above, though, a simple measure of handwriting fluency was a clear, children’s score in the alphabet task was the main factor that more important predictor of average pause duration and it needed predicted the average duration of handwriting pauses between to be removed for writing status (TD v. WD) to become a subjects, while schooling level did not explain unique variance significant factor. Again, as with Grade, a non-binary variable above and beyond this measure. Only when handwriting fluency would facilitate the detection of a correlational pattern with the was removed from the model did schooling level become a outcome variable, rather than a binary one. However, even if significant factor. This was not the case for the average number of handwriting fluency is sufficiently efficacious to identify pauses, where schooling level contributed to explaining significant handwriting difficulties, from a theoretical and a clinical between-subject variance even after controlling for the powerful standpoint, it is paramount to understand the mechanisms of effect of handwriting fluency scores. We have mentioned these difficulties to arrive at effective remediation strategies. elsewhere that the handwriting fluency score provides a larger Future research should strive to expand the current findings to scale that facilitates establishing a pattern between this skill and build a more complete explanatory picture of handwriting pause number or duration, in contrast with the binary variable of difficulties in struggling writers. Grade. Besides this observation, which is of an operational nature, perhaps a more important conclusion would be that handwriting fluency appears to be a sensitive-enough indicator of handwriting 5. Limitations skill, rather than the more sophisticated (and much more difficult to obtain) measures of handwriting pause duration and number. Our results need to be interpreted with caution due to the limited sample size, and the fact that the research was embedded in a rather particular linguistic setting. Further studies should 4.4. Handwriting pauses as markers of account for more types of handwriting assessment and possible writing difficulties differences that arise from/between them. Therefore, the present results should be further explored with a larger sample size of It has long been established that writing is best understood as children in all grades, to be able to establish more accurate a cognitive process (Hayes and Flower, 1980; Alamargot and developmental and longitudinal markers to explore further the Chanquoy, 2001). Longitudinal studies have demonstrated that handwriting limitations of children at-risk. Moreover, future there are causal effects between different components of writing studies should consider. (e.g., Vilageliu et al., 2016). Intervention studies have repeatedly demonstrated that providing procedural scaffolding to write improves writing competence (e.g., Graham et al., 2012, 2018). 6. Concluding remarks More specifically, providing handwriting strategies, from scaffolded learning to remedial instruction (see Alves et al., 2018; Difficulties with handwriting can hinder the execution of Limpo and Graham, 2020 for detailed reviews and examples of other writing processes and in turn, impair overall text quality and best-practices in handwriting teaching), leads to improvements in proficiency (Berninger et al., 2008). Longer pauses within the text quality (e.g., Santangelo and Graham, 2016). Therefore, given letter could account for the fact that the writer may have not still that writing processes in general, and handwriting in particular, fully integrated and automatized the symbolic-abstract shape of are causally linked to writing development, we reasoned that letters and, therefore, they have to either rely on visual feedback features of handwriting execution, such as pauses, could of the strokes (Alamargot et al., 2021). Alternatively, writers might be markers of writing difficulties. For this purpose, we examined need to scan through their sensori-motor integration graphical whether either handwriting pause duration or number could representations of the handwritten letters to be able to plan and be process-specific indicators of writing difficulties. Our results reproduce the strokes sequentially (Longcamp