cursive handwriting research uk

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Teaching of cursive writing in the first year of primary school: Effect on reading and writing skills

Cristina semeraro.

1 Department of Education, Psychology, Communication, University of Bari “Aldo Moro”, Bari, Italy

Gabrielle Coppola

Rosalinda cassibba, daniela lucangeli.

2 Department of Developmental Psychology and Socialization, University of Padova, Padova, Italy

Associated Data

All files are available from Figshare: https://figshare.com/s/209a49a536acef7cf0bb .

There is increasing evidence that mastering handwriting skills play an important role on academic achievement. This is a slow process that begins in kindergarten: at this age, writing is very similar to drawing (i.e. scribbles); from there, it takes several years before children are able to write competently. Many studies support the idea that motor training plays a crucial role to increase mental representations of the letters, but relatively little is known about the specific relation between handwriting skills and teaching practices. This study investigated the efficacy of cursive writing teaching. The sample comprised 141 students attending eight classes of the first grade of primary school, all with typical development, not exhibiting any cognitive or sensory disabilities, nor displaying motor disorders that could significantly hinder the execution of the writing task. We tested whether the development of academic writing skills could be effectively supported by training strategies focusing on cursive writing. All rules and characteristics of the letters were explained by demonstrating the correct writing movements, based on the idea that movement learning becomes more valuable when children begin to connect the letters in order to write individual words. Growth models on pre-, post- and follow-up measures showed that performance on prerequisites and writing and reading skills were better overall among the children in the intervention group as compared to control group.

Introduction

The research in the area of handwriting ability highlights an increase in graphical and visual-spatial difficulties in handwriting [ 1 ]. “Dysfluent writing” and “shape abnormality” are key characteristics of handwriting disorders described in the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders of the American Psychiatric Association (DSM-5). The term “dysfluent writing” refers to less fluent (i.e., slower) handwriting, while the term “shape abnormality” refers to distortions of pressure and irregularities in the forms of letters. According to the official international diagnostic systems [ 2 , 3 , 4 ], visual-motor and visual-spatial difficulties in writing are manifestations of a motor development disorder (dysgraphy). Poor graph-motor skills may increase the risk of difficulties in the visual-motor and spatial components of writing; therefore, interventions aimed at supporting and enhancing graphic activity, a function not adequately recognized thus far [ 5 ], could represent a valid action to prevent graphical and spatial difficulties in writing, especially in the context of formal education.

At the time of entry into primary school, children use much of their cognitive energy to control the production of letters and the graphical aspects of writing. A significant portion of their time and cognitive energy is, in fact, invested in controlling down processes (for example, correct writing of letters), while few attentive resources remain available for more complex tasks, such as generating ideas, lexical access, management of cognitive activities, and orthographic review of the text [ 6 ].

The well-known “cognitive constraint” related to writing [ 7 , 8 , 9 ] suggests the importance of automating the production of letters and words during writing, so that children can direct their attentive resources to the more complex aspects of text production, such as the decoding of reading and the orthographic accuracy of writing [ 10 , 11 ]. Available findings support the idea that, in the second [ 11 ] and third grade of primary school [ 12 ], a considerable amount of variance in the quality of a written text can be attributed to the automation of the production of letters. Since the movements necessary for the production of letters are under voluntary control, if not automated they can represent a high cognitive cost for children in terms of attention, which in turn prevents them from performing higher order academic tasks such as composing or paying attention to spelling and grammar [ 13 ].

With this in mind, research has examined the efficacy of early interventions targeting handwriting or of spelling instruction for struggling writers in first grade and findings show increased output, improved sentence writing skills, and better writing quality for children benefitting of such support [ 14 , 15 , 11 ]. Similar gains in writing output and sentence writing skills were obtained when struggling writers in second grade were provided with extra spelling instruction [ 16 , 17 ]. The findings from the two studies reviewed above, altogether, indicate that handwriting intervention early in primary grades may be a critical factor in preventing writing difficulties, at least for children who do not master handwriting easily [ 18 , 19 , 20 ]. Graham and Harris [ 21 ] reviewed the evidence on the role of handwriting in children's development as writers. Consistent with the view that handwriting instruction is an essential ingredient in writing development, they found that handwriting skills, particularly handwriting fluency (i.e., the amount of text that can be written down correctly per minute), improve with age and schooling [ 22 , 23 ], and that individual differences in handwriting skills (most notably handwriting fluency) predict how much and how well children will write [ 24 , 25 ]. Thus, these findings underscore the importance of motor programs in supporting the development of writing skills in primary school children [ 26 , 27 ]. However, it is still unclear what should the training target in order to effectively promote writing development [ 28 ].

To promote better writing skills the choice of writing style seems to be fundamental [ 29 ]. Cursive style, besides being predictive of better writing skills, seems easier to learn for young children in primary school [ 29 – 31 ]. Let us consider the graphical features differentiating printed writing from cursive [ 32 ], as cursive and print are the basic types of handwriting that children learn in primary school [ 33 , 34 ]. The movements used for these types of handwriting can be generally classified as either discontinuous patterns (i.e., temporally consistent start-and-stop movements, as in printed handwriting) and continuous patterns (i.e., an emergent property of trajectory-throughout movements as in cursive handwriting). Consistency of movement in time and space has been claimed to be an important feature of “good” handwriting [ 35 ], and this is a distinctive characteristic of cursive writing.

It has been reported that younger-aged children have higher irregularity and inconsistency of movement and time when performing discontinuous loops than with continuous ones [ 36 ]; moreover, it seems that young children have more difficulty performing discontinuous handwriting patterns compared with continuous patterns [ 37 ].

We believe such differences require further attention. In printed characters, graphic movement is not continuous: the gesture stops, there are repeated stops and starts of the pencil and the motor process is broken. Instead, on the graph-motor plane, cursive is the writing style closest to the child’s natural movements. For example, if we think of scribbles, the first graphic charts of the child are curved and rotating and, by the age of 3, they tend to close the open shapes. Therefore, there is a spontaneous curvilinear and/or circular graphical tendency in writing processes; moreover, the first letter reproduced by children is usually the letter "O", which does not require a template. Lastly, while the reproduction of printed letters involves copying a static model composed of segments that must be plotted in a precise graphic direction, the letters in cursive connect to each other dynamically [ 1 ]. Spencer et al. [ 38 ] proposed different control mechanisms for continuous versus discontinuous movements. Performing discontinuous movements requires an explicit representation of the temporal goal (i.e., when to start and stop), whereas performing continuous movements does not require an explicit event-related timing process. The authors claimed that the explicit processes used in controlling temporal consistency of discontinuous movements involve the cerebellum. In contrast, implicit timing processes for continuous movements may not closely relate to the cerebellum. Behaviorally, temporal deficits in patients with cerebellum damage were restricted to discontinuous circle drawing [ 39 ]. It is known that the cerebellum develops more slowly over a longer duration (i.e., until about 16 years of age) than most of the subcortical and cortical areas [ 40 ] and it is especially vulnerable to developmental disorders [ 41 ]. Thus, there is also a neuropsychological rationale for believing that temporal control for discontinuous handwriting may be more challenging than for continuous patterns in young children due to the relatively slower cerebellum development. If this is the case, these findings suggest that teaching cursive writing should occur much earlier than it is typically done in the current education systems of most countries (e.g., Canada, France, the Netherlands). In particular, a study examined temporal consistency in continuous and discontinuous circle and line drawing in children from five to twelve years of age [ 31 ] and, in line with Spencer et al. [ 38 ], the explicit timing demands were lower in continuous drawing than in the discontinuous task. This study showed that young children had high temporal and spatial variability in discontinuous circle drawing but not in continuous circling, continuous line drawing, and discontinuous line drawing. Overall, these findings [ 20 , 25 , 29 , 35 ] suggest that the temporal control of discontinuous movements (i.e., printed handwriting) may be more challenging than that of continuous movements (i.e., cursive handwriting) and that these discontinuous movements are under voluntary control. This is a cost for children in terms of attention and cognitive resources. Therefore, cursive handwriting might be easier for young children to learn.

Despite this state of the art of the current literature, in Italy there is widespread belief among teachers that printed writing is easier for young children to learn than cursive writing. The guidelines of the Italian National Ministry of Education (MIUR) regarding teaching in primary school give no clear guideline about the timing and methods for teaching writing skills and teachers are free to make personal decisions in this regard (MIUR, reference legislation 2012 - Prot. n°5559 - 2012 ). Nevertheless, pedagogical models [ 25 – 29 ] have influenced the selection of global methods (use of printed characters for reading and writing) for read-write abilities. The predilection for printed characters is certainly not justified in light of what we know about the development of the child’s graph-motor skills, but exclusively on a perceptive basis.

Despite this, it is common practice to start teaching the printed style of writing and to move to cursive writing by the middle or end of the first year of primary school, continuing to give more attention to printed writing, especially for children with learning difficulties.

On this topic, the results of a study conducted by Morin and colleagues [ 35 ] are of particular interest: these scholars explored the existing relationship between three different methods of teaching writing (print writing only, cursive writing only, and print writing in the first grade of primary school with cursive in the second grade) and writing skills development (writing speed, spelling and text production) in a sample of children attending the second grade of primary school in Canada. Findings show that children who have learned to write using only the cursive style show superior performance in both spelling and syntax when compared to the other two groups. The teaching of both styles (first print, and then cursive in the second grade of primary school) does not favor the acquisition of automatic movements, resulting, therefore, in disadvantages compared to the cursive-only method.

All previously published studies have evaluated writing skills exclusively in terms of cognitive measurement, perceptive and graph-motor. Over the years, a broad range of studies have been developed pertaining, in particular, to the learning of writing skills for pre-school and primary school students without, however, deepening the issue of the methods used for teaching writing. To our knowledge, no previously published study has focused on using cursive as the primary type of writing in order to improve writing, reading and spelling skills in children at the start of primary school.

In order to fill this gap, we first aimed to evaluate the efficacy of a teaching program focuses on the effects of intensive cursive learning on the prerequisites of writing and reading. Secondly, we aimed to test the efficacy of the teaching program for the acquisition of writing and reading skills. More specifically, we propose a specific graph-motor training program and intend to evaluate the effect of the training on reading and writing skills at a distance of 6 months, comparing the children who benefited from the training with children who followed the standard programs used in Italian schools.

Material and methods

Participants.

The sample comprised 141 students attending eight classes in the first grade (68 female—48.2%; 73 male—51.8%); age: M = 6.2, SD = .29) at four schools in the centre and suburbs of a city in the south of Italy. Selection criteria included Italian native speaker children, unidentified for cognitive or sensory disabilities and not displaying motor disorders which could significantly hinder the execution of the writing task. The eight classes were comparable in terms of: gender ratio ( χ 2 = 2.61, n.s.); age t (139) = 1.68, n.s.; measurement of socioeconomic status (parents’ years of education): mother’s educational level, t (127) = -.976, n.s. and father’s educational level, t (127) = -1.223, n.s.; teacher experience (all teachers were female with more than 15 years of teaching experience); and pre-test prerequisites of reading and writing skills ( Table 1 and Table 2 ). The total sample was divided randomly into two sub-samples. An intervention group (TG) was made up of children from four classes (N = 73, F = 40 (54.8%), age: M = 6.16, SD = .28) who took part in the cursive training. The remaining four classes (N = 68; F = 28 (41.2%), age: M = 6.24, SD = .30) made up the control group (CG) and followed the standard programs of writing skills training (uppercase, lowercase, printed, and cursive writing were presented simultaneously). The study had the prior approval of the Local Ethics Committee of Department of Education, Psychology, Communication, University of Bari “Aldo Moro” (Committee: Andrea Bosco, Associate Professor in Psychometrics and Statistics, Antonietta Curci, Associate Professor in General Psychology, Valerio Meattini Full Professor in Theoretical Philosophy). For all children, parents signed an informed consent prior to the taking part to the protocol.

Note . The statistic test was not significance.

Design overview

At pre-training (September, beginning of the school year: T0) two tasks to evaluate the prerequisites of reading and writing skills were administered. Subsequently, classes were randomly assigned to one of the two conditions: the intervention group, which took part in teaching sessions focused on cursive writing; and the control group, with classes following the traditional method of teaching writing skills. The training phase took place during the whole school year of first grade (September–May). The same tasks were administered post-training (in May, at the end of the school year: T1). In addition, in post-training, we administered a standardized battery of tests to evaluate reading and writing skills. Another six months later, prerequisites and reading and writing skills tests were administered a second time (T2) during a follow-up session (November).

Prerequisites assessment

Two tests were selected to assess the prerequisites:

• 1. Prerequisite of reading and writing skills PRCR-2/2009 (Batteria per la valutazione dei prerequisiti di letto-scrittura) [ 42 ]. Selective visual and left-right serial analysis tests were selected:

Semicircles: This task assesses the ability to analyze and remember graphic signs and their sequence; it also evaluates a visual memory of differently oriented signs.

Recognition of letters: This task examines visual analysis abilities.

Two-letter search: This task allows the evaluation of both discrimination and visual search abilities and the capacity to proceed from left to right, as well as the ability to make the short-term memory operational, all of which is fundamental to reading and writing learning.

Search of letters written in different ways: This task evaluates the ability to recognize a letter written in different allographs (uppercase, lowercase, printed and cursive) evaluating grapheme-phoneme conversion capacity.

Search of a sequence of letters: This task examines a child’s ability to look for a visual configuration sequentially, thus evaluating visual search abilities.

• 2. Test for the Evaluation of Writing and Orthographic Ability BVSCO-2 (Batteria per la Valutazione della Scrittura e della Competenza Ortografica-2) [ 43 ]. This task examines handwriting fluency when writing the sequence of letters “ LE ” for one minute (handwritten lowercase cursive characters LE praxis). The test involves the calculation of a measure of fluency: how many graphemes are written correctly in one minute.

