Does handwriting on a tablet screen affect students’ graphomotor execution? A comparison between Grades Two and Nine

Human Movement Science 44 (2015) 32–41

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Human Movement Science journal homepage: www.elsevier.com/locate/humov

Does handwriting on a tablet screen affect students’ graphomotor execution? A comparison between Grades Two and Nine Denis Alamargot a,⇑, Marie-France Morin b a

Laboratoire Cognitions Humaine et Artificielle (CHArt-UPEC), Université de Paris Est-Créteil, Paris, France Chaire de Recherche sur l’Apprentissage de la Lecture et de l’ECriture chez le jeune enfant (CREALEC), Faculté d’Education, Université de Sherbrooke, Québec, Canada b

a r t i c l e

i n f o

Article history: Received 16 May 2015 Revised 12 August 2015 Accepted 17 August 2015

Keywords: Handwriting Digital tablet Graphomotor execution Movement kinematics Writing development

a b s t r a c t We sought to ascertain how handwriting with a plastic-tipped pen on the screen of a digital tablet affects graphomotor execution in students, compared with handwriting on paper with a ballpoint pen. We predicted that the modification to propriokinesthetic feedback induced by the screen/plastic tip combination would differently disturb younger and older students, who rely on perceptual feedback either to form letters (former) or to adjust movement execution (latter). Twenty-eight students from Grades Two and Nine were asked to handwrite the alphabet and their names and surnames under the two conditions. Kinematics were recorded using the tablet, controlled by Eye and Pen software. Results showed that handwriting on the tablet surface with a plastic-tipped pen primarily affected pen pauses in the second graders and pen movements in the ninth graders, suggesting a disturbance in segment trajectory calculation in the younger participants and reduced control of muscular adjustment in the older children. Ó 2015 Elsevier B.V. All rights reserved.

1. Introduction 1.1. Writing and new technologies The advent of new technologies in schools means that students are now having to write with different tools in different media, including keyboards, virtual keyboards (tablets), and pen or fingers on a tablet surface, and no longer just with pen/ pencil on paper. While this new technological reality may arouse fresh interest in writing (Clark & Dugdale, 2009; Karsenti & Collin, 2013), it does not necessarily make the activity itself any easier. For example, keyboarding is less efficient than handwriting in at least three areas (for a summary, see Caporossi & Alamargot, 2014; Mangen & Velay, 2010; Matthewman & Triggs, 2004). (i) Keyboarding requires frequent shifts of attention between the screen and the keyboard, an aspect that does not exist in handwriting. In addition, with handwriting, the text is produced at the very place where the motor action is performed, so the writer can simultaneously consider the letter’s formation and its textual context (Caporossi & Alamargot, 2014). (ii) Second, using readymade letters in keyboarding does not involve any graphomotor processing, unlike ⇑ Corresponding author at: ESPE de l’Académie de Créteil – Université Paris-Est Créteil (UPEC), Site de Bonneuil – rue Jean Macé, 94861 Bonneuil sur Marne Cedex, France. E-mail address: [email protected] (D. Alamargot). http://dx.doi.org/10.1016/j.humov.2015.08.011 0167-9457/Ó 2015 Elsevier B.V. All rights reserved.