et al., 2016). showed that children with writing difficulties, identified as having Further neuropsychological studies could help inform of any handwriting difficulties (Pascual and Salas, 2021), paused for differences, delays, or divergences in the neuroanatomical longer during handwriting execution. However, they made a integration and specificity of the handwritten automatization. similar number of pauses per letter as their TD peers. In other The present study has demonstrated that a 2,000 ms threshold words, during handwriting execution, struggling writers do not may be adequate for exploring high-level writing processes pause more often, but when they do so, it takes them longer than (Schilperoord, 2002; Strömqvist et al., 2006; Alves et al., 2008), but TD controls to resume handwriting. The finding that struggling it is not appropriate to understand transcription processes. A writers pause more than their TD peers during handwriting non-trivial proportion of schoolaged children, specially in the execution is in line with previous studies with dyslexic children initial stages of learning to write and those with writing difficulties, Frontiers in Psychology 10 frontiersin.org Pascual et al. 10.3389/fpsyg.2022.1052264 have not yet automatized low-level writing processes and, and wrote the first draft of the manuscript. NS performed the therefore, pauses under 2,000 ms should be considered to account statistical analyses. All authors contributed to the article and for the overall writing process. Overall, pauses amount to about approved the submitted version. half the time taken to compose a text (Strömqvist and Wengelin, 1999; Alamargot et al., 2007), and allow writers’ working memory to handle and access cognitive resources (McCutchen, 2000). If Funding pauses due to handwritten activity can be pinpointed around the 500 ms threshold, future studies should aim to explore those This research was supported by Spanish grants 2015ACUP pauses above 500 ms, to scrutinize thresholds for transcription 00175 and PID2019-108791GA-I00, awarded to NS. activity, from accessing lexical information, to resolving spelling ambiguities (Wengelin, 2006; Brizan et al., 2015; Medimorec and Risko, 2017). The specific role of different types of pauses should Acknowledgments be further explored both in text composition and process- specific tasks. The authors are indebted to the schools that participated in Letter features had a small to insignificant effect in children’s the projects. We are also thankful to Mar Formiga for her help as handwriting pauses. This finding in itself does not entirely resolve a RA, and to Gabriel Liberman and Amir Hefetz for their support an instruction issue on which script to teach. Nonetheless, it with the statistical analyses. indicates that choice of script does not substantially affect the cognitive load during handwriting. Teaching practices should be reassessed considering the real utility of carefully choosing a Conflict of interest script type for the formal instruction of writing. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could Data availability statement be construed as a potential conflict of interest. The datasets generated for this study are available on request to the corresponding author. Publisher’s note All claims expressed in this article are solely those of the Ethics statement authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the The studies involving human participants were reviewed and reviewers. Any product that may be evaluated in this article, or approved by Ethics Commitee of the Autonomous University of claim that may be made by its manufacturer, is not guaranteed or Barcelona. Written informed consent to participate in this study endorsed by the publisher. was provided by the participants’ legal guardian/next of kin. Supplementary material Author contributions The Supplementary material for this article can be found online MP, NS, and OS contributed to the conception, design of the at: https://www.frontiersin.org/articles/10.3389/fpsyg.2022.1052264/ study, and wrote sections of the manuscript. MP built the database full#supplementary-material References Ailhaud, E., Chenu, F., and Jisa, H. (2016). “A developmental perspective on the Alamargot, D., Plane, S., Lambert, E., and