All participants were evaluated through a collective administration.

Reading and writing skills assessment

Reading and writing skills assessment was conducted using the following tests:

• MT battery for primary school [ 44 ], for the assessment of 3 parameters: fluency, accuracy and reading comprehension. Fluency and comprehension suggest two measures of reading ability, while accuracy of reading is represented by the number of errors committed.
• Test for the Evaluation of Writing and Orthographic Ability BVSCO-2 (Batteria per la Valutazione della Scrittura e della Competenza Ortografica-2) [ 43 ]. This included two other tasks to evaluate handwriting fluency: writing the sequence of letters UNO ( ONE ) for one minute ( UNO praxis) and writing the sequence of numbers UNO-DUE- , and so on ( ONE–TWO–… ) for one minute (Number praxis). The test involves the calculation of a measure of fluency: how many graphemes are written correctly in one minute. In addition, we selected another task concerning this battery to evaluate accuracy in writing during text dictation. This test measures spelling accuracy, represented by the number of errors committed.
• Diagnosis of spelling disorders in developmental age, spelling to dictation test [ 45 ]: This consisted of two sections: dictation of (1) words and (2) pseudo-words. This test measures spelling accuracy as represented by the number of errors committed.

Training phase

The training lasted nine months, from September to May; forty sessions were managed by teachers who had been previously trained. Supervision was provided by psychologists who were expert in learning psychology (including the first author).

In applying this training to writing instruction, the first phase clarifies the conventions and characteristics of the letters, illustrating the necessary movements for their formation and verifying that each child has learned them (pre-graphism).

In the second phase, the child practices the production of letters, learning to control movements and trajectories. The aim of this phase is to produce graphemes carefully, respecting the proportions of letters, spaces, and lines of writing.

Each training session lasted about 90 minutes, with two weekly meetings. The experimental group practiced the cursive characters exclusively, while the control group practiced the two different types of writing (i.e. printed and cursive) simultaneously. These activities were carried out during teaching hours.

The sessions took place collectively, but the children worked on their own. At the beginning of the session, after a short period welcoming the children and making them feel comfortable (10 min.), and after leading review activities of the materials and activities presented in the previous session (10 min.), the teacher presented the new activities on the blackboard (20 min.). Each child practiced on their own cards for the various activities proposed (30 min.). After each card had been completed and coloured, children put the materials in a personal folder (10 min.). The last part of the lesson involved a blackboard exercise focusing on the materials presented during the session (10 min.). In order to consolidate learning, after every ten sessions there was a review lesson of the work done in the previous sessions. Children spent about 70 minutes per week writing in cursive, in accordance with the authors who have stated that handwriting should be taught systematically in short sessions several times a week, totalling 50–100 minutes per week, for it to be beneficial to students.

The activities, selected by “Write in Cursive” [ 46 ] were built on different levels in order to promote the learning of cursive handwriting:

• Pre-graphism: We started with simple executions that required a progressive degree of motor precision, sign control, directionality, and respect for spacing. In this training, we exerted the subsequent production of cursive letters through repetitive and curvilinear movements.
• Letters Presentation: Letters were presented according to their similarity and gradual articulator movements rather than in alphabetical order, respecting the following sequence: a, o, c, d, g, q / i, t, u / n, m / e, l, f, b / v, w, r, s/ p / h / z / x, y, k, j.
• Connection Between Letters Presentation: Vowels and consonants were shown together. This movement learning becomes more valuable when children start to connect one letter to the next to write digrams and trigrams.

We preferred to use lined exercise books and not quadrille pads to support a progressive motor and space control.

Within each training session, the activities were structured by steps:

• First step: all rules and characteristics of the cursive letters were explained to the entire group by having the teacher demonstrate the correct movements to execute each letter on the blackboard. The teacher dedicated to this activity about 15 minutes of each session.
• Second step: the children subsequently began their individual activity on the pages in the manual. The activity was to copy the cursive letter on a sketch design of the letter either in isolation or at the beginning, middle or end of a word (only the letter presented by the teacher, and not the other letters of the word); this task demanded increasing motor, direction and space control.
• Third step: the next task consisted of copying the same cursive letter on one page of their notebook for about 50 times (A4 format). This task, through repetitive and circular movements, enabled the children to strengthen the writing of cursive letters.
• Fourth step: the last task was the fusion of cursive letters to form syllables and then words. Consequently, children practiced cursive letters writing by controlling the movements and trajectories in order to better understand the relationship between cursive letters, spaces and lines.
• Fifth step: finally, to verify correct production across all students, the teacher performed a double check; the first on-line occurred during the writing of the letters, and consisted of correcting the pupils who produced erratic movements; the second occurred after execution, by verifying the single materials produced by the pupils. Those pupils who showed more uncertain graphic traits or incorrect production were joined by the teacher in the next session.

The training activities did not provide any intervention on reading skills or orthographic knowledge. For these skills, students followed traditional teaching methods.

Preliminary analyses

First, we tested for possible associations between the socio-demographic variables (child’s gender and mother’s and father’s years of education) and the variables of interest in the study at each time point. All preliminary analyses were tested using the Bonferroni-corrected alpha level to protect against capitalizing of chance, according to the number of associations that were tested at each time point (6 at the pre-test, and 14 at the post-test and follow-up). None of the measures at each time point was found to be associated with mothers’ and fathers’ years of education. As to the effect of the child’s gender, none of the measures collected at each time point differed between girls and boys, with the exception of the two-letter search in the post-test, t(139) = 3.42, p < .001, with girls performing significantly better compared to boys, M girls = 3.94, SD = 3.10; M boys = 6.36, SD = 4.99 (lower scores indicate a better performance, as scores refer to the number of errors).

Main analyses

Because we were dealing with a repeated-measures design with measurements collected at two and three points in time (Level 1) nested within cases (Level 2), the aims were tested using multilevel models which allow the treatment of non-independent measures and give the added advantage of being able to deal with missing data at each time point. A set of multilevel models were run, with measures at each time (Level 1) nested within cases (Level 2). Each of the six measures of prerequisite reading and writing skills as well as those of reading, writing and spelling skills (respectively three, two and three measures) was used as the dependent variable. As random effects, we entered intercepts for subjects as well as by-subject random slopes for the effect of time, with a variance components covariance structure. This latter random effect was dropped when it did not result in a significant increase of the model fit. In accordance with the aims, the fixed effects of time and group (intervention vs. control) were tested: the first predictor allowed us to test whether the outcomes underwent a change over time, irrespective of group; the second predictor allowed us to test whether the two groups differed in the outcome measures. Thirdly, the interaction term time X group was inserted in order to verify whether the effect of time was moderated by that of the intervention. The test of our aims depends mainly on this term, which whether significant or not proved that the intervention was causing different growth curves of the outcome/s across the two groups (intervention vs. control). Along with these predictors, in order to control for possible effects on the outcome, fixed effects of the child’s gender were also included in the models and were dropped from the final models if they resulted in non-significant effects. Δ -2LL < .05 and lowest Akaike’s AIC were the fit indexes used to select the models best fitting the data, for nested and non-nested models respectively.

As to the test of the first aim, the models for each outcome measure with the best fit are reported in Table 3 : None of the models predicting the prerequisites gained significant fit from the random effects of time, suggesting no significant inter-individual variability in the growth curve of each outcome; therefore, this effect was dropped from each final model. As to the fixed effects of time, results show a linear improvement in the recognition of letters, the search of sequences of letters, and handwriting speed. Conversely, the two-letter search results worsened from one time to the next. Gender was found to be a significant predictor of performance in the two-letter search and the recognition of sequences of letters, with girls performing better compared to boys in both cases. As expected, group condition was found not to be a significant predictor, which means that there were no significant differences between the two groups in the dependent variable, while a significant interaction group X time was found for three out of five outcomes, namely, the performance in the semicircles task, the two-letter search, and handwriting speed. Overall, these interactions mean that over time in the two groups the dependent variables underwent different growth rates. In order to explore these interaction effects and understand the differing growth rates of the measures among the two groups, the mixed models were re-run separately for each sub-group [ 47 ]. Each model included the fixed and random effects of time, while the between-subject variance was estimated by entering intercepts for subjects as the random effects. Results showed that performance on the three tasks was better overall among the children belonging to the intervention group compared to those of the control group; as to the performance in the semicircles task, from one time to the next, the children demonstrated reduced errors of b = -1.436, p < .001, intercept = 3.711, p < .001 in the intervention group, compared to b = -.35, n.s., intercept = 3.064, p < .001 in the control group. As to the two-letter-search task, the performance of the control group decreased significantly over time, b = 2.127, p < .001, intercept = 7.247, p < .001, while that of the intervention group remained stable, b = .539, n.s., intercept = 7.386, p < .001. Lastly, as to handwriting speed, the intervention group gained on average almost 16 graphemes per minute across time, compared to the control group which gained on average 11 graphemes per minute from one time point to the next, b = 15.953, p < .001, intercept = 44.641 and b = 11.003, p < .001, intercept = 42.853, p < .001, respectively for each group. Fit of the models run within each group to explore the interaction effects time X group did not improve their fix when estimating the random effects of time, suggesting, therefore, a similar slope for the effects of time among the children of each group (intervention vs. control).

* p < .05.

** p < .01.

*** p < .001.

Note . Time: 0,1, 2. Group: 0 = control; 1 = intervention. Gender: male -.5 and female .5. Random effects of time were dropped due to the lack of a significant increase in the fit indexes.

With respect to the test of the second aim, models with the best fit indexes predicting reading skills are reported in Table 4 and show that reading comprehension, fluency and accuracy increase linearly over time and none were predicted by child’s gender; models predicting reading fluency and accuracy also included random effects of time, suggesting significant inter-individual differences in slopes for the effects of time. As to the group effects, the group benefitting from the intervention months before performed better on reading comprehension but worse on reading accuracy when compared to the control group. Lastly, the interaction term group X time was significant for reading comprehension and fluency, which means that over time in the two groups the dependent variables underwent different growth rates. In order to explore these interaction effects and understand the different growth rates of the measures among the two groups, the mixed models were re-run separately for each sub-group [ 48 ]. Each model included the fixed and random effects of time, while the between-subject variance was estimated by entering intercepts for subjects as the random effects. As to reading fluency, the model tested among each group showed that the random effects of time increased the fit only for the intervention group, suggesting significant inter-individual variability in the growth curve among the children who had benefitted from the intervention. Over time, the reading fluency of these children decreased significantly, b = -.238, p < .001, intercept = 1.161, p < .001. Conversely, the reading fluency scored of the children in the control group increased significantly over time, b = .198, p < .05, despite having an average starting point lower than that of the intervention group (intercept = 1.131, p < .001).

Note . Time: 0,1, 2. Group: 0 = control; 1 = intervention. Gender: male = -.5; female = .5.

A similar pattern of results emerged from the single slope analysis predicting reading comprehension: the model tested in each group showed that the random effects of time increased the fit only among the intervention group, suggesting a significant inter-individual variability in the slope for the effect of time for the children who had benefitted from the intervention. Over time, these children remained stable in their reading comprehension, b = -213, n.s., intercept = 8.739, p < .001. Conversely, the children of the control group displayed an average level of comprehension lower than that of the intervention group, intercept = 6.782, p < .001, but differently from the intervention children, it increased significantly over time, b = 1.433, p < .001.

Models with the best fit indexes predicting writing skills are reported in Table 5 and show that none of the two indexes for writing fluency was predicted by the child’s gender, and that both increased linearly over time. Besides the fixed effects of time, writing fluency was also predicted by a random effect of time, suggesting significant inter-individual differences in the children’s improvement. Children who had benefited from the intervention had better performance, compared to the control group; nevertheless, as the significant interaction term time X group and the following single slope analysis both suggest, the intervention group started with a higher performance in writing fluency on the word ONE which did not increase significantly over time, while the control group displayed a significant increase in the same performance, although having a much lower starting point compared to the former group, b = 1.493, n.s., intercept = 59.972, p < .001 in the intervention group and b = 7.460, p < .001, intercept = 48.797, p < .001.

Lastly, models with the best fit indexes predicting spelling skills are reported in Table 6 and show that spelling skills were not predicted by gender, nor by random effects of time, suggesting similar slopes among the children. Spelling words and pseudo-words significantly increased over time, while spelling text did not. Children who had benefited from the intervention, when compared to the control children, displayed overall higher performance on all three spelling skills tests, as their performances were characterized by a significantly lower number of mistakes. Lastly, no significant interaction was found between time and group condition, suggesting that both groups underwent the same changes over time.

This study focused on the impact of visual-motor handwriting training on the reading and writing skills of 6-year-old children. The children involved had not yet begun systematic school handwriting instruction. We therefore aimed to explore the effects of a teaching program focused on intensive cursive instruction on: (a) the prerequisites of writing and reading; and (b) the acquisition of writing and reading skills. The results revealed that changes in reading and writing skills varied as a function of the type of training received. Moreover, within the longitudinal research design we also tested the effects of time. Regarding the first aim, we found that post-training, the intervention group made fewer mistakes than the control group in the “semicircles” task. The intervention group also showed a more stable performance through time in the “two-letter-search task. Moreover, the intervention group was able to write 16 graphemes per minute, while the control group had a rate of 11 graphemes per minute. In line with previous studies, the reading and writing prerequisites strongly correlated with age, thus suggesting that the progressive acquisition of the visual search ability and the semicircles task followed a specific developmental trajectory [ 45 ].