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handwriting. The writer’s task is therefore limited to spatially locating the specific letters on the keyboard and pressing the corresponding keys (Mangen & Velay, 2010). This difference in motor execution has an effect on reading, as the additional motor encoding that occurs during letter formation has been shown to promote the recognition of these letters, both in kindergarten children (Longcamp, Zerbato-Poudou, & Velay, 2005) and in adults (Longcamp, Boucard, Gilhodes, & Velay, 2006). (iii) The use of a keyboard can prove to be a costly alternative for children, as they consume cognitive resources searching for the keys they have to press, at the expense of written production. By comparing the handwriting and typing fluency of 300 children aged 4–11 years as they copied out a sentence, Connelly, Gee, and Walsh (2007) demonstrated the superiority of handwriting, regardless of age. In a second study with fifth and sixth graders, the authors showed that keyboarding can be as much as two years behind handwriting in development. Only students who have received keyboard training (i.e., touch-typing instruction) seem to benefit from the use of word processing software (see also Christensen, 2004; Rogers & Case-Smith, 2002). This series of examples linked to the use of a keyboard clearly shows that while technology can provide new and stimulating tools for writing, it can also impose new cognitive constraints that are not immediately perceptible. There is a similar problem when children use digital tablets in class, writing on the screen with a plastic-tipped pen. The few studies to have observed the impact of tablet use on writing have focused mainly on the new learning methods offered by interactivity (Berninger, Nagy, Tanimoto, Thompson, & Abbott, 2015; Jolly & Gentaz, 2013). The question of graphomotor constraints introduced by the particularly smooth tablet surface does not seem to have been considered, probably because this tool has only very recently been introduced into the classroom. Nonetheless, we all seem to have difficulty writing on a smooth and slippery surface, such as when we sign our name on the back of a credit card (Wann & Nimmo-Smith, 1991). In the same way, writing with a plastic-tipped pen on the glass surface of a tablet produces a sensation of sliding over a slippery surface, which suggests that the fine motor control required for adjusting pen movements is disturbed. It therefore seems timely to analyze the effects of screen surface on handwriting, by comparing the two handwriting media (i.e., paper and screen). Moreover, as handwriting control develops with age, notably with the mastery of motor programs at around 9 or 10 years of age, these possible effects probably vary according to the student’s level of development. 1.2. Development of handwriting skills and graphomotor execution Handwriting movements are complex, and their mastery takes time. Assuming that handwriting acquisition begins formally at school at around 5–6 years, proficiency in handwriting is not definitively acquired before 14–15 years (Accardo, Genna, & Borean, 2013; Blöte & Hamstra-Bletz, 1991; Rueckriegel et al., 2008; Ziviani & Wallen, 2006). During this developmental period, movement control shifts from a retroactive mode, based on the interpretation of sensory information (visual and propriokinesthetic feedback), to a proactive mode, based on central motor programs. Elaborated for each letter, these programs generally emerge at around 9–10 years (Blöte & Hamstra-Bletz, 1991; Chartrel & Vinter, 2006, 2008; Schmidt & Lee, 2005; Vinter & Chartrel, 2010; Zesiger, 1995) and provide the instructions needed for the motor control system to produce integrated movements (Paillard, 1990; Ziviani & Wallen, 2006). It is only at around 14–15 years that motor programs become completely automated (Ajuriaguerra, Auzias, & Denner, 1971; Rueckriegel et al., 2008). Before 9–10 years of age and the acquisition of motor programs, handwriting is slow and laborious. Considerable pressure is exerted on the pen, reflecting significant muscle tension, as well as the use of the shoulder and elbow to write (Bara & Gentaz, 2011; Chartrel & Vinter, 2004). The letters children form are often large, and have an irregular or rough appearance. The handwriting process is punctuated by pauses needed to calculate letter segments, based on sensory information. At the developmental level, Accardo et al. (2013) have shown that pause duration, which decreases significantly between 6 and 11 years, represents a sensitive indicator of changes in handwriting skills. Adopting another perspective, Paz-Villagrán, Danna, and Velay (2014) compared handwriting pauses in dysgraphic children aged 8–11 years with those of proficient children aged 7–9 years. These authors found that pauses that are either too numerous or too long are an indicator of dysfluency or poor handwriting. Beyond 9–10 years of age and the acquisition of motor programs, letter size, the amount of pressure exerted on the pen, and the frequency and duration of pauses between two segments decrease, while the speed, fluidity and legibility of letter formation increase (Accardo et al., 2013; Bara & Gentaz, 2011; Chartrel & Vinter, 2006, 2008; Freeman, 1914; Meulenbroek & Van Galen, 1988; Vinter & Chartrel, 2010; Vinter & Zesiger, 2007; Zesiger, Deonna, & Mayor, 2000; Ziviani & Wallen, 2006). Thus, in young writers who have not yet acquired any motor programs, perceptual feedback plays an essential role in controlling handwriting movements (Ziviani & Wallen, 2006). Chartrel and Vinter (2006) showed that when they were blindfolded, students aged 8–10 years increased their propriokinesthetic feedback by putting more pressure on the pen and by making the letters larger and increasing pen speed. In adults, while the proactive control of movement limits recourse to sensory feedback, it does not totally replace it. Deprivation of visual and/or propriokinesthetic information has been shown to disturb movement kinematics. By asking university students to handwrite the letter sequences gegegeg and nenenen with and without visual feedback, Van Doorn and Keuss (1993) highlighted an increase in pressure, speed and letter size in the absence of vision. Increased pressure augments the contact with the paper, and thus the amount of proprioceptive information available (see also Van Doorn, 1992; Van Doorn & Keuss, 1992). The proprioceptive system therefore continues to contribute to the proper execution of motor programs and the effective production of movements in adults. By studying pointing gestures in deafferented patients, Bard, Turrell, Fleury, and Teasdale (1999) showed that the motor system has the ability to