Chesnet, D. (2010). Using eye and pen units of written French” in Written and spoken language development across the movements to trace the development of writing expertise: case studies of a 7th, 9th lifespan literacy studies (perspectives from cognitive neurosciences, linguistics, and 12th grader, graduate student, and professional writer. Read. Writ. 23, 853–888. psychology and education). eds. J. Perera, M. Aparici, E. Rosado and N. Salas, vol. 11 doi: 10.1007/s11145-009-9191-9 (Cham: Springer) Alves, R. A. (2019). “The early steps in becoming a writer: enabling participation Alamargot, D., and Chanquoy, L. (2001). “General introduction” in Through the in a literate world” in International handbook of language acquisition. eds. J. Horst models of writing. Studies in writing, vol. 9 (Dordrecht: Springer), 1–29. and K. T. J. Von (United Kingdom: Routledge Taylor & Francis Group). Alamargot, D., Dansac, C., Chesnet, D., and Fayol, M. (2007). “Parallel processing Alves, R. A., Castro, S. L., De Sousa, L., and Strömqvist, S. (2007). Influence of before and after pauses: A combined analysis of graphomotor and eye movements typing skill on pause-execution cycles in written composition. In M. Torrance, during procedural text production” in Cognitive Factors in Writing. eds. M. Torrance WaesL. Van and D. Galbraith (Eds.), Writing and cognition: Research and D. Galbraith and L. v. Waes (Dordrecht, Boston, London: Elsevier Sciences Publishers). applications. United Kingdom: Brill. Alamargot, D., Morin, M. F., and Simard-Dupuis, E. (2021). Handwriting delay in Alves, R. A., Castro, S. L., and Olive, T. (2008). Execution and pauses in writing dyslexia: children at the end of primary school still make numerous short pauses narratives: Processing time, cognitive effort and typing skill. International Journal when producing letters. J. Learn. Disabil. 53, 163–175. doi: 10.1177/0022219420903705 of Psychology 43, 969–979. doi: 10.1080/00207590701398951 Frontiers in Psychology 11 frontiersin.org Pascual et al. 10.3389/fpsyg.2022.1052264 Alves, R. A., Leal, J. P., and Limpo, T. (2019). “Using hand spy to study writing in De Sousa, H. M. P., and Leal, J. P. (2013). Hand Spy: Melhoramentos a um Sistema real time: a comparison between low- and high-quality texts in grade 2” in Observing de Gestão de Experiências sobre Processos Cognitivos da Escrita. Porto: writing. Insights from keystroke logging and handwriting. eds. E. Lindgren and K. Porto University. Sullivan (Brill), 50–70. Dockrell, J. E., Connelly, V., and Arfé, B. (2019). Struggling writers in elementary Alves, R. A., and Limpo, T. (2015). Progress in written language bursts, pauses, school: capturing drivers of performance. Learn. Instr. 60, 75–84. doi: 10.1016/j. transcription, and written composition across schooling. Sci. Stud. Read. 19, learninstruc.2018.11.009 374–391. doi: 10.1080/10888438.2015.1059838 Drijbooms, E., Groen, M. A., Alamargot, D., and Verhoeven, L. (2020). Online Alves, R. A., Limpo, T., Fidalgo, R., Carvalhais, L., Pereira, L. Á., and Castro, S. L. management of text production from pictures: a comparison between fifth graders (2016). The impact of promoting transcription on early text production: effects on and undergraduate students. Psychol. Res. 84, 2311–2324. doi: 10.1007/ bursts and pauses, levels of written language, and writing performance. J. Educ. s00426-019-01199-x Psychol. 108, 665–679. doi: 10.1037/edu0000089 Fielding, A., and Goldstein, H. (2006). Cross-classified and multiple membership Alves, R. A., Limpo, T., Salas, N., and Joshi, R. M. (2018). “Best practices in structures in multilevel models: An introduction and review. Research Report No. handwriting and spelling” in Best practices in writing instruction. eds. S. 791. Department of Eduction and Skills. University of Birmingham Graham, C. A. Mac Arthur and M. Hebert. 3rd ed (New York, NY: The Guilford Ganzeboom, H. B., De Graaf, P. M., and Treiman, D. J. (1992). A standard Press), 211–239. international socio-economic index of occupational status. Soc. Sci. Res. 21, 1–56. Alstad, Z., Sanders, E., Abbott, R. D., Barnett, A. L., Henderson, S. E., Connelly, V., doi: 10.1016/0049-089X(92)90017-B et al. (2015). Modes of alphabet letter production during middle childhood and Graham, S., Berninger, V. W., Abbott, R. D., Abbott, S. P., and Whitaker, D. (1997). adolescence: Interrelationships with each other and other writing skills. Journal of Role of mechanics in composing of elementary school students: a new Writing Research 6:199. doi: 10.17239/jowr-2015.06.03.1 methodological approach. J. Educ. Psychol. 