We can detect a worsening performance in each group over time in the “two-letter-search” task. Nevertheless, the training group’s performance was more stable than the control group’s performance. This performance difference can be explained by the children’s ability to process the words in their entirety by accessing mental vocabulary, rather than identifying every single letter which forms the word itself (global versus local processing) [ 45 ]. As far as writing fluency is concerned, our data comply with previous studies which show a linear relationship between graphic-motor abilities and developmental trajectories [ 49 , 50 ]. The higher number of graphemes written by the intervention group is due to the training. This result is important because handwriting speed can be considered a good predictor for more complex tasks such as orthography and test processing. A substantial gender difference in prerequisite tasks—mainly in analysis and visual search abilities—in favor of females was found. Previous studies have demonstrated a higher rate of learning disabilities in boys than girls, but it has not yet been fully explained why this gender difference appears. In most studies the gender effect appears in the early stages of learning [ 49 ]. Therefore, this study suggests that the gender difference can play a relevant role in reading and writing prerequisite skills, but that these differences were no longer present further on when considering writing and reading skills. The second aim of the present study was to analyze the effect of training on reading and writing skills. There are a lot of research studies that demonstrate a linear trend of reading skills, highlighting an increased performance in instrumental reading abilities such as fluency and accuracy, as well as text comprehension. These data can be observed for both groups, but there is also an inter-individual difference over time. This variability affects the first learning phases in reading; performances become more homogeneous with schooling and with age. Accuracy reading performance in the control group increased more than in the intervention group, since there were substantial differences at the beginning: the control group started from a significantly lower average performance, not due to an effect of the training. Similarly, at the early learning stages, text comprehension processes are necessarily distinguished by a huge inter-individual variability, because text comprehension is a complex learning process in which several abilities merge; as a consequence, it takes a longer period and more skills to make this ability stable over time. In the early learning stages, we cannot find a strict correlation between reading abilities and comprehension [ 50 ]; indeed, some studies show that children in the fourth grade are able to understand the meaning of a text even without proper accuracy abilities [ 51 ]. This result may be obtained by submitting simpler texts with lower syntactic complexity [ 5 ]. It is worth pointing out how the training produced a certain stabilizing effect from the early learning stages, for both instrumental reading abilities and text comprehension. In various studies, this fact is seen as a good predictor of study skills in the following years. Concerning writing and reading abilities, there is a remarkable linear growth over the time due to a higher grapho-motor control. Concerning writing speed, many studies show that automating certain activities in the act of handwriting may enable students to apply their cognitive resources to more complex activities, such as orthographic accuracy [ 27 ]. As proof of what was previously stated, the intervention group achieved better performance both in orthographic ability and text fundamental units. These findings are in agreement with the literature in affirming that the development of more fluent writing with grapho-motor abilities during the early stages of learning to write enables students to reach better accuracy levels for orthographic features [ 48 ]. The most interesting result related to cursive handwriting training is the data regarding writing fluency. A great deal of the literature supports the idea that children with more fluent handwriting in the early stages of learning show better writing abilities in terms of orthography and increased text composition skills. Our results support the literature by underlining the relationship between graphic and orthographic skills. This relationship is observed and supported by other studies [ 15 , 16 , 20 , 25 ], which show the contribution made by this variable with regard to more complex cognitive writing skills. We also observed that the intervention group’s handwriting skills changed dramatically over the school year, showing better results than those predicted by the usual evolutionary trends. These results demonstrate how children can improve not only basic skills, but also subsequent learning abilities thanks to domain-specific training carried out in the field of grapho-motor learning. Our study supports recent works that demonstrate how improvements in instrumental handwriting features may occur upon teaching and direct, explicit daily practice [ 15 , 16 ], particularly during the early stages of schooling. All this suggests the importance of automating the production of letters and words during writing so children can direct their attentive resources to the regulation of more complex aspects of text production, such as the decoding of texts and the orthographic accuracy of writing [ 8 ]. In fact, working memory seems to play a key role in the processes of writing and reading.

Bourdin and Fayol [ 7 ] examined writing processes within the explicit context of working memory. They varied the response modality (spoken vs. written) in a serial recall task and found that recall was significantly poorer in the written condition for children but not for adults. The authors interpreted these findings as evidence that the transcription process of adults, but not children, was sufficiently fluent to operate with minimal working memory demands. When adults were required to write in cursive uppercase letters, thereby preventing their use of overlearned, highly fluent transcription processes and depriving them of access to working memory, also adults showed poorer recall when writing. In a related series of experiments, Bourdin and Fayol [ 7 ] changed the task from serial recall to sentence generation and again demonstrated that transcription imposed resource costs for children but not for adults. Thus, until transcription processes develop sufficient fluency, writers seem constrained by working memory limits [ 9 ]. With regard to the reading processes, certainly the training of visuo-spatial skills has strengthened the positive effect that writing has provided to reading skills. A study undertaken at Indiana State University, in which an experimental group of children were taught exclusively cursive writing in the first grade, appears to support our position. Achievement in spelling and word reading was higher in the experimental group, while there were more reversals and transposition errors in the control group [ 52 ]. Recent studies support the same results [ 30 , 53 , 54 ].

Nevertheless, we believe that working on the quality of the practice is fundamental; otherwise it would be highly improbable for writing feature rates to increase without negatively affecting readability. Concerning this feature of education, further investigation is needed to better understand the relation between handwriting practice and the development of writing abilities during primary school. Moreover, our study introduces an innovative fact not previously dealt with in recent literature: that children who adopted the cursive type as the only handwriting type showed a higher writing rate than pupils using more types. This fact contrasts with the literature which states that the cursive type decreases writing rates [ 51 ]. We also observed that pupils using cursive as the only handwriting type had better results in producing orthographically correct words than students using more types. As shown by other studies [ 20 ], it seems that the grapho-motor component affects word production management, especially for writers in the learning phase. In addition, we observed that children who only learned the cursive type made faster improvements in reading. This fact may be explained by a major focus of active resources on the lexical access task. The very nature of the cursive type may help students to easily memorize and recall a word unit, since in the cursive type the letters of a word are linked one to another, while in print type they are separated [ 35 ].

In conclusion, like other studies [ 10 , 11 , 35 ], our work tends to demonstrate how, upon training, writing and reading abilities improve in terms of written letter rate (students write faster), orthography (words are written correctly), and reading (students read and understand better). However, writing quality is a parameter to be investigated thoroughly in further studies. Considering writing type, we can observe how students who learn every type simultaneously do not achieve results as good as those achieved by cursive-only students. This finding supports the idea that the development of writing abilities in primary school is better favored by the teaching of a single type of handwriting, namely cursive handwriting. Furthermore, teaching of the cursive type generates improvement in graphic and orthographic word production by the end of the school year. A remarkable feature to be taken into account is the rapid improvement of basic skills in the intervention group as compared to the control group.

Our research sheds light on a number of educational issues. Firstly, it is necessary to think about the role of grapho-motor abilities in the development of handwriting skills, as well as giving more weight to grapho-motor skills in teaching plans. Secondly, it is important to support the teaching community to ensure that decisions regarding handwriting automatization are taken at the beginning of the educational process [ 55 ]. In order to do so, explicit and direct teaching of letter shapes and frequent practice are essential elements [ 35 ]. Last but not least, it is necessary to think further about the relevance of single-learning process based teaching, since it has been demonstrated that by acting on single learning abilities, there are greater advantages to be had in future learning.

Funding Statement

The authors received no specific funding for this work.

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The Research on Cursive Handwriting

Colleen beck otr/l.

• by Colleen Beck OTR/L
• November 1, 2017

If you have a school aged child, then you might have seen them learn cursive in schools…or maybe not. In recent years, cursive seems to have dropped from the radar in school curriculum. But why is that? What does the research tell us about cursive handwriting, and what is the science behind cursive? Should cursive be brought back to the classrooms? In this blog post, we’re talking specifically about the latest research on cursive handwriting.

We do have an extensive series and resources on how to teach cursive handwriting , so if the cursive writing research below gets you interested, you can start there!

Cursive Handwriting Research

So, what does research say about cursive handwriting? A lot!

We pulled together a few links on different research studies that looked at different components of cursive writing. The research tells us that cursive changes the brain and helps with learning!

One thing that we have to consider (as parents and as school based OT professionals who are in the mess of handwriting goals…) is to consider technology. Kids are surrounded by tech, screens, and apps all day long. And, that’s not a terrible thing, it’s just that moderation is needed.

So, when it comes to cursive handwriting specifically, we have the technology of tablets and the writing stylus. One team of researchers shared the benefits of practicing letter formation. But, knowing how important it is to practice handwriting and that physical act of writing letters, what do we do about all of the screen use and technology we have now?

The nice thing that we see in occupational therapy in the schools is that we can transition kids from print to cursive as a tool for supporting letter formation. This helps with the motor plan of writing. It also helps with letter reversals. But, we can also use the technology to practice and get all of the benefits of learning letters.

Another study found that using a stylus and screen is just as effective as writing on paper and with a pencil. This is great for the student that needs motivating handwriting activities to actually practice letter formation.

So, what’s the takeaway? It’s all about finding the right balance. Whether you’re a student or a teacher, it’s smart to know when to go digital or stick with traditional methods. Plus, everyone’s different, right? Still another study found that what works for one learner might not click with another and that using different strategies can build those neural pathways.

Cursive Changes the Brain

This link explores the brain and how it relates to cursive handwriting . Some important areas that are referenced include findings of  changes occurring in the brains that allow a child to overcome motor challenges  when children are exposed to cursive handwriting.

Additionally, the article describes a study in which has shown that physical instruction such as cursive handwriting lessons actually changed the participant’s brain structure.

Cursive for Motor Control Challenges

There is some research indicating cursive handwriting can be a valuable tool for motor control challenges such as those who struggle with dyslexia or dysgraphia. Read more about dyslexia and occupational therapy .

It’s been found that there are distinct neural pathways that develop when we physically write letters. 

N euroimaging studies have revealed an cognitive processes involving primarily left-hemisphere brain areas that are involved in writing tasks, finger writing, and imagined writing.

Cursive Progression

Cursive handwriting, like printed handwriting becomes more individualistic and develops a personal style, especially during grades 3 and 4, and as children develop . 

Practice matters! Quality of handwriting has been shown to  enhance writing skills, reading, and learning or memory of language.

There are studies that have shown improved handwriting abilities through use of multi-sensory activities (Case-Smith et al., 2012; Keller, 2001; Lust & Donica, 2011). You’ll find more research on handwriting in The Handwriting Book:

Research references on cursive handwriting

Case-Smith, J., Holland, T., Lane, A., & White, S. (2012). Effect of a co-teaching handwriting program for first graders: One-group pretest-posttest design. The American Journal of Occupational Therapy, 66(4), 396-405. Keller, M. (2001). Handwriting club: Using sensory integration strategies to improve handwriting. Intervention in School and Clinic, 37(1), 9. Lust, C. A., & Donica, D. K. (2011). Effectiveness of a handwriting readiness program in Head Start: A two-group controlled trial. The American Journal of Occupational Therapy, 65(5), 560-8.

Over the past 30 days, we’ve shared cursive handwriting tips, strategies, activity ideas, free resources including cursive letter flashcards, tricks, and everything you need to know on how to teach cursive handwriting. Today, as a final post in this cursive handwriting series, we wanted to share the science behind cursive.

Below, you’ll find the research on cursive handwriting . These are the studies that explore cursive, the evidence, and the sources you need for teaching and learning to write in cursive. This post is part of our 31 day series on teaching cursive. You’ll want to check out the  How to Teach Cursive Writing  page where you can find all of the posts in this series.  For more ways to address the underlying skills needed for  handwriting , check out the handwriting drop-down tab at the top of this site.

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Cursive Writing: What Is It & How To Learn Cursive

• January 18, 2024

Table of Contents:

Introduction, what is cursive writing, background of cursive writing, learning cursive writing: take it step by step, step 1: understand the cursive alphabet, step 2: master individual letters, step 3: practice capital letters, step 4: joining letters, step 6: practice with sentences, is there an order for teaching cursive writing, why people write in cursive, speed and efficiency:, intellectual development:, aesthetic appeal:, individuality:, tips to write well in cursive, understand the cursive alphabet:, use the right tools:, start with lowercase letters:, consistent practice:, master the connections:, maintain a steady pace:, posture and grip matter:, experiment with styles:, conclusion:.

Cursive writing is a style of handwriting where all the letters in a word are joined, giving the penmanship a flowing, often elegant, appearance. One can trace its origins back to Roman times. At its core, this writing is a skill blending aesthetics and efficiency – it helps write faster and adds a visual appeal to the written text. Learning cursive involves more than just mastering elegant letters. It enhances cognitive abilities and academic performance, contributing to children’s mental and intellectual development.

Our Manuscript Writing Guide offers step-by-step instructions on writing in cursive and provides insightful tips to make learning more enjoyable and rewarding.

Cursive writing is a unique style of penmanship primarily characterized by handwriting, where letters are often connected in a flowing manner. ‘Cursive’ is derived from the Latin’ cursivus,’ meaning ‘flowing’ or ‘running.’ This alludes to the pen’s flowing and continuous movement while writing cursive.

When learning cursive, consider letter positioning and shape as key elements. Each letter has its designated line, forming a joint writing style prevalent throughout history. Cursive, valued by professors, enhances writing prowess.

Master sloping letters starting from the base and ending with a stroke at the upper baseline. Some letters feature loops at the top or bottom, varying by letter.

Now, let’s talk about a little of its history. The origins of cursive writing date back to the times of ancient civilizations. The Romans were among the first societies to use this writing style, developing it as a way to write faster and more efficiently. This swift writing style was valuable, enabling scribes to capture live speeches and facilitating maintaining records more quickly.

But it took off during the Renaissance, with the advent of the writing method known as “Italic Handwriting.” Named after Italy, its place of origin, Italic Handwriting is a semi-cursive writing style characterized by curved and flowing letters, which were easier to write and more aesthetic.

By the 18th and 19th centuries, this writing style became commonly taught in schools worldwide. Modifications and developments led to different styles of cursive writing, influenced by specific geographical regions like English Roundhand and Spencerian Script in America.