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modify and correct erroneous trajectories simply on the basis of feedback loops. For these authors, proprioceptive information, alongside vision, has a special status among motor programs, ensuring the online regulation (adjustment) of the initial motor commands (see also Prochazka, 2011). Regarding the adjustment of handwriting movement on the basis of propriokinesthetic information, paper smoothness has been shown to modify handwriting speed and pressure in experienced writers. When Chan and Lee (2005) asked adults to write a series of Chinese characters, they found that handwriting speed was slower for coated paper than for uncoated paper: writers needed to exercise more care and greater pen control to be able to write on the low-friction surface. A similar effect, but restricted to pen pressure, was demonstrated by Wann and Nimmo-Smith (1991). By asking adults to handwrite under conditions where pen (nylon tip vs. ballpoint tip) and paper (80 g/m paper vs. plain white paper) combinations produced different degrees of friction,1 the authors showed that mean pressure decreases when writing on a high-friction surface and then increases on switching to a low-friction surface. Pen pressure was therefore modulated in order to maintain a more stable ratio between frictional forces and input forces. This result highlights the sensitivity that skilled adults appear to have to the kinematics of handwriting movement, and reflects an acquired strategy of increasing frictional forces in order to maintain the input–output dynamics at a level comparable to that of a normal, usual writing surface. 1.3. The present study On the strength of studies with adults comparing paper textures and/or pen combinations (Chan & Lee, 2005; Wann & Nimmo-Smith, 1991), we can assume that, by modifying the propriokinesthetic feedback that students are accustomed to receive when writing on paper in the classroom, the smooth surface of a tablet screen, coupled with a plastic tipped pen, makes it more difficult for them to execute their handwriting movements. As far as we know, no such comparison has yet been undertaken among children, even for different roughnesses of paper. Furthermore, studies of the development of handwriting skills lead us to think that the modification in propriokinesthetic feedback, induced by the screen/plastic tip combination differently disturbs younger and older students (before and after motor program acquisition). Because younger students rely more heavily on perceptual feedback (retroactive visuo-propriokinesthetic feedback) to form letters, this type of change in the propriokinesthetic information presumably leads them to make longer pauses between segments in order to calculate their succession appropriately. By contrast, owing to their mastery of motor programs, more advanced writers (above the age of 9–10 years) can produce larger segments more fluently and without any significant pauses (Accardo et al., 2013). As the propriokinesthetic system therefore continues to contribute to the proper execution of motor programs and the ability to modify and correct erroneous trajectories (Bard et al., 1999), we reasoned that the change brought about by the screen/plastic tip combination would induce adjustments to pen movements. Older students would maximize their propriokinesthetic feedback by increasing the pressure they exerted on the pen and, possibly, the size of the letters they produced and, as a consequence (isochrony principle), their speed of movement. To verify these hypotheses, we took several methodological decisions and precautions. In order to compare participants’ graphomotor performances in two types of handwriting conditions (pen on a sheet of paper and pen on a tablet screen), we (i) administered the written alphabet recall task and the name-surname task (Chuy, Alamargot, & Passerault, 2012; Pontart et al., 2013) to children from two different age groups (Grades 2 and 9) corresponding to the stages before and after acquiring handwriting motor programs; (ii) analyzed graphomotor performances, looking at letter legibility and handwriting kinematics (see Accardo et al., 2013; Mergl, Tigges, Schroter, Moller, & Hegerl, 1999; Rosenblum, Chevion, & Weiss, 2006; Rosenblum, Dvorkin, & Weiss, 2006; van Galen & Weber, 1998). To maximize the validity of our comparison of the two different writing conditions, we controlled for the effects of important factors such as handwriting tool, kinematic measurements, writing situation (posture, gesture, brightness), and friction between tip and surface. (i) The magnetic pen that had to be used with the tablet was the same size and shape as the pen that is commonly used in the classroom. It did not induce any particular difficulties with pen grasp, even among the younger students. (ii) To be able to compare handwriting kinematics on paper and on the screen, it was vital to use the same screen tablet and pen each time to preserve the digitizing rate and sensitivity. This is why we decided to place the sheet of paper over the tablet screen in the paper condition. Because the magnetic grid of the digitizing screen tablet is able to detect the presence of the pen even when it is in the air (up to about 1 cm from the surface), the addition of an ordinary sheet of paper (without any magnetic component) did not interfere with the tablet’s sensitivity and its ability to detect pen movements. To allow the magnetic pen to actually write on paper, the plastic tip of the pen (used for writing on the screen) had to be removed and replaced with a ballpoint tip. (iii) The decision to place the sheet of paper on the tablet had the added advantage of putting participants in exactly the same postural situation (body position, room for arm and gestural movement) and limiting the difference in brightness (owing to the relative transparency of the sheet of paper). Moreover, in order to control the amount of information displayed to participants and the amplitude of their writing movements in the two conditions, the size and location of the writing zones on the screen were replicated on the sheet of paper. (iv) To ascertain the effect induced by the surface and the pen tip, we first assessed the static friction effect between tip and surface. To do so, like Wann and Nimmo-Smith (1991), we used an articulated