89, 170–182. doi: 10.1037/0022- Arfé, B., Corato, F., Pizzocaro, E., and Merella, A. (2020). The effects of script and 0663.89.1.170 orthographic complexity on the handwriting and spelling performance of children Graham, S., Harris, K. R., and Adkins, M. (2018). The impact of supplemental with dyslexia. Journal of Learning Disabilities 53, 96–108. doi: handwriting and spelling instruction with first grade students who do not acquire 10.1177/0022219419892845 transcription skills as rapidly as peers: a randomized control trial. Read. Writ. 31, Bara, F., Morin, M. F., Alamargot, D., and Bosse, M. L. (2016). Learning 1273–1294. doi: 10.1007/s11145-018-9822-0 different allographs through handwriting: the impact on letter knowledge and Graham, S., McKeown, D., Kiuhara, S., and Harris, K. R. (2012). A meta-analysis reading acquisition. Learn. Individ. Differ. 45, 88–94. doi: 10.1016/j.lindif.2015. of writing instruction for students in the elementary grades. Journal of Educational 11.020 Psychology 104:879. doi: 10.1037/a0029185 Barnett, A., Henderson, S., Scheib, B., and Schulz, J. (2007). The Detailed Graham, S., Weintraub, N., and Berninger, V. W. (1998). The relationship between Assessment of Speed of Handwriting (DASH). Manual. London: Pearson Clinical. handwriting style and speed and legibility. J. Educ. Res. 91, 290–297. doi: Beauvais, C., Olive, T., and Passerault, J.-M. (2011). Why are some texts good 10.1080/00220679809597556 and others not? Relationship between text quality and management of the writing Hayes, J. R., and Flower, L. S. (1980). “Identifying the organisation of writing processes. J. Educ. Psychol. 103, 415–428. doi: 10.1037/a0022545.10.1037/ processes” in Cognitive processes in writing. eds. L. Gregg and E. R. Sternberg a0022545 (Hillsdale, NJ: Erlbaum). 1st edn. 3–30. Beers, S. F., Berninger, V. W., Mickail, T., and Abbott, R. D. (2018). Online writing Idescat. (2015). Indicadors anuals. Usos lingüístics de la població. Llengua inicial, processes in translating cognition into language and transcribing written language d’identificació i habitual. Generalitat de Catalunya. Available at: https://www.idescat. by stylus and keyboard in upper elementary and middle school students with cat/indicadors/?id=anuals& n=10364 persisting dysgraphia or dyslexia. Learn. Disabil.: Multidis. J. 23, 70–86. doi: 10.18666/ldmj-2018-v23-i2-9008 James, K. H., and Gauthier, I. (2006). Letter processing automatically recruits a sensory–motor brain network. Neuropsychologia 44, 2937–2949. doi: 10.1016/j. Beers, S. F., Mickail, T., Abbott, R. D., and Berninger, V. W. (2017). Effects of neuropsychologia.2006.06.026 transcription ability and transcription mode on translation: evidence from written compositions, language bursts and pauses when students in grades 4 to 9, with and Kandel, S., Álvarez, C. J., and Vallée, N. (2008). Morphemes also serve as processing without persisting dyslexia or dysgraphia, compose by pen or by keyboard. J. Writing units in handwriting production. Neuropsychology and cognition of language Res. 9, 1–25. doi: 10.17239/jowr-2017.09.01.01 behavioral, neuropsychological and neuroimaging studies of spoken and written language. Kerala, India: Research Signpost, 87–100. Berninger, V. W., Nielsen, K. H., Abbott, R. D., Wijsman, E., and Raskind, W. (2008). Writing Problems in Developmental Dyslexia: Under-Recognized and Kandel, S., and Perret, C. (2015). How does the interaction between spelling and Under-Treated. Journal of School Psychology 46, 1–21. doi: 10.1021/nl061786n.Core- motor processes build up during writing acquisition? Cognition 136, 325–336. doi: Shell 10.1016/j.cognition.2014.11.014 Berninger, V. W., Fuller, F., and Whitaker, D. (1996). A process model of writing Kandel, S., and Soler, O. (2010). Differential syllable effects when learning to write development across the life span. Educ. Psychol. Rev. 8, 193–218. doi: 10.1007/ French and Catalan words. Curr. Psychol. Lett.s: Brain Behav. Cogn. 25:3. doi: BF01464073 10.4000/cpl.4965 Berninger, V. W., Yates, C. M., Cartwright, A. C., Rutberg, J., Remy, E., and Kim, Y.