Learning to write in cursive can be super fun and rewarding. It’s like drawing and writing all mixed up together. Here’s a step-by-step guide that’ll have you writing cursive like a pro in no time.

Okay, so each cursive letter is a bit like a little drawing. Some are like loops, and others have tails. Knowing what each letter should look like is your first big step. And watch out for the ‘entry strokes’ and ‘exit strokes’ – they’re like ramps to help letters join up and dance across the page together.

Now, let’s buckle down and draw – I mean, write these letters! Grab some lined paper (those lines are like training wheels), and start with the easiest lower-case ones like ‘c,’ ‘l,’ ‘a,’ ‘d,’ ‘g,’ and ‘o.’ They’re mostly all about the loop-de-loops. After you’ve got the easy dudes down, step up to the tricky gang like ‘b,’ ‘f,’ ‘k,’ ‘p,’ and ‘z.’

Capital letters in cursive can look super fancy, like kings and queens of the alphabet. They’re a bit tougher than the lower-case crew, so tackle them with patience. Like before, stick with it until you feel you’ve befriended each of these capital letter royals.

Linking the letters together is what makes cursive, well, cursive! Practice sliding from one letter to the next without picking up your pen. It’s like they’re holding hands.

Then, It’s combining letters time! Start small with easy words. Once you’re good at those, throw in some longer ones. It’s like building with blocks – start with a small tower before you build the castle.

Got the hang of individual words? Excellent! Now, it’s time to connect them into sentences. This is where all your learning truly comes to life. Keep that pen flowing, connecting your thoughts and your paper seamlessly.

As with any skill, mastering cursive writing requires a dedicated commitment. Establish a writing routine where you put aside at least 20 minutes each day to focus on the cursive alphabet—start with lowercase letters before progressing to uppercase ones. Writing essay drafts in cursive enhances skill and familiarity. Later, type them into a Word document for ease and practice.

The more you write, the more your hand remembers, and the better you get. It’s like playing a game – the more you play, the higher your score.

Teaching cursive doesn’t follow a strict order, but experts suggest starting with lowercase letters before uppercase ones.

Children typically begin learning cursive around age seven, progressing independently by age nine. The recommended order for learning cursive letters includes:

– c, a, d, g, q

– i, t, p, u, w, j

– e, l, f, h

– k, r, s

– b, o, v

– m, n, y, x, z

This sequence, backed by research, introduces simpler letters first, resembling their print counterparts and aiding in joining words efficiently. Progression to more complex letters occurs as children master initial ones through consistent practice.

Cursive writing is gradually regaining popularity, with handwriting enthusiasts and educational institutions advocating its benefits. Here are a few reasons why people choose to write in cursive:

Writing in cursive is significantly faster than print handwriting. The continuous flow of cursive handwriting increases writing speed, promoting efficiency.

Research suggests that learning cursive can enhance intellectual development in children. It helps refine motor skills, improves literacy levels, facilitates memory recall, and promotes the development of cognitive skills.

Cursive handwriting offers a unique aesthetic appeal that adds personal charm to any written piece. Its fluidity makes it ideal for ceremonial documents and calligraphy. Furthermore, the role of cover design typesetting enhances this visual charm in print documents, creating a polished look.

In addition to its functional and cognitive benefits, this writing style is unique to each writer. How one connects and forms letters is typically individual, fostering self-expression and providing a sense of identity through penmanship.

Writing in Cursive is a beautiful art form, though it may seem daunting initially. Here are some practical tips to improve your cursive writing skills:

To write well in cursive, first familiarize yourself with the cursive alphabet. Note the nuances for each letter in the cursive script — both lowercase and uppercase.

A good quality pen or pencil and lined paper can greatly impact how you learn this writing style. A pen running smoothly over the paper will make writing much easier.

Lowercase letters are simpler and more frequently used in this style of writing. Practice them consistently until you’re comfortable, then graduate to uppercase letters.

Like any other skill, practice makes perfect. Develop a habit of writing in cursive daily. This consistency will help you retain the unique strokes of cursive.

The cursive style of writing is all about the flow. Spend ample time mastering connecting one letter to another, creating an uninterrupted line of text.

Keep your speed slow and consistent while learning. Trying to write quickly may make your letterforms sloppy. As you become more comfortable with cursive writing, gradually increase your speed while maintaining legibility.

A comfortable sitting posture and a relaxed yet firm grip on the pen can help you write better and for longer periods.

Over time, you can experiment with cursive variations to develop your unique style. Remember, your handwriting is a reflection of your individuality.

Should You Teach Cursive Writing?

Teaching cursive writing offers numerous benefits, making it a valuable skill for children. Beautiful cursive enhances neatness and writing speed, which is crucial for jotting down lecture notes efficiently.

Cursive fosters motor skills, pen control, and letter recognition while refining manual dexterity and hand-eye coordination. Introducing cursive early facilitates easier skill absorption, aiding overall education.

Cursive isn’t limited to English; it’s a tool across disciplines. Encouraging cursive empowers children to express themselves uniquely, fostering individual handwriting styles. Embrace the art of cursive for its practicality and personal touch in communication and self-expression.

When considering all the enriching benefits of learning cursive, it’s also worth noting that these skills extend beyond education settings. Partnering with a Business Book Writing can bring that vision to life for those looking to further reinforce this skill, or perhaps even publish their cursive practice materials. Such services can assist in creating customized practice books to preserve the art of cursive writing.

Cursive writing is integral to human culture and history with varied practical, intellectual, and aesthetic benefits. While technology continues to evolve and mechanical typing replaces handwriting, nothing can beat the charm, individuality, and personal touch of a well-scripted cursive note.

Becoming proficient in cursive involves more than mastering strokes and connections—it promotes cognitive growth and fosters a feeling of artistic individuality.

Though technology’s impact is immense, particularly with tools like AI writing generators for creating custom learning resources, the significance of cursive doesn’t dwindle. Using AI for studying cursive can be an advantage, but the essence of the skill lies in personal dedication and practice.

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The scripts favoured by English scribes evolved and changed over time. At the beginning of the medieval period, scribes used 'set' scripts, which were very formal and tidy. Well-separated letters were their principal characteristic. However, the most significant development in script in the English Middle Ages was the evolution of cursive hands which made the process of writing quicker and more efficient. Cursive scripts contain letter forms made with as few strokes of the pen as possible. They were first developed for the speedy copying of official documents or records, but gradually became used for copying other types of text. Many hands are made up of a mixture of characteristics from different styles.

Textura Script

Sometimes called Gothic Book Hand or Black Letter, this was the most enduring script of the Middle Ages and was in use from the twelfth to the sixteenth century. It is not a cursive hand, and is instead characterised by an upright appearance, and the use of separate strokes to form letters, which required the frequent raising or lifting of the nib from the writing surface. Letter forms are kept separate from one another, and when well spaced give an appearance of formality and neatness. There are various different forms of Textura, usually characterised by the way in which scribes formed the bottom of their letters.

The example below is a Textura Quadrata hand, written c.1250-1300. Quadrata is the 'high-Gothic' variety of Textura, which is characterised by the consistent use of diamond-shaped feet on 'minim' letters made up of vertical strokes (such as i, m, n, u). The script is very regular and used for good quality books. Note the diamond shapes at the end of the lines and, less clearly, at the foot of letters. The top stroke of the letter 'a' is open, which is not a characteristic of true Textura Quatrata.

Detail from WLC/LM/4, f. 8v

The 'rotunda' form of Textura has minims with rounded or curved feet formed through the natural upward movement of the pen nib. This was the least formal type of Textura. In the example below, from the mid-thirteenth century, the letter 'g' is formed like the number '8'. This is seen more frequently in 'Anglicana' hands.

Detail from WLC/LM/3, f. 72r

After the thirteenth century Textura was seldom used to copy literary manuscripts containing texts in English. In the fourteenth and fifteenth centuries it became increasingly associated with liturgical or devotional manuscripts, or luxury books of a secular nature, as a display script. An excellent example of the use of Textura as a display script in a high-quality book is provided by the Wollaton Antiphonal, which was probably written in the 1430s.

Detail from the Wollaton Antiphonal, MS 250, f. 207r

Cursive scripts (Cursiva)

Cursive scripts were developed for business use such as the copying of documents and letters. They gradually became used for the speedier and more efficient copying of literary texts too.

The cursive form 'Anglicana' developed in England from Textura to become the most widely-used book hand of the later Middle Ages in Britain and northern France. It first appears in documents in around 1260, and is the script most often used in the fourteenth and fifteenth centuries for the copying of English literary texts (especially the manuscripts of works of Chaucer and Langland). A variety of Anglicana continued to be used as a legal hand as late as the eighteenth century.

This fragment from the South English Legendary, written in the early fourteenth century, is in Anglicana. One of the most striking differences from Textura is how many letters extend above or below the writing line. For instance, a long-tailed 'r' with the descender reaching below the line of writing (as seen in the second word, 'seruant'), and a long 's' which also extends below the writing line (as seen in the word 'ssame' at the end of the second line. At this date, this script is also characterised by hooks and flourishes.

Detail from WLC/LM/38

Like Textura, Anglicana also developed different varieties. 'Anglicana Formata' is the most formal of these. It was used for copying books and shows letter forms which are uniform and separate. Cursive forms are kept to a minimum. In particular, ascenders and descenders are shorter and less exaggerated and the script looks solid and square.

Here are two examples from fifteenth-century manuscripts in the Wollaton Library Collection. The second example shown here is an Anglicana Formata with some traits from Textura, especially in the letter 'd', and in the way the minims have been carefully finished.

Detail from Speculum Vitae , WLC/LM/9, f. 199r

Detail from John Gower, Confessio Amantis, WLC/LM/8, f. 67r

Court hands 

The scripts used for writing legal and administrative documents were slightly different from formal book hands used for literary works, but shared many characteristics. These are the hands that local historians will most often encounter. Overall they are called 'court hands', but certain government departments developed their own particular styles of handwriting, such as 'Exchequer hand' and 'Chancery hand', which get harder to read as they fossilize into very stylized forms after the fifteenth century.

The example below is a typically spiky, precise hand used for writing charters in the twelfth century.

Detail from Me 3 D 2, c.1175

In the thirteenth century scribes began to use a form of Cursiva Anglicana. The hand is rounder and more fluid, but still employs tall ascenders, some of which ('H' and 'L') have hooks at the top. The capital letters are embellished with double lines.

Detail from Ne D 2172, c.1230-1250

Below is an early fourteenth-century example of an administrative record. The cursive style of writing, and the very extensive use of abbreviations, allowed the scribe to write fast.

Detail from manorial court record, MS 66/1, c.1430

In the later Middle Ages there is a lot more variety in types of hand, and many overlaps between particular styles. Here is an example of a cursive script from the late fourteenth century. Ascenders and abbreviations are still quite looped but not as tall and extended as in the previous example.

Detail from Ne D 4716, 1388

The next example is a very clear script from the mid-fifteenth century, by the professional scribe 'Froddesham'. In comparison with the previous example, the letters are very tightly formed. This hand owes something to Textura scripts, especially in the way some of the letters such as 'd', 'o' and 's' are written using a diamond, rather than a round, shape.

Detail from Ne D 4662, 1452

Towards the end of the fifteenth century 'Secretary' script, imported to England from France and Italy a century before, came to have substantial influence on the way in which scribes wrote. It is characterised by a slanting or angular appearance and the use of broken strokes where one would expect to find curved strokes used to form the lobes or bows of letters such as a 'a', 'd' and 'g'. Descenders slope and taper.

This marriage agreement includes some elements which would be seen in later Secretary hands, but the writing seems to be a personal, rather hybrid style. For instance, the scribe sometimes writes 'the', but sometimes uses the old Anglo-Saxon letter thorn, 'þe'.

Detail from Ne D 1903, 1476

Next page: Letter forms and abbreviations

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Why Cursive Handwriting Is Good for Your Brain

Writing by hand helps the brain learn and remember better, an eeg study finds..

Posted October 2, 2020 | Reviewed by Devon Frye

As school-age children increasingly rely solely on digital devices for remote- and in-class learning, many K-12 school systems around the world are phasing out cursive handwriting and no longer mandate that kids learn how to write in longhand script. Relying solely on a keyboard to learn the alphabet and type out written words could be problematic; accumulating evidence suggests that not learning cursive handwriting may hinder the brain's optimum potential to learn and remember.

A new EEG-based study by researchers at the Norwegian University of Science and Technology (NTNU) reaffirms the importance of "old-fashioned" cursive handwriting in the 21st-century's Computer Age. Even if students use digital pens and write by hand on an interactive computer screen, cursive handwriting helps the brain learn and remember better. These findings ( Askvik, Van der Weel, & Van der Meer, 2020 ) were recently published in the peer-reviewed journal Frontiers in Psychology .

"Some schools in Norway have become completely digital and skip handwriting training altogether. Finnish schools are even more digitized than in Norway. Very few schools offer any handwriting training at all," Audrey van der Meer , a neuropsychology professor at NTNU, said in an October 1 news release . "Given the development of the last several years, we risk having one or more generations lose the ability to write by hand. Our research and that of others show that this would be a very unfortunate consequence of increased digital activity."

For this study, Van der Meer and colleagues used high-density EEG monitoring to study how the brain's electrical activity differed when a cohort of 12-year-old children and young adults were handwriting in cursive, typewriting on a keyboard, or drawing visually presented words using a digital pen on a touchscreen, or with traditional pencil and paper.

Data analysis showed that cursive handwriting primed the brain for learning by synchronizing brain waves in the theta rhythm range (4-7 Hz) and stimulating more electrical activity in the brain's parietal lobe and central regions. "Existing literature suggests that such oscillatory neuronal activity in these particular brain areas is important for memory and for the encoding of new information and, therefore, provides the brain with optimal conditions for learning," the authors explain.