1 The friction of a nylon-tipped pen on 80 g/m paper was estimated to be 0.25 (coefficient of friction), that of a ParkerÒ ballpoint on 80 g/m paper 0.125, and that of a nylon tip on very smooth, plain white paper 0.05.

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Fig. 1. Apparatus for assessing the impact of friction on pen movement speed.

Table 1 ‘‘Pen movement speed (cm/s) in four handwriting conditions with four loads gradually increasing the pressure exerted on the pen. Load (on pen)

10 g 20 g 30 g 40 g Mean

Handwriting conditions (surface  pen tip)

Mean

Paper/plastic

Paper/ballpoint

Screen/ballpoint

Screen/plastic

No No No No X

10.65 5.70 2.84 1.52 5.18

32.86 26.16 19.58 11.68 22.57

56.13 50.16 44.09 38.71 47.27

movement movement movement movement

33.22 27.34 22.17 17.30

arm that held the pen on the surface and constrained its path. The translational force exerted on the pen to move it was generated by a 40 g load, while the pressure exerted on the pen was varied by adding weights to the pen (10, 20, 30 or 40 g) (see Fig. 1). Measures of pen movement speed (for 22 cm of translational motion) were repeated under 16 conditions (4 loads  paper/screen surface  ballpoint/plastic tip). As shown in Table 1, results clearly indicated that the screen surface, when using a plastic tip, was dramatically smoother, generating, for the same translational force, a higher pen movement speed (mean: 47.27 cm/s) than the 80 g/m paper surface, when written on with a ballpoint tip (mean: 5.18 cm/s). This difference remained however much pressure was exerted on the pen. It should be noted that the paper/plastic tip pairing induced such high friction that the 40 g weight did not generate any translational motion, however little pressure was exerted on the pen. 2. Experiment 2.1. Participants Fourteen second graders (4 boys, 10 girls, age: M = 7.53 years, SD = .30, two left-handers) and ninth graders (7 boys, 7 girls, age: M = 14.45, SD = .32, two left-handers) took part in this experiment. They were from three schools on the outskirts of the French city of Poitiers in the Vienne département. None of the students had ever written with a pen on a screen tablet before. None had repeated a grade or displayed any learning disabilities or fine motor disorders (as assessed by the Fingertip Tapping, Imitating Hand Positions and Manual Motor Sequences tasks of the NEPSY; Korkman, Kirk, & Kemp, 2003; see Table 4 in Appendix). 2.2. Experimental tasks All the students were asked to write out (i) their name and surname twice, starting with uppercase letters (Pontart et al., 2013), and (ii) lowercase letters of the alphabet recalled in the right order (Abbott & Berninger, 1993). In both cases, students were invited to write in their usual handwriting, as quickly and accurately as possible.

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Fig. 2. Information displayed on the tablet or printed on the sheet of paper for the alphabet task.