-S., Al Otaiba, S., Folsom, J. S., Greulich, L., and Puranik, C. S. (2014). Abbott, R. D. (1992). Lower-level developmental skills in beginning writing. Read. Evaluating the dimensionality of first-grade written composition. J. Speech Lang. Writ. 4, 257–280. doi: 10.1007/BF01027151 Hear. Res. 57, 199–211. doi: 10.1044/1092-4388(2013/12-0152 Bourdin, B., and Fayol, M. (1994). Is written language production more difficult Kim, Y.-S., Al Otaiba, S., Puranik, C. S., Folsom, J. S., Greulich, L., and than oral language production? A working memory approach. International Journal Wagner, R. K. (2011). Componential skills of beginning writing: an exploratory of Psychology 29, 591–620. doi: 10.1080/00207599408248175 study. Learn. Individ. Differ. 21, 517–525. doi: 10.1016/j.lindif.2011.06.004 Bourke, L., Davies, S. J., Sumner, E., and Green, C. (2014). Individual differences Kim, Y. S., Petscher, Y., Foorman, B. R., and Zhou, C. (2010). The contributions in the development of early writing skills: testing the unique contribution of of phonological awareness and letter-name knowledge to letter-sound acquisition—a visuospatial working memory. Read. Writ. 27, 315–335. doi: 10.1007/s11145-013- cross-classified multilevel model approach. J. Educ. Psychol. 102, 313–326. doi: 9446-3 10.1037/a0018449 Brizan, D. G., Goodkind, A., Koch, P., Balagani, K., Phoha, V. V., and Rosenberg, A. Kim, Y. S. G., and Schatschneider, C. (2017). Expanding the developmental (2015). Utilizing linguistically enhanced keystroke dynamics to predict typist models of writing: a direct and indirect effects model of developmental writing cognition and demographics. Int. J. Hum. Comput. Stud. 82, 57–68. doi: 10.1016/j. (DIEW). J. Educ. Psychol. 109, 35–50. doi: 10.1037/edu0000129 ijhcs.2015.04.005 Lam, S. S., Au, R. K., Leung, H. W., and Li-Tsang, C. W. (2011). Chinese Caravolas, M., Downing, C., Hadden, C. L., and Wynne, C. (2020). Handwriting handwriting performance of primary school children with dyslexia. Res. Dev. Disabil. 32, 1745–1756. doi: 10.1016/j.ridd.2011.03.001 legibility and its relationship to spelling ability and age: Evidence from monolingual and bilingual children. Frontiers in Psychology 11:1097. doi: 10.3389/ Limpo, T., and Alves, R. A. (2017). Written language bursts mediate the fpsyg.2020.01097 relationship between transcription skills and writing performance. Written Communication 34, 306–332. doi: 10.1177/0741088317714234 Chenu, F., Pellegrino, F., Jisa, H., and Fayol, M. (2014). Interword and intraword pause threshold in the writing of texts by children and adolescents: a methodological Limpo, T., and Graham, S. (2020). The role of handwriting instruction in writer’s approach. Front. Psychol. 5:182. doi: 10.3389/fpsyg.2014.00182 education. Br. J. Educ. Stud. 68, 311–329. doi: 10.1080/00071005.2019.1692127 Connelly, V., Dockrell, J., Barnett, A., and Lane, G. (2012). “Children challenged Longcamp, M., Velay, J. L., Berninger, V. W., and Richards, T. (2016). by writing due to language and motor difficulties” in Past, present, and future Neuroanatomy of handwriting and related reading and writing skills in adults and contributions of cognitive writing research to cognitive psychology. ed. V. Berninger children with and without learning disabilities: French-American connections. (New York, NY: Psychology Press/Taylor Francis Group). 217–245. Pratiq. Ling, Lit. Didact. 171–172, 1–11. doi: 10.4000/pratiques.3175 Frontiers in Psychology 12 frontiersin.org Pascual et al. 10.3389/fpsyg.2022.1052264 Maarse, F. J., Van Galen, G. P., and Thomassen, A. J. (1989). Modelsforthe Rosenblum, S., and Livneh-Zirinski, M. (2008). Handwriting process and product generation of writing unitsin handwritingunder variation of size, slant, and characteristics of children diagnosed with developmental coordination disorder. orientation. Human Movement Science 8, 271–288. Hum. Mov. Sci. 27, 200–214. doi: 10.1016/j.humov.2008.02.011 Maggio, S., Lété, B., Chenu, F., Jisa, H., and Fayol, M. (2012). Tracking the mind Salas, N., and Silvente, S. (2020). The role of executive functions and transcription during writing: immediacy, delayed, and anticipatory effects on pauses and writing skills in writing: a cross-sectional study across 7 years of schooling. Read. Writ. 33, rate. Read. Writ. 25, 2131–2151. doi: 10.1007/s11145-011-9348-1 877–905. doi: 10.1007/s11145-019-09979-y McCutchen, D. (2000). Knowledge, processing, and working memory: implications Santangelo, T., and Graham, S. (2016). A comprehensive meta-analysis of handwriting for a theory of writing. Educ. Psychol. 