The latest (2020) research on the brain benefits of cursive handwriting adds to a growing body of evidence and neuroscience -based research on the importance of learning to write by hand. Almost a decade ago, researchers ( James & Engelhardt, 2012 ) used MRI neuroimaging to investigate the effects of handwriting on functional brain development in young children.

Karin James and Laura Engelhardt found that handwriting (but not typing or tracing letter shapes) activated a unique "reading circuit" in the brain. "These findings demonstrate that handwriting is important for the early recruitment in letter processing of brain regions known to underlie successful reading. Handwriting, therefore, may facilitate reading acquisition in young children," the authors noted.

Another recent fMRI study ( Longcamp et al., 2017 ) of handwriting and reading/writing skills in children and adults found that "the mastery of handwriting is based on the involvement of a network of brain structures whose involvement and inter-connection are specific to writing alphabet characters" and that "these skills are also the basis for the development of more complex language activities involving orthographic knowledge and composition of texts." ( For more on the brain benefits of setting our keyboards aside see " Why Writing by Hand Could Make You Smarter " by William Klemm .)

The latest (2020) study on the importance of cursive handwriting suggests that from an early age, children who are encouraged to augment time spent using a keyboard with writing by hand or drawing * establish neuronal oscillation patterns that prime the brain for learning. As the authors sum up:

" We conclude that because of the benefits of sensory-motor integration due to the larger involvement of the senses as well as fine and precisely controlled hand movements when writing by hand and when drawing, it is vital to maintain both activities in a learning environment to facilitate and optimize learning. "

Audrey van der Meer and her NTNU colleagues are advocating for policymakers to implement guidelines that ensure school-age children receive a minimum of handwriting training and encourage adults to continue writing by hand. "When you write your shopping list or lecture notes by hand, you simply remember the content better afterward," Van der Meer said in the news release.

"The use of pen and paper gives the brain more 'hooks' to hang your memories on. Writing by hand creates much more activity in the sensorimotor parts of the brain," she added. "A lot of senses are activated by pressing the pen on paper, seeing the letters you write, and hearing the sound you make while writing. These sense experiences create contact between different parts of the brain and open the brain up for learning."

* For more on the benefits of drawing and the arts to improve K-12 classroom learning see " Arts-Integrated Pedagogy May Enhance Academic Learning ."

LinkedIn and Facebook image: Aila Images/Shutterstock

Eva Ose Askvik, F. R. (Ruud) van der Weel and Audrey L. H. van der Meer. "The Importance of Cursive Handwriting Over Typewriting for Learning in the Classroom: A High-Density EEG Study of 12-Year-Old Children and Young Adults." Frontiers in Psychology (First published: July 28, 2020) DOI: 10.3389/fpsyg.2020.01810

Christopher Bergland is a retired ultra-endurance athlete turned science writer, public health advocate, and promoter of cerebellum ("little brain") optimization.

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The axe falls on precursive handwriting from Department for Education

Breaking News! The DfE announces the end of the lead-in stroke and teaching cursive handwriting from the start. 

Earlier this month, a notification was slipped in silently by the Department for Education (DfE) as part of the supporting documents for the validation of the systematic synthetic phonics programmes (SSP).

Within this document, the DfE stated that early years foundation pupils should NOT be taught separate letters that start on the baseline with a lead-in stroke and should NOT be taught cursive from the start.

Furthermore, they stated ‘all resources designed for children to read should be in print’.

Definition of PRINT: to write (text) clearly without joining the letters together. Children may be taught simple exit strokes for letters that end on the line (a, d, h, i, k, l, m, n, t, u).

A time to celebrate

We have been seeing a rapid growth in the use of the lead-in stroke in handwriting and it is a trend that has been sweeping through schools in every country over recent years.

But this ‘trend’ is like marmite, you either love it or loathe it.

For years we have repeatedly and tirelessly lobbied the Government to ban this fad from our schools and to ensure the correct methods of teaching handwriting are implemented.

Therefore, we are highly delighted by this recent announcement.

The damage lasts a lifetime

This is the first time we have revealed this picture publicly.

In 2017 a new trend started to appear.

Parents were appearing at our handwriting workshops having had their child’s handwriting copied and tattooed onto their body.

This is a lovely sentiment, but it does highlight the importance of legible handwriting.

We think that this picture speaks a thousand words about the lead-in stroke; for a child not even being able to write their own name in a legible text that can be read clearly by others, there is a clear issue.

This is why we constantly lobbied the Government and urged every school to switch from the lead-in stroke immediately.

So where did it all begin?

The lead-in stroke, also known as the entry stoke, pre-cursive, continuous cursive, or ‘whoosh’ as some children call it, was never intended to be used as a handwriting model.

It was introduced by advisors in the field of dyslexia as a ‘one style suits all’ and to save time in teaching two different styles of handwriting: printing (letter formation) and then joining (cursive).

It was sold to teaching staff as: Why teach two styles of handwriting when you can teach one?

Dr Rosemary Sassoon is a well renowned typographer and expert on handwriting, particularly that of children. She said ‘the lead-in stroke was introduced to aid the flow of ink from the nib of a fountain pen’. She also said, ‘enforcing the lead-in stroke and continuous cursive as a model is vicious’.

We wholeheartedly agree with her.

This is a mis-selling scandal by special needs groups; it is not the fault of school leaders or teaching staff, but what I do see is poor practice.

If we want to raise standards in handwriting and literacy, handwriting should be part of the Initial Teacher Training (ITT); if it were, this hideous trend would never have gained traction.

How to teach and support legible handwriting

We will keep on lobbying the Government to ensure that the lead-in stroke is quickly banished from all schools and for all teaching staff to be trained on teaching handwriting confidently and correctly, based on the science behind how we write.

The lead-in stroke is totally unnecessary even for joined-up handwriting; it damages writing confidence and it prevents automaticity and fluency.

Furthermore, children must be taught to print letters in their handwriting families and not as part of a phonics reading programme.

It is invaluable to know and understand the science behind how we write from the first mark to fluency.

Legible handwriting is achieved by having the basic requirements:

• A comfortable pencil grip.
• Good postural and visual control.
• Bi-lateral integration of motor skills and learning to print first, progressing to joining at the age of 7 years old.

Our vast amount of experience and passion for teaching handwriting correctly sets us apart from any other supplier of handwriting resources and teacher training.

Drawing on our years of expertise and research from teaching thousands of children, teenagers and adults in schools and universities, our books follow scientific research to achieve beautiful speedy and fluent handwriting.

This announcement from the DfE is something to be celebrated, but it is just the first step in building towards the correct teaching of handwriting in all schools.

Ensuring schools and teaching staff have effective support and resources at their disposal is an essential step moving forward.

As a school teacher, what do you think of this announcement from the DfE and do you feel confident about teaching handwriting moving forward?

If you feel your school would benefit from some support switching from the pre-cursive and cursive with the entry/lead-in stroke, help is on hand.

Don’t hesitate to get in touch with us to discuss your concerns and find out how we can support your school moving forward.

The contents of this page are the Copyright of Morrells Handwriting 2008-2024. Any evidence and research from 3rd parties is always quoted and accredited to the author. You are welcome to quote any content from our website, if it is quoted and accredited to Morrells Handwriting. Failure to do so is an infringement of our Copyright. All rights reserved to Morrells Handwriting.

ORIGINAL RESEARCH article

The importance of cursive handwriting over typewriting for learning in the classroom: a high-density eeg study of 12-year-old children and young adults.

• Developmental Neuroscience Laboratory, Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway

To write by hand, to type, or to draw – which of these strategies is the most efficient for optimal learning in the classroom? As digital devices are increasingly replacing traditional writing by hand, it is crucial to examine the long-term implications of this practice. High-density electroencephalogram (HD EEG) was used in 12 young adults and 12, 12-year-old children to study brain electrical activity as they were writing in cursive by hand, typewriting, or drawing visually presented words that were varying in difficulty. Analyses of temporal spectral evolution (TSE, i.e., time-dependent amplitude changes) were performed on EEG data recorded with a 256-channel sensor array. For young adults, we found that when writing by hand using a digital pen on a touchscreen, brain areas in the parietal and central regions showed event-related synchronized activity in the theta range. Existing literature suggests that such oscillatory neuronal activity in these particular brain areas is important for memory and for the encoding of new information and, therefore, provides the brain with optimal conditions for learning. When drawing, we found similar activation patterns in the parietal areas, in addition to event-related desynchronization in the alpha/beta range, suggesting both similarities but also slight differences in activation patterns when drawing and writing by hand. When typewriting on a keyboard, we found event-related desynchronized activity in the theta range and, to a lesser extent, in the alpha range in parietal and central brain regions. However, as this activity was desynchronized and differed from when writing by hand and drawing, its relation to learning remains unclear. For 12-year-old children, the same activation patterns were found, but to a lesser extent. We suggest that children, from an early age, must be exposed to handwriting and drawing activities in school to establish the neuronal oscillation patterns that are beneficial for learning. We conclude that because of the benefits of sensory-motor integration due to the larger involvement of the senses as well as fine and precisely controlled hand movements when writing by hand and when drawing, it is vital to maintain both activities in a learning environment to facilitate and optimize learning.

Introduction

Digital devices are increasingly replacing traditional writing by hand ( Longcamp et al., 2006 ; Kiefer et al., 2015 ), and as both reading and writing are becoming more and more digitized at all levels of education, it is crucial to examine the long-term implications of this practice that are still largely unknown ( Mangen and Balsvik, 2016 ; Patterson and Patterson, 2017 ). Despite several studies supporting the benefits for learning when taking notes by hand compared to laptop note-taking (e.g., Longcamp et al., 2005 ; Smoker et al., 2009 ; James and Engelhardt, 2012 ; Mueller and Oppenheimer, 2014 ; Van der Meer and Van der Weel, 2017 ), it is still unclear how computer use impacts student productivity and learning ( Patterson and Patterson, 2017 ). Due to contradictory results, it has been hard to achieve an explicit agreement, whether the technology serves to help or hinder student performance. Therefore, it is essential to further investigate the long-term implications for learning and how the processes of cursive writing, typewriting, and drawing are working in the brain within a developmental perspective.

Cursive writing is a complex and central cultural skill ( Kersey and James, 2013 ; Kiefer et al., 2015 ), involving many brain systems and the integration of both motor and perceptual skills ( Vinci-Booher et al., 2016 ; Thibon et al., 2018 ). The skill of cursive writing is often used as a tool for learning ( Arnold et al., 2017 ), considering the depths of processing that note-taking by hand provides, even in the absence of a review of the notes ( Kiewra, 1985 ). Thus, cursive writing has been considered an essential precursor for further academic success ( Fears and Lockman, 2018 ), and the skill is typically acquired during childhood in societies with a strong literacy tradition ( Kiefer et al., 2015 ). Children must learn how to coordinate their hand movements accurately and produce the shape of each letter, and they may take several years to master this precise skill ( Van der Meer and Van der Weel, 2017 ).

Today, most adults write using a keyboard and computer ( Longcamp et al., 2005 , 2006 ), and in some countries programs for elementary school education, typewriting on digital devices has already replaced traditional handwriting ( Kiefer et al., 2015 ). Therefore, the amount of time spent writing by hand has been reduced as learning activities are increasingly relying upon digital devices ( Mueller and Oppenheimer, 2014 ; Vinci-Booher et al., 2016 ). These devices (e.g., tablets and mobile phones) may improve a student’s ability to take notes, but they may also hinder learning in different and unknown ways ( Stacy and Cain, 2015 ). Most educators acknowledge note-taking as an important factor of classroom learning ( Stacy and Cain, 2015 ), and keyboard activity is now often recommended as a substitute for early handwriting as this type of activity is less demanding and frustrating for children ( Cunningham and Stanovich, 1990 ).

Proponents of computers in the classroom stress the benefits of children being able to produce large texts earlier and receiving immediate feedback on their texts and questions through the Internet ( Hultin and Westman, 2013 ). On the other hand, critics of computers in the classroom have found computer use to have a negative impact on course grades ( Patterson and Patterson, 2017 ), lower class performance ( Fried, 2008 ) as well as being distracting in the way that students habitually multitask ( Sana et al., 2013 ). Compared to typewriting training, handwriting training has not only been found to improve spelling accuracy ( Cunningham and Stanovich, 1990 ) and better memory and recall ( Longcamp et al., 2006 ; Smoker et al., 2009 ; Mueller and Oppenheimer, 2014 ), but also improved letter recognition ( Longcamp et al., 2005 , 2008 ). These benefits have not only been found in traditional handwriting using an ink pen, but also in handwriting using a digital pen ( Osugi et al., 2019 ). These results suggest that the involvement of the intricate hand movements and shaping of each letter may be beneficial in several ways. Therefore, the next question might be if any motor activity facilitates learning, or if the keyboard and pen cause different underlying neurological processes within the brain. If so, changing the motor condition while children are learning may affect their subsequent performance ( Longcamp et al., 2005 ).

From the sensorimotor point of view, cursive writing and typewriting are two distinct ways of writing and may as well involve distinct processes in the brain ( Longcamp et al., 2005 , 2006 ; Alonso, 2015 ). The process of cursive writing involves fine coordination of hand movements when producing the shape of each letter, whereas typewriting requires much less kinesthetic information ( Longcamp et al., 2006 ; Smoker et al., 2009 ; Kiefer et al., 2015 ). Several fMRI-studies, in preliterate ( James and Engelhardt, 2012 ) and preschool children (e.g., James, 2010 , 2017 ; Vinci-Booher et al., 2016 ), as well as adults ( Menon and Desmond, 2001 ; Longcamp et al., 2003 ), have shown that areas related to writing processes are also activated when simply perceiving visual letters, suggesting that writing and reading are interrelated processes including a sensorimotor component ( Longcamp et al., 2005 , 2006 ).