2.3. Material The two writing tasks were performed on an LCD digitizing screen tablet (Wacom Cintiq 21UX) linked to a laptop computer (Apple MacBook, piloted by Eye and PenÒ software; Alamargot, Chesnet, Dansac, & Ros, 2006; Chesnet & Alamargot, 2005). The students wrote directly on the tablet using a pen (Wacom InkPen) with a plastic tip (no ink), and on an A3 sheet of 80 g/m paper placed on the tablet, in which case the same pen was equipped with a ballpoint tip. The Eye and PenÒ software (i) recorded the position and state of the tip (with or without pressure) in realtime on the tablet screen/sheet of paper, and (ii) managed the display of the instructions (for the two experimental conditions) and the writing zones and visual (letter formation) feedback on the screen (screen condition only). These zones comprised four boxes in which participants wrote the two series of names and surnames, and 26 boxes in which they wrote the recalled alphabet letters (Fig. 2). Each writing zone featured French ruled writing lines within a gray frame (see also Alamargot et al., 2014). 2.4. Procedure The two tasks were performed individually, in a predetermined order (name-surname followed by alphabet task). The order of the handwriting conditions (on screen and on paper) was alternated from one participant to the next (i.e., counterbalanced within-participants design). There was no time limit on writing, but the students never wrote for very long. On average, the alphabet task was completed in 94 s (Grade Two) and 33 s (Grade Nine), and the name-surname task in 46 s (Grade Two) and 18 s (Grade Nine). 2.5. Measured variables Handwriting performances were subjected to a twofold analysis (letter legibility and handwriting kinematics). (i) Concerning the legibility of letter formation, we calculated a legibility score (total number of legible letters/total number of letters produced, %) using the Evaluation Tool of Children’s Handwriting (ETCH; Amundson, 1995; see also Alamargot et al., 2014). (ii) The kinematics of handwriting was assessed for all letter productions (whatever the legibility) via pen pressure on the tablet’s surface (out of 1200 levels of pressure), letter size, using the information supplied by the tablet (length of pen movement/number of letters produced, cm/letter), pen speed (mean speed of pen movements between two pauses, cm/ s), and pen pauses, defined according their duration (mean duration of pauses, ms). A pause had to last more than 20 ms. This value was determined by the formula 3  (1000/150), where 150 was the actual sampling frequency (Hz) of the digitizing

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tablet. Since it is possible to lose two successive samples during the acquisition and transmission of data to the Eye and Pen software, we took the duration of three consecutive samples as the minimum pause threshold; events of a shorter duration were linked to pen movement sampling (Alamargot, Plane, Lambert, & Chesnet, 2010). 3. Results It is important to mention that all the students successfully completed the alphabet task. The ninth graders produced the maximum number of letters (M = 26) without any recall errors (omission or order), regardless of writing surface. The number of letters recalled by the second graders was also close to the maximum, and did not differ significantly between the surfaces (screen: M = 25.79, SD = 48; paper: M = 25.86, SD = .36; Student’s t test = .563, df = 13, p > .55). Few recall errors were made, and never more than one per participant. The percentage of students who produced recall errors did not vary according to surface (screen: 21.42% (three participants); paper: M = 28.57% (four participants); v2(1, 14) = 2.75, p > .15). Results for letter legibility and handwriting kinematics (movement and pauses) are summarized in Tables 2 and 3. We ran a series of analyses of variance (ANOVAs) for each of the variables we measured, considering grade (Grade Two/Nine) and order of conditions (paper–screen/screen–paper) as between-participants factors, and writing surface (screen/paper) and handwriting task (alphabet/name-surname) as within-participants factors. As we did not detect any significant effect of order of conditions for each measure, this factor was removed from the analyses. In agreement with our hypotheses, only the results relating to the surface factor and its interactive effects with grade and/or handwriting task were taken into account. When the effect of the interaction with the surface factor was significant, partial post hoc Newman Keuls-type comparisons were carried out, and the main effect of the other interacting factor was then described. The Bonferroni correction was applied to avoid the risk of Type-1 errors. 3.1. Legibility of letter formation The percentage of legible letters was significantly lower on screen (M = 84.90%) than on paper (M = 90.66%), F(1, 26) = 24.02, MSE = 9.25, p < .001. The main effect of task was not significant (p > .90), unlike its interaction with surface, F(1, 26) = 8.01, MSE = 3.39, p < .01. Legibility was lower on the screen (M = 83.10%) than on paper (M = 92.33%) in the name-surname writing task (p < .001). Furthermore, legibility on the screen was lower in the name-surname task than it was in the alphabet task (M = 86.72%, p < .05). No other significant interaction with surface was found (see Table 2). 3.2. Handwriting kinematics – Pressure exerted by the pen: The main effect of surface was significant, F(1, 26) = 7.06, MSE = 36143, p < .04. Greater pressure was exerted by the pen on the screen (M = 484) than on paper (M = 448). The main effect of grade was also significant, F(1, 26) = 7.07, MSE = 564242, p < .02. More pen pressure was exerted by ninth graders (M = 537) than by second graders (M = 395). The Surface  Grade interaction was significant, F(1, 26) = 15.33, MSE = 110528, p < .001. Pressure was modified by surface, but only for ninth graders (p < .005). – Letter size: Only the main effect of surface was significant, F(1, 26) = 104.57, MSE = 13.34, p < .0001. The distance traveled by the pen to form a letter was always longer on the screen (M = 2.76 cm/letter) than on paper (M = 2.07 cm/letter), regardless of grade and writing task. – Pen speed: The main effect of surface was significant, F(1, 26) = 40.05, MSE = 13.84, p < .0001. The pen moved faster on the screen (M = 3.65 cm/s) than on paper (M = 2.95 cm/s). Grade also had a significant effect, F(1, 26) = 42.48, MSE = 143.76, p < .0001. Pen speed was higher in Grade Nine (M = 4.43 cm/s) than in Grade Two (M = 2.17 cm/s). The Surface  Grade interaction was significant, F(1, 26) = 40.05, MSE = 13.84, p < .0001. The main effect of surface was significant in Grade Nine (1.08 cm/s difference between screen and paper conditions; p < .01) but not in Grade Two (.33 cm/s difference between the screen and paper conditions; p > .20). No significant interaction with surface was observed.