35, 13–23. doi: 10.1207/S15326985EP3501_3 instruction. Educ. Psychol. Rev. 28, 225–265. doi: 10.1007/s10648-015-9335-1 McMaster, K., and Espin, C. (2007). Technical features of curriculum-based measurement in writing: A literature review. The Journal of Special Education 41, Schilperoord, J. (2002). “On the Cognitive Status of Pauses in Discourse 68–84. doi: 10.1177/00224669070410020301 Production” in Contemporary tools and techniques for studying writing. eds. T. Olive and C. M. Levy (Dordrecht: Springer Science & Business Media), 61–87. doi: Medimorec, S., and Risko, E. F. (2017). Pauses in written composition: on the 10.1007/978-94-010-0468-8_4 importance of where writers pause. Read. Writ. 30, 1267–1285. doi: 10.1007/ s11145-017-9723-7 Schomaker, L. R. B. (1991). Simulation and recognition of handwriting movements: a vertical approach to modeling human motor behavior. Nijmegen: NICI, Nijmeegs Meulenbroek, R. G., and Van Galen, G. P. (1990). Perceptual-motor complexity of printed and cursive letters. J. Exp. Educ. 58, 95–110. doi: 10.1080/00220973. Instituut voor Cognitie-onderzoek en Informatietechnologie. 1–223. Available at: 1990.10806527 https://hdl.handle.net/2066/113914 Monsalves, M. J., Bangdiwala, A. S., Thabane, A., and Bangdiwala, S. I. (2020). Schwellnus, H., Cameron, D., and Carnahan, H. (2012). Which to choose: LEVEL (Logical Explanations & Visualizations of estimates in linear mixed models): manuscript or cursive handwriting? A review of the literature. J. Occup. Ther. Sch. recommendations for reporting multilevel data and analyses. BMC Med. Res. Early Interv. 5, 248–258. doi: 10.1080/19411243.2012.744651 Methodol. 20:3. doi: 10.1186/s12874-019-0876-8 Shi, Y., Leite, W., and Algina, J. (2010). The impact of omitting the interaction Monteiro, C. F., and Leal, J. P. (2013). Managing experiments on cognitive between crossed factors in cross-classified random effects modelling. Br. J. Math. processes in writing with hand spy. Comput. Sci. Inf. Syst. 10, 1747–1773. doi: Stat. Psychol. 63, 1–15. doi: 10.1348/000711008X398968 10.2298/CSIS121130061M Soler, O., and Kandel, S. (2009). Factores lingüísticos en la programación del trazo Morin, M. F., Lavoie, N., and Montésinos-Gelet, I. (2012). The effects of en la escritura infantil: importancia de la estructura silábica. Infancia y Aprendizaje manuscript, cursive or manuscript/cursive styles on writing development in grade 32, 189–198. doi: 10.1174/021037009788001789 2. Lang. Lit. 14, 110–124. doi: 10.20360/G21S3V Soler-Vilageliu, O., and Kandel, S. (2012). A longitudinal study of handwriting Muthén, B., and Muthén, L. (2017). Mplus in LindenW.J. van der (Ed.). Handbook skills in pre-schoolers: the acquisition of syllable oriented programming strategies. of item response theory: Volume Three: Applications (1st ed.). (pp. 507–518). Boca Raton, FL: Chapman and Hall/CRC. doi:10.1201/9781315117430 Read. Writ. 25, 151–162. doi: 10.1007/s11145-010-9251-1 Olive, T., Alves, R. A., and Castro, S. L. (2009). Cognitive processes in writing Strömqvist, S., Holmqvist, K., Johansson, V., Karlsson, H., and Wengelin, Å. during pause and execution periods. Eur. J. Cogn. Psychol. 21, 758–785. doi: (2006). “What keystroke-logging can reveal about writing” in Computer key-stroke 10.1080/09541440802079850 logging and writing: Methods and applications (studies in writing). eds. K. Sullivan and E. Lindgren (United Kingdom: Elsevier), 45–72. Pagliarini, E., Guasti, M. T., Toneatto, C., Granocchio, E., Riva, F., Sarti, D., et al. (2015). Dyslexic children fail to comply with the rhythmic constraints of Strömqvist, S., and Wengelin, Å. (1999). “The temporal patterning of actions in handwriting. Hum. Mov. Sci. 42, 161–182. doi: 10.1016/j.humov.2015. on-line writing” in International literacy project working papers in relevant features 04.012 of spoken and written language: Developing literacy across genres, modalities, and Palmis, S., Danna, J., Velay, J. L., and Longcamp, M. (2017). Motor control of languages. Vol. 1. ed. R. A. Aisenman (Tel Aviv: Tel Aviv University Press). 