Even though several researchers have pointed to certain task-specific brain areas, recent findings in modern neuroscience suggest that the brain is not that simple. Neural processes are highly dynamic ( Lopes da Silva, 1991 ; Singer, 1993 ) and we still know very little about how the different brain systems are working together ( Buzsáki, 2006 ). As recent findings of cognitive neuroscience have found processes in the brain to occur every millisecond, the EEG technique lends itself well to studying brain electrical activity as a function of cursive writing, typewriting, and drawing. The EEG-technique allows us to investigate changes in the state of the underlying networks ( Lopes da Silva, 1991 ), and can reveal the continuously changing task-specific spatial patterns of activations ( Pfurtscheller et al., 1996 ). Studies of cortical oscillations have become a fundamental aspect of modern systems neuroscience, yet, there are still conflicting definitions regarding the different rhythms and their cognitive usefulness ( Fröhlich, 2016 ).

In general, brain oscillations are interactions between the thalamus and cortex and can be viewed as generated by changes in one or more parameters that control oscillations in neuronal networks ( Pfurtscheller and Lopes da Silva, 1999 ). The complex interactions and the following distinctive frequencies are, in short, reflecting different cognitive processes ( Klimesch et al., 1994 ; Berens and Horner, 2017 ). At the neural level, cortical oscillations have been found to reflect periodically membrane voltages that interact by synaptic transmission, reflecting a pattern of depolarization and hyperpolarization that enables or disables effective translation of incoming synaptic input into postsynaptic action potential firing ( Fröhlich, 2016 ). In other words, the frequencies of the following oscillations depend both on the individual neurons and the strength of the action potentials ( Lopes da Silva, 1991 ; Singer, 1993 ). This temporal organization of neural firing is of high importance and is also thought to be critical for the formation of long-term memories in the hippocampus ( Berens and Horner, 2017 ).

Frequency-specific changes in the ongoing EEG, that are not phase-locked to a specific event, can be observed in form of event-related synchronization (ERS) (an increase in spectral amplitude) or event-related desynchronization (ERD) (a decrease in spectral amplitude) ( Pfurtscheller and Aranibar, 1977 ; Pfurtscheller and Lopes da Silva, 1999 ). These longer-lasting ongoing changes can be detected using spectral analyses ( Klimesch, 1996 ), e.g., induced temporal spectral evolution (TSE), to study differences in a given frequency band ( Pfurtscheller et al., 1994 ; Salmelin and Hari, 1994 ). The TSE technique calculates temporal dynamics of EEG oscillations and quantifies both event-related suppressions and/or enhancements of rhythms after the original EEG-data have been inspected and filtered through specific filters ( Salmelin and Hari, 1994 ). Both ERD and ERS are highly frequency-specific and can be displayed in both the same or different locations on the scalp simultaneously ( Lopes da Silva, 1991 ; Pfurtscheller, 1992 ; Pfurtscheller et al., 1996 ; Pfurtscheller and Lopes da Silva, 1999 ).

In a recent EEG-study, Van der Meer and Van der Weel (2017) found that drawing by hand activates larger networks in the brain compared to typewriting, and concluded that the involvement of fine hand movements in note-taking, as opposed to simply pressing a key on a keyboard, may be more beneficial for learning, especially when encoding new information. They found a desynchronized activity within the alpha band in the parietal and occipital areas of the brain, suggesting this activity to be beneficial for learning, especially as the activity was shown to occur in the rather deep structures of the brain (e.g., hippocampus, the limbic system). Both handwriting and drawing are complex tasks that require integration of various skills ( Van der Meer and Van der Weel, 2017 ), and adults often use the same term to refer to young children’s writings and drawings ( Treiman and Yin, 2011 ). Both processes involve several visuomotor components and precise coordination ( Planton et al., 2017 ) to produce artificial marks that appear on a surface ( Treiman and Yin, 2011 ). As drawing can be said to be just as complex as handwriting, this activity is not used daily as an intensive learning strategy in the form of written productions ( Planton et al., 2017 ). Nevertheless, drawing may exhibit just as much higher-level processing as handwriting, if not more so, especially when it comes to creating creative drawings as opposed to writing standardized letters. Therefore, it would be interesting to investigate whether drawing and cursive writing engage similar or different activation patterns in the brain, and how they differ from typewriting on a keyboard based on the literature mentioned above.

As previous studies have found support for the benefits of note-taking by hand in terms of learning, the present study aimed to expand the findings by Van der Meer and Van der Weel (2017) , and further investigate the neurobiological differences in the adult and child brain related to cursive writing, typewriting, and drawing, using high-density EEG. It was hypothesized that handwriting and drawing would activate similar brain areas, in profound structures of the parietal lobe, to a greater extent than typewriting on a keyboard. Studying the adult brain state can provide valuable information ( Vinci-Booher et al., 2016 ), but investigating the stages that lead to the adult-like neural signatures can help us better understand cognitive development and why the brain responds to certain stimuli the way it does as a result of experience ( James, 2010 ). Therefore, the present study includes a group of 12-year-old children, in addition to adults, to investigate if the same activations are apparent as in the literate adult, and perhaps even more critical in terms of learning and initiation of essential neuronal structures in the brain. Hence, the present study aims to investigate the importance of teaching cursive writing in school and to further explore which strategies of cursive writing, typewriting, or drawing are more beneficial to facilitate and optimize learning in the classroom.

Materials and Methods

Participants.

Sixteen healthy school-aged children and sixteen healthy adults were recruited to participate in this study at the Developmental Neuroscience Laboratory at NTNU (Norwegian University of Science and Technology). The study followed a cross-sectional design to study differences in oscillatory brain activity in tasks of cursive writing, typewriting, and drawing among children and adults. The school-aged children were recruited from 7th graders at the Waldorf school in Trondheim, who are very used to cursive handwriting and drawing. Interested parents contacted the lab for further information about their child’s participation. The adults were recruited through different lectures at the university campus, or they were contacted through friends. All participants were right-handed, as determined by the Edinburgh Handedness Inventory ( Oldfield, 1971 ). Only right-handed participants with a handedness quotient larger or equal to +0.6 took part in the study, ranging from lowest to highest, 0.65–0.93 in adults and 0.60–1.00 in children, respectively. Four of the children were removed from further analysis due to inadequate data or other information that could affect the data analyses (e.g., dyslexia, ADHD, or prematurity). In addition, four of the adults were removed due to inadequate data and to maintain equal sized groups. Because of this, the resulting total sample included 12 school-aged children and 12 young adults.

For the school-aged children (four boys and eight girls), the mean age was 11.83 years ( SD = 0.39). Parents gave their informed consent concerning their children, and the child could withdraw from the experiment at any time without any consequences. For the adults (six men and six women), the mean age was 23.58 years ( SD = 2.02). The adults also gave their informed consent and could withdraw at any time. The adults were rewarded with a 150 NOK cinema ticket, whereas the school-aged children were rewarded with snacks in the lab and a picture of themselves with the EEG-net on. The Regional Committee for Medical and Health Ethics approved the study.

Experimental Stimuli and Paradigm

Psychological software tool, E-prime 2.0, was used to generate 15 different Pictionary words on a separate Microsoft Surface Studio. The participants used a digital pen to write in cursive by hand and draw directly on the touch screen, and a keyboard to typewrite the presented words. The screen measured 25.1″ × 17.3″ × 0.5″ and had a screen resolution of 4500 × 3000 (192 PPI) pixels.

The experiment included a total of 45 trials, where each word was presented in three different conditions, represented in a semi-randomized order. The 15 words varied in difficulty, from concrete words, such as “shoe,” to more abstract words, such as “birthday.” For each trial, participants were instructed to either (a) write in cursive the presented word with a digital pen directly on the screen, (b) type the presented word using the right index finger on the keyboard, or (c) draw the presented word by freehand with a digital pen directly on the screen. Whereas handwriting and typewriting were both relatively simple transcription tasks, drawing included higher-level processing (ideation). Before each trial, an instruction appeared 1–2 s before one of the 15 target words appeared, and the participants were given 25 s to either handwrite, type, or draw the word. EEG data were recorded only during the first 5 s of each trial. The participants could draw and write wherever they preferred directly on the screen. The words that were typed were the only words that did not appear on the screen while the participant was typewriting. A small sound indicated that the current trial was over and a new one was about to start. The drawings and writings produced by the participants were stored for offline analyses (see Figure 1 ).

Figure 1. Example of writings and drawings of (A) 12-year-old boy and (B) 23-year-old female student. Figure is reproduced using x,y-coordinates over time from the touchscreen.

EEG Data Acquisition

An EEG Geodesic Sensor Net (GSN) ( Tucker, 1993 ; Tucker et al., 1994 ) with 256 evenly distributed sensors was used to record EEG activity from the participant’s scalp. The signals were amplified using a high-input EGI amplifier, at maximum impedance at 50 kΩ to ensure optimal signal-to-noise ratio ( Picton et al., 2000 ; Ferree et al., 2001 ). The amplified signals were recorded by Net Station software with a sample rate of 500 Hz. All data were stored for further off-line analyses.

Participants usually arrived several minutes prior to the experiment. On arrival, a consent form with all necessary information was given to the participants to sign. For the children, both the parent and the child signed the consent form. The participant’s head was measured to find the correct size for the net. While the participant completed the Edinburgh Handedness Inventory ( Oldfield, 1971 ), the net was soaked in a saline electrolyte for 15 min to optimize electrical conductivity. After being partially dried from the soaking, the net was mounted on the participant’s head. Next, the participant was moved to the experimental room where further information regarding the experiment was given. The experimental room was separated from the control room, where two assistants operated the computers necessary for data acquisition. The participant was sitting comfortably in an adjustable chair in front of a table with two levels, to minimize unnecessary movement in between trials that could cause artifacts in the data. A pillow was used to avoid tension in the back, and the table with the screen (on the second level) was placed as close as possible to the participant. A keyboard was further placed (on the nearest level) in a preferred position for the participant, and a digital pen was used for writing and drawing on the screen. The participants were asked to support their elbow to minimize hand movements in the trials using the pen. In addition, they were asked to sit as still as possible, while at the same time trying to perform the tasks as naturally as possible. The EEG-net was connected to the amplifier and the impedance of the electrodes was checked. Electrode connectivity could be improved by either adjusting their position or by adding additional saline electrolyte for better contact.

A pre-test was completed before the experiment where one of the assistants was present in the room. During this test, the participants could ask questions if needed, and necessary adjustments could be made. The pre-test included one example of each experimental condition, using a word not included in the actual experiment. The experiment started immediately after the pre-test was finished, the impedance was approved, and the participant was ready.

Two experiments were conducted at the same time, with a total of six different conditions, resulting in a total of 90 trials. In order to tap into the neural underpinnings of creative processes, the additional conditions in the separate experiment included (d) describe the presented word with a digital pen directly on the screen (e), copy the presented sentence with a digital pen directly on the screen, and (f) draw a copy of the presented drawing with a digital pen directly on the screen. However, the focus of the present paper was on comparing neuronal oscillations during the paradigm tasks of handwriting, typewriting, and drawing. Data acquisition was carried out in two blocks (45 trials in each) and lasted for about 45 min. Between the two blocks, the participants were given a pause where they could drink water and have a break from the screen. A pause was also initiated if the participant was moving a lot or appeared nervous, to remind the participant to relax and sit as still as possible. Further, the participants were told to knock on the window, separating the experimental room and control room, if they needed additional breaks or had any questions during the experiment.

Data Pre-analyses

Brain Electrical Source Analysis (BESA) research software version 7.0 was used to analyze the EEG data. Recordings were segmented using Net Station software and then exported as raw files with the appropriate auxiliary files attached, prior to the analyses in BESA. Average epoch was set to −250 to 4500 ms with a baseline definition of −250 to 0 ms. Low cut-off filter was set to 1.6 Hz to remove slow drift in the data, while the high cut-off filter was set to 75 Hz. The notch filter was set to 50 Hz to avoid line interference in the data.

Artifact contaminated channels, caused by head or body movements, were either removed or interpolated using spherical spline interpolation ( Perrin et al., 1989 ; Picton et al., 2000 ). A maximum limit of 10% of the channels could be defined as bad. When scanning for artifacts, threshold values for gradient, low signal, and maximum amplitude were set to 75, 0.1, and 200 μV, respectively. Manual artifact correction was applied to separate important brain activity from artifacts using manual and semi-automatic artifact correction with fitting spatial filters ( Berg and Scherg, 1994 ; Ille et al., 2002 ; Fujioka et al., 2011 ). When it was not possible to apply manual artifact correction, an automatic artifact correction (with values 150 μV for horizontal and 250 μV for vertical electrooculogram amplitude thresholds) was applied to explain artifact topographies by principal component analysis (PCA) ( Ille et al., 2002 ).

For the school-aged children, the mean numbers of accepted trials were 11 ( SD = 1.63) for handwriting, 9.67 ( SD = 2.74) for typewriting, and 12.08 ( SD = 1.89) for drawing, respectively. For the adults, the mean numbers of accepted trials were 14.33 ( SD = 0.98) for handwriting, 13.42 ( SD = 1.24) for typewriting, and 14.08 ( SD = 1.56) for drawing, respectively. After all the data were sufficiently artifact-free, time-frequency analysis in brain space was performed.