Table 2 Mean percentage (standard deviation) of legible letters, according to Grade (Two/Nine), writing surface (screen/paper) and writing task (alphabet/namesurname). Screen

Letter legibility (%)

Grade 2 Grade 9

Paper

Alphabet

Name

All tasks

Alphabet

Name

All tasks

85.30 (12.56) 88.14 (6.15)

79.70 (21.05) 86.48 (9.59)

82.70 (16.80) 87.31 (7.87)

88.41 (10.58) 89.56 (5.32)

88.13 (18.05) 96.52 (3.42)

88.27 (14.31) 93.04 (4.37)

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Table 3 Handwriting kinematics for movement: mean (standard deviation) pen pressure, pen speed, letter size and pause duration according to Grade (Two/Nine), writing surface (screen/paper) and writing task (alphabet/name-surname). Screen

Pen pressure

Grade 2 Grade 9

Letter size (cm)

Grade 2 Grade 9

Pen speed (cm/s)

Grade 2 Grade 9

Pause duration (ms)

Grade 2 Grade 9

Paper

Alphabet

Name

All tasks

Alphabet

Name

All tasks

358 (173) 566 (116) 3.19 (.83) 2.97 (.60) 2.39 (.77) 5.12 (1.48) 684 (233) 450 (109)

405 (180) 607 (122) 2.66 (.85) 2.22 (.49) 2.27 (.67) 4.83 (1.34) 396 (115) 245 (49)

381 (176) 586 (119) 2.92 (.84) 2.60 (.55) 2.33 (.72) 4.95 (1.41) 540 (174) 347 (79)

383 (167) 477 (124) 2.46 (.47) 2.13 (.46) 2.01 (.55) 4.00 (1.25) 531 (102) 347 (52)

435 (185) 499 (104) 2.04 (.57) 1.65 (.24) 2.00 (.47) 3.80 (.98) 267 (77) 210 (50)

409 (176) 488 (114) 2.25 (.52) 1.89 (.35) 2.00 (.51) 3.90 (1.115) 399 (89) 278 (51)

– Mean pause duration: The main effect of surface was significant, F(1, 26) = 43.52, MSE = 307355, p < .0001. The mean duration of pauses was higher when writing on a screen (M = 443 ms) than on paper (M = 339 ms). The main effect of grade was also significant, F(1, 26) = 31.90, MSE = 686282, p < .0001. Pauses were longer for second graders (M = 469 ms) than for ninth graders (M = 313 ms). The Surface  Grade interaction was significant, F(1, 26) = 5.04, MSE = 35611, p < .04. The effect of surface was greater for second graders (141-ms difference between screen and paper conditions; p < .0005) than for ninth graders (69-ms difference between both conditions; p < .05).