248–256. handwriting in the developing brain: a review. Cogn. Neuropsychol. 34, 187–204. doi: Sumner, E., Connelly, V., and Barnett, A. L. (2013). Children with dyslexia are 10.1080/02643294.2017.1367654 slow writers because they pause more often and not because they are slow at Pascual, M (2020). Children at-risk of writing difficulties [Doctoral dissertation]. handwriting execution. Read. Writ. 26, 991–1008. doi: 10.1007/s11145-012-9403-6 Autonomous University of Barcelona. Sumner, E., Connelly, V., and Barnett, A. L. (2014). The influence of spelling ability Pascual, M., and Salas, N. (2021). The cognitive profile and text-based traits of on handwriting production: children with and without dyslexia. J. Exp. Psychol. struggling writers (El perfil cognitivo y los rasgos textuales de los escritores con Learn. Mem. Cogn. 40, 1441–1447. doi: 10.1037/a0035785 dificultades). J. Study Educ. Develop. 44, 219–253. doi: 10.1080/02103702.2020. 1848090 Van den Noortgate, W., De Boeck, P., and Meulders, M. (2003). Cross- classification multilevel logistic models in psychometrics. J. Educ. Behav. Stat. 28, Piasta, S. B., and Wagner, R. K. (2010). Learning letter names and sounds: effects 369–386. doi: 10.3102/10769986028004369 of instruction, letter type, and phonological processing skill. J. Exp. Child Psychol. 105, 324–344. doi: 10.1016/j.jecp.2009.12.008 Van Galen, G. P. (1991). Handwriting: Issues for a psychomotor theory. Human Plamondon, R., Yu, L. D., Stelmach, G. E., and Clément, B. (1991). On the movement science 10, 165–191. doi: 10.1016/0167-9457(91)90003-G automatic extraction of biomechanical information from handwriting signals. IEEE van Hell, J., Verhoeven, L., and van Beijsterveldt, L. (2008). Pause time patterns Transactions on Systems, Man, and Cybernetics 21, 90–101. doi: 10.1109/21.101140 in writing narrative and expository texts by children and adults. Discourse Process. Prunty, M., and Barnett, A. L. (2017). Understanding handwriting difficulties: a 45, 406–427. doi: 10.1080/01638530802070080 comparison of children with and without motor impairment. Cogn. Neuropsychol. Vilageliu, O. S., Lasheras, C. S., Ramis, Y., and Castellà, J. (2016). “Development of 34, 205–218. doi: 10.1080/02643294.2017.1376630 Literacy and Notational Knowledge. Prediction of Literacy Development Difficulties Prunty, M. M., Barnett, A. L., Wilmut, K., and Plumb, M. S. (2014). An examination Through Graphomotor Measures in Grade 1” in Written and Spoken Language of writing pauses in the handwriting of children with developmental coordination Development across the Lifespan. Literacy Studies. Vol. 11. eds. J. Perera, M. Aparici, E. disorder. Res. Dev. Disabil. 35, 2894–2905. doi: 10.1016/j.ridd.2014.07.033 Rosado and N. Salas (Cham: Springer). doi: 10.1007/978-3-319-21136-7_6 Prunty, M., Barnett, A. L., Wilmut, K., and Plumb, M. (2016a). Visual perceptual Wengelin, Å. (2006). Examining pauses in writing: theory, methods and empirical and handwriting skills in children with developmental coordination disorder. Hum. data. Comp. Key-Stroke Log. Writing: Method. Appl. 18, 107–130. Mov. Sci. 49, 54–65. doi: 10.1016/j.humov.2016.06.003 Wengelin, A. (2007). “The word-level focus in text production by adults with Prunty, M. M., Barnett, A. L., Wilmut, K., and Plumb, M. S. (2016b). The impact of handwriting difficulties on compositional quality in children with developmental reading and writing difficulties” in Writing and cognition: Research and applications. coordination disorder. Br. J. Occup. Ther. 79, 591–597. doi: 10.1177/0308022616650903 Vol. 20. eds. M. W. Torrance, L. van Waes and D. Galbraith (Oxford, United Kingdom: Elsevier). 67–82. Prunty, M. M., Pratt, A., Raman, E., Simmons, L., and Steele-Bobat, F. (2020). Grip strength and pen pressure are not key contributors to handwriting difficulties in Wagner, R. K., Puranik, C. S., Foorman, B., Foster, E., Wilson, L. G., Tschinkel, E., children with developmental coordination disorder. Br. J. Occup. Ther. 83, 387–396. et al. (2011). Modeling the development of written language. Reading and writing doi: 10.1177/0308022619885046 24, 203–220. doi: 10.1007/s11145-010-9266-7 Frontiers in Psychology 13 frontiersin.org