Time-Frequency Analysis in Brain Space

Time-frequency analysis in brain space was conducted for analysis of oscillatory activity, using multiple source dipoles that modeled the main brain regions of interest (see Figure 2 ). As the EEG-technique measures voltage changes at the scalp around dipoles, the orientations of these dipoles are essential as they provide the specific distribution of an EEG-activity ( Luck, 2005 ; Fröhlich, 2016 ). Measuring oscillatory activity directly on scalp surface electrodes may not be ideal, due to mixed brain source contributions and wide distribution of focal brain activity on the scalp surface caused by the nature of dipole fields and the smearing effect of volume conduction in EEG. Therefore, optimal separation of brain activity was achieved using source montages derived from a multiple source model where waveforms separated different brain activities ( Scherg and Berg, 1991 ). The multiple source model transforms the recorded data from sensor level into brain source space and provides source waveforms that can be used as a direct measure for the activity in the brain regions of interest on a single trial basis ( Hoechstetter et al., 2004 ). A discrete multiple source modeling was used for the time-frequency transformation. This model is created from averaged ERP data and/or sources in the brain regions of interest and is used to create an inverse spatial filter, i.e., a source montage that separates the different brain activities. The source model is then used to calculate a source montage and the source waveforms of the single trials. The regional sources of interest included the frontal, central, temporal, parietal, and occipital areas (see Figure 2 ). Using the procedure of multiple source model, it is possible to separate the time-frequency content of different brain regions even if their activities severely overlap at the surface of the scalp ( Hoechstetter et al., 2004 ).

Figure 2. Head model of a typical 12-year-old boy. The model shows four dipoles (with location and direction of electrical current) in regional sources of interest, over frontal, central, temporal parietal, as well as occipital areas.

A 4-shell ellipsoidal head model ( Berg and Scherg, 1994 ; Hoechstetter et al., 2004 ), was used to analyze the sources of interest of the young adults after loading the artifact-corrected coordinate files. The values for bone thickness and conductivity were set to 7.0 and 0.0042 mm (default values in BESA), respectively. For the 12-year-old children, age-appropriate template models were set to 12 years for realistic templates for source analysis.

The time-domain signal was transformed into the time-frequency domain by selecting a certain temporal resolution using complex demodulation ( Papp and Ktonas, 1976 ). The time-frequency displays, representing changes in amplitude over time (TSE, temporal spectral evolution), were generated from each single trial by averaging spectral density amplitudes over trials such that each graph displayed, plotted the spectral amplitude density of one montage channel over time and frequency which were normalized to the baseline for each frequency ( Pfurtscheller et al., 1994 , 1996 ; Hoechstetter et al., 2004 ). Average evoked response signals were subtracted to focus only on induced (instead of evoked) brain activity before computing the TSE ( Pfurtscheller et al., 1994 ; Handy, 2005 ).

A time-frequency display is shown where the power/amplitude for each time is normalized to the mean power/amplitude of the baseline epoch for that frequency. The x-axis shows the time relative to the event, the y-axis shows the frequencies. The intensities are displayed as a color-coded plot. The resulting value is computed as:

with A( t , f ) = activity at time t and frequency f (either power or absolute amplitude) and A baseline ( f ) = mean activity at frequency f over the baseline epoch. The TSE value is in the range from [−100%, + ∞] and describes the spectral change of activity at sampling time t relative to the activity during the baseline epoch. A value of +100% means that activity is twice as high as during the baseline epoch.

Comparisons between the three conditions handwriting, typewriting, and drawing were computed for each participant with time-frequency displays (changes in amplitude over time). TSE displays were limited between frequency cut-offs of 4–60 Hz, while frequency and time sampling were set at 1 Hz and 50 ms.

Statistical Analyses

Probability of significance in amplitude values and frequency ranges between each of the three conditions was tested with BESA Statistics 2.0. Using this program, average TSE statistics for each participant could be computed to use these significant time-frequency ranges as guides in finding maximum oscillatory activity in the individual TSEs. To address the multiple comparisons problem, a combination of permutation tests and data clustering was employed in the statistical test. Data clusters that showed a significant effect between conditions were assigned initial cluster values. Using both between-groups and within-group ANOVA’s, these initial cluster values were passed through permutation and assigned new clusters so that the significance of the initial clusters could be determined. A Bonferroni correction was used to adjust for multiple comparisons ( Simes, 1986 ). Cluster alpha (the significance level for building clusters in time and/or frequency) was set at 0.01, and the number of permutations was set at 10.000. Low- and high cut-offs for frequency were kept at 4 and 60 Hz, and epochs were set from −250 to 4500 ms. post-hoc tests were run to test for statistical differences between the three conditions and two age groups.

Individual Time-Frequency Responses

Figures 3 , 4 display the results of individual TSE (temporal spectral evolution) maps of brain regions of interest for the three experimental conditions handwriting, typewriting, and drawing, for a typical adult and child participant. Brain regions of interest included frontal, temporal, parietal, central as well as occipital areas, in frequencies from theta (4 Hz) and up to gamma (60 Hz) range. The signal magnitude (amplitude%) reflects estimated neural activity in the various brain regions compared to baseline (−250 to 0 ms) activity. Increased spectral amplitude [induced synchronized activity, event-related synchronization, (ERS)] is shown as red-colored contours and decreased spectral amplitude [induced desynchronized activity, event-related desynchronization (ERD)], is shown as blue-colored contours.

Figure 3. Individual time-frequency displays of a typical male adult. The y-axes display frequencies from 4 to 60 Hz. The x-axes display the time interval from baseline to 4500 ms of recordings of the trial. The signal magnitude (amplitude%) reflects the estimated neural activity in the various brain regions during the experimental conditions compared to baseline activity (−250 to 0 ms). Event-related synchronization (ERS) is shown as red-colored contours, more prominent in lower frequencies (theta 4–8 Hz) for handwriting and drawing and higher frequencies (beta 12–30 Hz and gamma >30) for typing. Event-related desynchronization (ERD) is shown as blue-colored contours, more prominent in higher frequencies (beta 12–30 Hz and gamma >30) for handwriting and drawing and lower frequencies (theta 4–8 Hz) for typing. Brain areas included the following frontal, temporal, central, parietal and occipital areas: FpM, fronto-polar midline; FL, frontal left; FM, frontal midline; FR, frontal right; TAL, temporal anterior left; TAR, temporal anterior right; TPL, temporal posterior left; TPR, temporal posterior right; CL, central left; CM, central midline; CR, central right; PL, parietal left; PM, parietal midline; PR, parietal right; OpM, occipito-polar midline.

Figure 4. Individual time-frequency displays of a typical 12-year-old girl, in frontal, temporal, central, parietal and occipital areas. The y-axes display frequencies from 4 to 60 Hz. The x-axes display the time interval from baseline to 4500 ms of recordings of the trial. The signal magnitude (amplitude%) reflects the estimated neural activity in the various brain regions during the experimental conditions compared to baseline activity (−250 to 0 ms). Event-related synchronization (ERS) is shown as red-colored contours and event-related desynchronization (ERD) is shown as blue-colored contours, showing the same activation patterns as for the adult in Figure 3 .

In the parietal and central areas, event-related synchronization (ERS) was more prominent in lower frequencies (theta 4–8 Hz) for handwriting and drawing, as opposed to in higher frequencies (beta 12–30 Hz, and gamma > 30 Hz) for typewriting. For handwriting, this activity appeared around 500–1000 ms and lasted throughout the trial in both adults and adolescents. For drawing, however, this activity appeared around 500 ms and lasted, though to a lesser extent, throughout the trial in the adults, as opposed to the children, where it appeared around 1000 ms and lasted consistently throughout the trial. For typewriting, this activity appeared to vary from 0 to 500 ms in both beta (12–30 Hz) and gamma (>30 Hz) frequencies in both adults and children. As for event-related desynchronization (ERD), this activity was more prominent in higher frequencies (beta 12–30 Hz, and gamma > 30 Hz) for handwriting and drawing and in lower frequencies (theta 4–8 Hz and, to a lesser extent, alpha 8–12 Hz) for typewriting. For handwriting and drawing in both groups, ERD activity appeared around 0 ms and lasted throughout the trial. In contrast, for typewriting, it appeared around 1000 ms and lasted throughout the trial for adults, whereas for children the activity was more variable and took place from 500 to 1500 ms. Figures 3 , 4 show the individual TSE maps of the brain regions of interest in a typical adult and child, respectively. These patterns were largely consistent among the participants in both groups.

Main Effects and post-hoc Analyses

Statistical analyses were run to test for statistical differences between the conditions and groups. Tables 1 , 2 display the detailed main effects (within-group ANOVA) of the permutation results (of clusters where the null hypothesis is rejected, i.e., data are not interchangeable) of the adults and children, respectively. These results revealed 10 and 4 significant clusters for the adults and the children, respectively.

Table 1. Permutation test of adult results for 10 significant clusters in decreasing order.

Table 2. Permutation test of child results for four significant clusters in decreasing order.

The post-hoc tests revealed significant differences in oscillatory activity primarily in the alpha (8–12 Hz) and theta (4–8 Hz) band between handwriting, typewriting, and drawing among both age groups. As the differences between typewriting and drawing, in both children and adults, were similar to the differences between typewriting and handwriting, only the statistical differences between typewriting and handwriting, and handwriting and drawing in the adults are reported here. Further investigations of the parietal and central brain areas in both age groups were conducted to study the various brain activation patterns of the different learning strategies. Figures 5 , 6 display the post-hoc results of the permutation tests in the adults between handwriting and typewriting, and between handwriting and drawing, respectively. When handwriting was compared to typewriting, the permutation results showed three significant positive clusters (in black), in the parietal right (PR), parietal midline (PM), and parietal left (PL) areas (see Figure 5 ). When handwriting was compared to drawing, the results showed one significant positive cluster (in black), in the central medial (CM) area (see Figure 6 ). These positive clusters suggest separate processes (differences in band power) between handwriting and typewriting in the parietal areas, as well as separate processes between handwriting and drawing in the central midline area.

Figure 5. Head model (nose up) with average significant (* p < 0.05) data clusters in the various sources of interest when handwriting is compared to typewriting in all adults. Three significant clusters (marked in black) were found in the parietal left (PL), parietal midline (PM), and parietal right (PR). For handwriting, an event-related synchronized activity in the theta (4–8 Hz) range is apparent in parietal, central, occipital, as well as in frontal areas. Event-related desynchronization is apparent in the beta (12–30 Hz) and gamma (>30 Hz) range in the central and frontal areas.

Figure 6. Head model (nose up) with average significant (* p < 0.05) data clusters in the various sources of interest when drawing is compared to handwriting in all adults. One significant cluster (marked in black) was found in the central midline (CM). For drawing, areas in the parietal and central regions are dominated by a desynchronized activity in the alpha (8–12 Hz) and beta (12–30 Hz) range. In addition, event-related synchronization is apparent in the theta (4–8 Hz) range in the parietal midline (PM).

The significant clusters of differences in band power were found mainly in the parietal and central regions. The parietal areas of the brain have been associated with cognitive processing of language and mechanisms for attention (e.g., Pfurtscheller et al., 1994 ; Brownsett and Wise, 2010 ; Benedek et al., 2014 ), whereas the central areas are influenced by the somatosensory cortex (e.g., Velasques et al., 2007 ). Therefore, these areas were chosen to further focus on the underlying brain electrical activity as a function of handwriting, typewriting, and drawing. Additionally, the potential deep structures of the brain, that may have their beneficial effects on learning ( Van der Meer and Van der Weel, 2017 ), may be found in these areas.

Figure 7 displays the average of all participants for handwriting, typewriting, and drawing in adults (see Figure 7A ) and children (see Figure 7B ) in the central and parietal brain regions of interest. For adults, handwriting appeared to be dominated by an event-related synchronization (ERS) (red areas) in the theta (4–8 Hz) range, in addition to an event-related desynchronization (ERD) activity in the beta (12–30 Hz) and gamma (>30) range. The theta activity appeared around 1000 ms and lasted throughout the trial. Contrary to handwriting, typewriting appeared to be dominated by an event-related desynchronized (ERD) (blue areas) activity in the theta (4–8 Hz) range and, to a lesser extent, in the alpha (8–12 Hz) range. This activity appeared around 1500 ms and lasted throughout the trial. In drawing, a synchronized theta (4–8 Hz) activity was apparent in the parietal midline (PM) and the parietal right (PR), in addition to a desynchronized alpha (8–12 Hz) and beta (12–30 Hz) range activity from around 500 ms and throughout the trial (see Figure 7A ).

Figure 7. Average results of all participants for typewriting, handwriting, and drawing in (A) adults and (B) children, in the parietal and central regions: PM, parietal midline; PR, parietal right; PL, parietal left; CM, central midline. For the adults, these areas showed event-related synchronization (ERS) in the theta (4–8 Hz) range for handwriting and event-related desynchronization (ERD) activity in the theta (4–8 Hz) and, to a lesser extent, in the alpha (8–12 Hz) range for typewriting. For drawing, event-related synchronization (ERS) was apparent in the theta (4–8) range in parietal midline as for handwriting. In addition, event-related desynchronization (ERD) activity was apparent in the alpha (8–12 Hz) and beta (12–30 Hz) range. The same patterns were observed, though to a lesser extent, in the children.

The same tendencies could be observed for the children, but they were less evident compared to the adults (see Figure 7B ). For the children, desynchronized and synchronized theta (4–8 Hz) range activity was also apparent in typewriting and to a lesser extent in handwriting, respectively. In drawing, synchronized theta (4–8 Hz) range activity was also apparent, yet to a smaller degree, in parietal midline (PM) and parietal right (PR). In addition, a desynchronized activity appeared to dominate in the gamma (>30 Hz) range in handwriting for the children.