4. Discussion Following studies assessing in children the impact of keyboarding on written production, compared to handwriting (Connelly et al., 2007), this exploratory study tends to examine the potential constraints introduced by new writing technologies like digital tablet, on graphomotor control. More precisely, the goal of this study was to identify the impact of a smooth tablet surface on handwriting quality and kinematics in students who either had or had not yet mastered handwriting motor programs. Given that the roughness of paper modifies handwriting speed and pressure (Chan & Lee, 2005; Wann & Nimmo-Smith, 1991), and considering, as we shown, the very low friction resulting from the tablet screen and the plastic tip combination, we predicted that the modification induced in propriokinesthetic feedback would differently disturb the younger and older students, who rely on perceptual feedback either to form letters (former) or to adjust movement execution (latter). Results revealed an effect of writing surface for each measure we considered. Handwriting on the screen tablet with a nylon tip led to a decrease in letter legibility (for the name-surname task) and an increase in letter size (for both the alphabet and name-surname tasks), regardless of grade. Concerning the interaction with grade, the hypothesis of different disturbances of handwriting in second graders and in ninth graders was generally confirmed. More specifically, the surface effect differed according to grade, with different interaction effects on movement or pausing. Writing on a screen with a nylon tip, as opposed to a sheet of paper with a ballpoint, only had an effect on movement execution in ninth graders, increasing both pen pressure and pen speed, whereas it had a more significant effect on pauses in second graders, leading to a greater increase in duration. These results are coherent with the development of graphomotor execution and the consequence of motor program mastery. Results from the second graders suggest that they had more difficulty calculating segment trajectories when they handwrote on the screen tablet surface with a plastic tip. By dramatically changing the propriokinesthetic information, the very low friction generated by the tablet/nylon tip combination forced these students to pause for longer between two segments. This extra time was probably needed to carefully analyze the previous segment, which had been formed using non-usual information, and to adjust the next one accordingly. Despite this processing, they produced larger and less legible letters. By contrast, results from the ninth graders confirmed that they were more disturbed in the online regulation of initial motor commands (Bard et al., 1999). Writing with the plastic-tipped pen on the smoother tablet surface led them to

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compensate for the decrease in propriokinesthetic feedback by pressing down harder on their pen, amplifying their movement (letter size) and increasing their pen speed. This behavior, observed in ninth graders here, is similar to that observed by Chan and Lee (2005), and Wann and Nimmo-Smith (1991) in adults handwriting on a low-friction surface. However, this online adaptation of movement kinematics was not sufficient here: the resulting letters were therefore less legible and pause durations increased slightly, albeit less than for second graders.

5. Conclusion The results of this study go a long way to answering the questions raised by the introduction of digital tablets in the classroom. Obviously, writing on a tablet surface is a very different experience from writing on paper, but the precise effects on graphomotor execution vary according to grade. We found that handwriting with a pen on a tablet modified (i) the calculation of segment trajectories in Grade Two, and (ii) the execution of motor programs in Grade Nine, probably owing to a lack of kinesthetic feedback throughout the task. Even if we cannot reach an extended conclusion on the strength of this exploratory study, our results nonetheless draw attention to the possible impact this device could have on learning and practicing handwriting movements, handwriting remediation, and day-to-day writing in the classroom. These initial results raise several questions that will need to be addressed in future studies. Four points have to be considered. (i) Only two grades were compared here. From a developmental perspective, research therefore needs to be extended to the levels before Grade Two (when handwriting is being acquired) and after Grade Nine (including adults, whose motor programs are completely proceduralized), as well as to the intermediate grades. (ii) Since the participants in this study were all writing on a tablet screen for the first time, the question of how students learn graphomotor control in this new digital situation is paramount, and we should therefore also consider the design and impact of possible training programs in the educational field. Learning to write on a tablet, as well as on paper, could improve graphomotor calculation and execution among young students using keyboards. As such, it might be useful to investigate different surface textures and types of pen/pencil tips in order to bring about ergonomic enhancements. For instance, our initial results suggest that increasing the texture of the screen surface and/or using a more frictional pen tip would reduce the difficulties that were encountered by our older students. (iii) We demonstrated an effect of tablet surface on the legibility and kinematics of handwriting. Given research showing a link between handwriting skills and spelling or compositional performances in children (Graham, Berninger, Abbott, Abbott, & Whitaker, 1997; Morin, Lavoie, & Montesinos, 2012; Pontart et al., 2013), the impact of this disturbance in handwriting control on higher level writing processes needs to be examined. To conclude, this pioneering study contributes to the understanding of the effects of introducing new technologies for writing in schools, in particular the introduction of handwriting on a screen with a pen. This type of investigation needs to become systematic, in order to weigh up the possible constraints on writers in different grades of the different writing devices that are now beginning to be used both in mainstream education and in the context of remediation for students with writing difficulties.