The aim of the current study was to further investigate brain electrical activity as a function of handwriting, typewriting, and drawing using high-density EEG in 12-year-old adolescents and adults. Fifteen different words, varying in task difficulty, were visually presented on a screen and the participants used a digital pen to write and draw directly on the touch screen, and a keyboard to type the presented words. Whereas handwriting and typewriting were both relatively simple transcription tasks, drawing included higher-level processing. TSE analyses were performed to explore underlying differences in brain oscillatory activity when participants were using a keyboard vs. a pen. In addition, the present study aimed to explore if drawing and cursive writing are activating similar or different processes within the brain. Regional sources of interest included frontal, temporal, parietal, central as well as occipital areas, in frequencies from theta (4 Hz) and up to gamma (60 Hz) range. Induced desynchronization is often taken to be an electrophysiological correlate of activated cortical areas involved in the processing of perceptual or cognitive information, or in the production of motor behavior ( Pfurtscheller, 1992 ). To focus on oscillatory brain activity in specific frequency bands that has shown to have beneficial effects on learning and memory ( Pfurtscheller and Lopes da Silva, 1999 ), the parietal and central areas were further investigated. These areas have also been associated with cognitive processes in visual perception (e.g., Pfurtscheller et al., 1994 ; Vilhelmsen et al., 2019 ) and language (e.g., Brownsett and Wise, 2010 ; Benedek et al., 2014 ) as well as to be influenced by sensorimotor cortex (e.g., Velasques et al., 2007 ).

TSE – Individual Analyses

The present findings revealed differences in oscillatory activity between handwriting, typewriting, and drawing for both children and adults. By visually reviewing the individual TSE analyses of a typical participant in both groups, these differences are shown as changes in band power (increase or decrease in spectral amplitude) between handwriting, typewriting, and drawing, apparently representing different sensorimotor processes within the brain. However, there seem to be more similarities between handwriting and drawing, compared to typewriting, despite differences in task difficulties, thus supporting the study by Van der Meer and Van der Weel (2017) .

Synchronized Theta Activity in Parietal and Central Areas in Handwriting

Event-related synchronization within the theta (4–8 Hz) band has been found to correlate with working memory performance and the ability to encode new information ( Klimesch et al., 1994 , 1996 , 2001 ; Klimesch, 1999 ; Raghavachari et al., 2001 ; Clouter et al., 2017 ). Therefore, our findings seem to support the potential benefits of handwriting activity for learning. Although the handwriting task in the present study was a relatively simple transcription task, it was still evident that the observed oscillatory brain activity is present whenever the specific sensory-motor movements involved in handwriting practices are included. Even though participants did not take personal notes from a lecture as in a natural classroom environment, it still seems this type of oscillatory activity in the brain is present when writing letters by hand or when drawing, as opposed to when simply pressing a key on the keyboard. Klimesch et al. (1994) have also proposed that hippocampal activity is reflected within the theta band and shown as synchronized theta band power. However, this activity can be difficult to pick up with EEG, yet it is likely that the present activity stems from the rather deep structures of the brain (e.g., hippocampus and the limbic system) and adds further support for handwriting and its relation to optimized learning.

Moreover, Bland and Oddie (2001) have found support for synchronized theta activity in mechanisms underlying sensorimotor integration. Although the present study does not replicate the desynchronized activity in the alpha band found by Van der Meer and Van der Weel (2017) , it still supports their findings because both ERS and ERD are highly frequency-specific, i.e., the alpha and theta band respond in different and opposite ways ( Pfurtscheller et al., 1996 ; Pfurtscheller and Lopes da Silva, 1999 ). In terms of cognitive effort, where the alpha band desynchronizes, the theta band synchronizes. Therefore, theta synchronization may indicate that different neural generators are involved, as with alpha desynchronization ( Klimesch et al., 1994 ; Klimesch, 1999 ). Thus, our findings corroborate the findings by Van der Meer and Van der Weel (2017) , but in a different frequency band. However, whereas alpha desynchronization is highly task-specific and correlates with (semantic) long-term memory performance, theta synchronization correlates with working memory performance and the ability to encode new information ( Klimesch et al., 1994 , 1996 , 2001 ; Klimesch, 1999 ; Clouter et al., 2017 ).

Lower frequencies are ideal for enabling communication over longer distances in the brain. Several studies have found support for lower frequencies to “gate” the occurrence of faster oscillations, e.g., theta (4–8 Hz) oscillation in humans often gates the gamma (>30 Hz) oscillation ( Canolty et al., 2006 ). For handwriting, especially in the individual TSE-analyses, a desynchronized gamma (>30 Hz) activity was apparent together with the synchronized theta (4–8 Hz) activity (see Figures 3 , 4 ). In general, gamma oscillations appear to be underlying mechanisms of neural coding ( Singer, 1993 ), and this theta-to-gamma cross-frequency coupling seems to be related to studies finding gamma networks to desynchronize and theta networks to synchronize during encoding, retrieval ( Solomon et al., 2017 ), as well as during episodic memory formation ( Burke et al., 2013 ). Solomon et al. (2017) have also suggested low-frequency oscillations to be essential for interregional communication in the human brain. However, other studies (e.g., Osipova et al., 2006 ), have found synchronized activity in both theta and gamma bands, thereby indicating that further research of this coupling is needed. Also, because of the broad definition of the gamma frequency (30–100 Hz), the present study only observed a small portion of the gamma band.

Desynchronized Theta Activity in Parietal and Central Areas in Typewriting

Conversely, for typewriting, a desynchronized activity was evident in the theta (4–8 Hz) and, to a lesser extent, in the alpha (8–12 Hz) range. The lower alpha (8–10 Hz) range has been found to reflect non-task related cognitive processes, such as expectancy, lower attention, and alertness ( Klimesch et al., 1992 , 1994 ; Klimesch, 1999 ). Therefore, this finding could reflect the focus in finding the correct keys on the keyboard, typewriting with the index finger only, and not seeing the output appearing on the screen. The fact that the words produced by the participants did not appear on the screen may have affected the participants’ attention in trying to write as correctly as possible. Typewriting with only the index finger may also have been unfamiliar and could have contributed to the need for increased attention.

The finding of desynchronized activity in the upper alpha (10–12 Hz) range, on the other hand, has been found to correlate with increasing task demands ( Boiten et al., 1992 ). Within the alpha band, a desynchronization seems to imply that the oscillators within the band are no longer coupled and start to oscillate with different frequencies ( Klimesch, 1999 ), implying that more areas of the brain are activated and multiple processes are occurring ( Basar et al., 2001 ). However, the desynchronized activity within the upper alpha (10–12 Hz) band observed here is apparent to a lesser extent, and is most likely due to increased attention and task demand because of the unfamiliar movements when typewriting with the index finger only. An alternative interpretation of this rhythm could also be the movement mu (8–12 Hz) rhythm. This rhythm appears to desynchronize during movement ( Cruikshank et al., 2012 ). Whereas the participants were resting their elbow in the drawing and handwriting condition, thereby effectively reducing movement, more arm movements were present when they used the keyboard. However, since the theta, alpha and mu rhythms are nearby in frequencies, they may be difficult to distinguish from each other. Therefore, its relation to learning remains unclear.

Different and Similar Activation Patterns in Handwriting and Drawing

The results reported above suggest that handwriting and drawing, just like typewriting and handwriting, are two separate processes within the brain. However, the neural processes involved in handwriting and drawing seem to be more similar to each other compared to typewriting. Our findings therefore both corroborate and extend the findings of Van der Meer and Van der Weel (2017) . Compared to handwriting, drawing exhibited a desynchronized alpha (8–10 Hz) and beta (12–30 Hz) range activity. These findings suggest an increase in cognitive effort and attentive information processing ( Lopes da Silva, 1991 ; Boiten et al., 1992 ), as well as the inclusion of motor actions ( Pfurtscheller et al., 1996 ), most likely related to higher-level processing during the ideation phase when participants are figuring out exactly what to draw. In addition, the synchronized theta (4–8 Hz) band activity found in handwriting was also apparent in certain areas of the parietal regions. Therefore, as with handwriting, drawing seems to facilitate learning to encode new information. The synchronized theta band activity in the parietal regions seems to be activated both when producing letters by hand and when creating creative drawings.

Using a meta-analysis of brain imaging studies, Yuan and Brown (2015) suggested that handwriting and drawing might employ the same underlying sensorimotor networks, but that some differences exist between them in the parietal areas. The reason for this difference may not be surprising, considering the extensive involvement of language and letters in writing ( Treiman and Yin, 2011 ), which drawing appears to lack. Although the present study only found a significant cluster in the central areas differentiating between handwriting and drawing, the average results clearly showed underlying differences in oscillatory activity in the parietal areas as well, especially in the alpha (8–10 Hz) and beta (12–30 Hz) range. The observed brain processes involved in handwriting and drawing seem to support the notion that both employ the same underlying sensorimotor networks.

As for the children, the same tendencies between handwriting, typewriting, and drawing could be observed, but they were far less evident compared to the adults. The reason for these less evident activation patterns could be due to more artifact-contaminated data in the children, resulting in fewer trials. EEG is particularly sensitive to movement, and young children are prone to movements. An alternative interpretation of these results may be that the oscillatory frequency rhythms observed in the adults, are not yet fully developed at the age of 12 years (e.g., Krause et al., 2001 ).

However, due to the observed tendencies, it seems likely that the differences observed in adults, also are of importance for children, if not more so. The specific type of experience may cause the neural changes associated with learning. Thus, handwriting might support the development of these activation patterns in achieving the neural specificity in the brain, including the synchronized theta activity and theta-to-gamma frequency coupling found in the present study. As children continue to improve their language and writing skills throughout adolescence, it is possible that these mechanisms are not yet fully developed at 12 years of age ( Krause et al., 2001 ). Moreover, memory systems involving retrieval might be the last to mature within the brain, suggesting that further research within this field is necessary ( Schneider et al., 2016 ). However, our findings still provide support for handwriting practice providing beneficial neuronal activation patterns for learning. Therefore, maintaining the handwriting skill in school for optimal development seems to be of high importance.

The Importance of Handwriting Practice in a Learning Environment

Whenever self-generated movements are included as a learning strategy, more of the brain gets stimulated, which results in the formation of more complex neural networks ( Van der Meer and Van der Weel, 2017 ). It also appears that the movements related to keyboard typing do not activate these networks the same way that drawing and handwriting do. Besides, when a child produces individual handwritten letters, the results will be highly variable, leading to a better understanding ( Li and James, 2016 ; James, 2017 ). The simultaneous spatiotemporal pattern from vision, motor commands, and kinesthetic feedback provided through fine hand movements, is not apparent in typewriting, where only a single button press is required to produce the complete desired form ( Longcamp et al., 2006 ; James, 2010 ; Vinci-Booher et al., 2016 ). Therefore, the ongoing replacement of handwriting by keyboard-writing may in some respects seem ill-advised as this appears to negatively affect the learning process ( Alonso, 2015 ; Mangen and Balsvik, 2016 ). The present findings suggest that the delicate and precisely controlled movements involved in handwriting contribute to the brain’s activation patterns related to learning. We found no evidence of such activation patterns when using a keyboard.

Although it is vital to maintain handwriting practice in school, it is also important to keep up in the continuously developing digital world. Young children should learn to write by hand successfully, and, at the same time learn to manage to write on a keyboard (e.g., learn the touch method and transcribe information fast), depending on the context. The present study shows that the underlying brain electrical activity related to handwriting, typewriting, and drawing is different. Hence, being aware of when to use which strategy is vital, whether it is to learn new conceptual materials or to write long essays. Even though there are underlying differences in the three strategies, it is important to note that the strategies are all cognitive tasks, each serving their own benefits.

With increasing technological development, it is vital that educators routinely evaluate the influences of learning environments ( Stacy and Cain, 2015 ) for long term implications. It is important to note that the present study did not attempt to suggest that we should prohibit digital devices in the classroom and go back to traditional handwriting in all levels of education. Instead, the purpose was to shed light on the topic and create awareness of which learning tradition has the best effect in what context. When using technological advances, it is important to ensure that handwriting practice remains a central activity in early letter learning, regardless if this occurs with a stylus and tablet or traditional paper and pencil ( Vinci-Booher et al., 2016 ). As digital note-taking has undergone a vast transition, using a digital format today still allows the individual to handwrite notes, add drawings, and highlight text ( Stacy and Cain, 2015 ). Therefore, the benefits from both writing methods can be implemented, and both students and teachers should be conscious of when to use which method. Moreover, learners will also vary in ability, which may affect which learning activities stimulate the use and/or effectiveness of cognitive processes ( Arnold et al., 2017 ).

In conclusion, as Van der Meer and Van der Weel (2017) found evidence for a clear difference in underlying electrical brain activity between typewriting and drawing, this study adds to this knowledge, by showing that typewriting, cursive handwriting, and drawing are each different processes. Nonetheless, handwriting and drawing seem to be more alike compared to typewriting. Therefore, an optimal learning environment needs to include the best from all disciplines, considering the strengths and support each of them offer. This way, both cognitive development and learning efficiency can be strengthened, and pupils and students of all ages and their teachers can keep up with the technological development and digital challenges to come.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researcher.

Ethics Statement

The studies involving human participants were reviewed and approved by the Norwegian Regional Ethics Committee (Central Norway). The participants (legal guardian/next of kin) provided written informed consent to participate in this study.

Author Contributions

EO, FW, and AM contributed equally to the conception, design, analyses and write-up of the work, and were accountable for all aspects of the research. All authors contributed to the article and approved the submitted version.

We received funds for open access publication fees from the NTNU.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We would like to thank Elisabeth Deilhaug and Stefania Rasulo for their help with recruitment and testing of participants, and Kenneth Vilhelmsen, Seth Agyei, and Regine Slinning for their discussions and help with the analyses.

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Keywords : high-density electroencephalography, cursive handwriting, typewriting, temporal spectral evolution, digital era, learning in the brain, educational psychology

Citation: Ose Askvik E, van der Weel FR and van der Meer ALH (2020) The Importance of Cursive Handwriting Over Typewriting for Learning in the Classroom: A High-Density EEG Study of 12-Year-Old Children and Young Adults. Front. Psychol. 11:1810. doi: 10.3389/fpsyg.2020.01810

Received: 08 April 2020; Accepted: 30 June 2020; Published: 28 July 2020.

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Copyright © 2020 Ose Askvik, van der Weel and van der Meer. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Audrey L. H. van der Meer, [email protected]

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