Ethical approval All procedures performed in this study involving human participants were in accordance with the ethical standards of the institutional and/or national research committee, with the 1964 Helsinki declaration and its later amendments or comparable ethical standards, and with the 1988 French rule ‘‘Huriet” on the bioethical protection of persons involved in human experimentations.

Acknowledgements This research received financial support from the French National Research Agency (ANR – France)’s Dynamics of Orthographic Processing (DyTO) project, the state/region planning contract (CPER) for Poitou-Charentes (France), and the Research chair in reading and writing learning in young children (CREALEC; University of Sherbrooke, Quebec, Canada). We would like to thank the schools in Biard, Cenon and Saint-Benoît (Vienne département) that contributed to the testing of their students, the Vienne Education Service, which facilitated our research team’s interventions in the different schools; Lisa Flouret, Virginie Pontart and Érika Simard-Dupuis for their contribution to the data collection and analysis, and Elizabeth Portier for her English translation of the manuscript.

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Appendix

Table 4 Participants’ characteristics and scores on the NEPSY motor skill tasks (Fingertip Tapping: time taken to perform the task in seconds; Imitating Hand Positions (IHP): score out of 24; Manual Motor Sequences (MMS): score out of 60; mean scores and standard deviations, mean standards ±2SD). None of the participants had scores more than two standard deviations above or below the mean for their group on any of the tasks. No.

Grade

Sex

Age

Handedness

Tapping

IHP

MMS

1 2 3 4 5 6 7 8 9 10 11 12 13 14

2 2 2 2 2 2 2 2 2 2 2 2 2 2

M M F F F M F F F F F F M F

7.08 7.26 7.53 7.05 7.67 7.94 7.73 7.37 7.42 7.27 7.62 7.89 7.70 7.92

15 16 17 18 19 20 21 22 23 24 25 26 27 28

9 9 9 9 9 9 9 9 9 9 9 9 9 9

F F M F F F M F F M M M M M

14.35 14.24 14.73 14.44 14.80 14.58 14.15 14.65 14.89 13.84 14.67 14.73 14.22 14.02

Right-handed Right-handed Right-handed Right-handed Right-handed Left-handed Right-handed Right-handed Right-handed Left-handed Right-handed Right-handed Right-handed Right-handed Mean SD Mean 2SD Mean + 2SD Right-handed Right-handed Right-handed Right-handed Right-handed Right-handed Left-handed Right-handed Right-handed Right-handed Right-handed Right-handed Right-handed Left-handed Mean SD Mean 2SD Mean + 2SD

66.6 71.7 68 79.58 66.6 91.7 64.34 79.1 82.3 63.7 92.3 61 51.6 76.5 72.50 11.67 49.16 95.84 40 38.8 47.1 38.41 40.3 40.6 39.04 45.28 42.3 34.44 36.4 51.12 50.67 33.8 41.30 5.44 30.42 52.19

24 21 23 20 24 24 21 22 23 21 22 24 24 23 22.57 1.40 19.77 25.37 24 24 24 24 24 24 23 24 24 23 24 24 23 23 23.71 0.47 22.78 24.65

53 51 46 55 49 57 42 48 51 57 52 58 53 48 51.43 4.57 42.29 60.57 56 58 53 57 58 49 59 59 56 60 57 59 56 57 56.71 2.84 51.03 62.39

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