Assessing the Development of Fine Motor Control in Elementary School Children Using Drawing and Tracing Tasks

Abstract

Adequately quantifying fine motor control is imperative for understanding individual motor behavior development and mastery. We recently showed that using different tasks to evaluate fine motor control may produce different results, suggesting that multiple measures for fine motor control may be evaluating different skills and/or underlying processes. Specifically, drawing behavior may depend on internal cueing, whereas tracing depends more on external cueing. To better understand how an individual develops a certain preference for cueing, we evaluated fine motor control in 265 typically developing children (aged 6–11) by measuring their accuracy for both drawing and tracing a circle. Our results first confirmed that there was no significant correlation between tracing and drawing task performances during this phase of development and, secondly, showed a significant developmental improvement in tracing, especially between 2nd and 3rd graders, whereas drawing ability improved only moderately. We discuss the potential roles of attentional focus and cognitive development as possible influencing factors for these developmental patterns. We conclude that using both a drawing and tracing task to evaluate fine motor control is rapid, economic and valuable for monitoring motor development among elementary school children.

Keywords

fine motor control typically developing children circle drawing circle tracing development of motor behavior

Introduction

During development, the nervous system is under continuous modification and maturation, making accurate quantification of various functional abilities imperative. For motor control specifically, many motor proficiency tests have been introduced (Beery & Beery, 2010; Bruininks & Bruininks, 2005; Folio & Fewell, 2000; Henderson et al., 2007; Piper et al., 1992; Russell et al., 2013). Among these tests, the Bruininks-Oseretsky Test of Motor Proficiency (BOT-2; Bruininks & Bruininks, 2005), the Movement Assessment Battery for Children (Movement ABC-2; Henderson et al., 2007), and the Beery-Buktenica Visual-Motor Integration Test (Preda, 1997), are specifically oriented toward typically developing children of scholastic ages. For a review of these and other commonly used motor tests for children, please refer to Scheuer et al., 2019. While several of the aforementioned tests examine both fine and gross motor skills, their administration is quite lengthy (20-40 min for the Movement ABC-2 and 45–60 min for BOT-2; Matheis & Estabillo, 2018). Furthermore, they are all commercial, proprietary tools that can be costly to administer on a large scale.

Another common approach for examining fine motor control is to employ drawing and tracing tasks (Cohen, Bravi, & Minciacchi, 2018; Gatouillat et al., 2017; Smits et al., 2018; Sülzenbrück et al., 2011; Vuillermot et al., 2009), which, due to their simplicity, do not require prior preparation and can be administered quickly. However, as recently evidenced, while both drawing and tracing tasks are estimates of fine motor control, they are not significantly correlated with one another (Cohen et al., 2018). In an attempt to explain their differences, prior researchers have suggested that these tasks may rely differentially on external or internal cueing processes, with some examinees favoring the former and others the latter. Among young children, drawing and tracing skills are still developing. Therefore, they may be controlled differently than might be the case for adults. In fact, adult handwriting, by being subject to years of practice and repetition, has generally become automatic and requires minimal attentional control (Tucha et al., 2008). Children’s handwriting on the other hand, is not only not yet automated, but it is subject to immense further development and change, most significantly for children between 7–10 years old, when children transition from control that is based on visual feedback to control from stable motor representations (Palmis et al., 2017; Rueckriegel et al., 2008). Though handwriting is considered to be a more elaborate task than drawing of simple shapes (Rueckriegel et al., 2008), handwriting provides insight into potential differences in motor control during these stages of development. Not surprisingly, correlations have been found between children’s drawing ability and their handwriting proficiency (Bonoti et al., 2005). Therefore, it is possible that children, still amidst individual development, show a different reliance on internal and external processing cues for drawing than do adults.

During early developmental ages, two factors may influence drawing and tracing performance. The first, of course, is that children of different ages may have different skill levels, manifested in part by different tracing and drawing performances between children of different age groups (Fransen et al., 2014). In fact. the presence of a template as well as the consolidation of automatic processes, due to habitual usage, may favor older children’s employment of an external cueing focus (Castaneda & Gray, 2007; Marchant, 2010; Marchant et al., 2007; Wulf, 2007, 2013; Wulf & Lewthwaite, 2010). Therefore, tracing performances, considered to employ a more external focus, may reflect significant maturation changes. The second influencing factor is that individual children possess different maturation of neural structures associated with motor control. For example, the corticospinal tract, an important structure for dexterity, changes rapidly from infancy to adolescence (Fietzek et al., 2000; Müller et al., 1991). Maturational differences in central nervous system regions are, in turn, associated with increasingly advanced functions (Toga et al., 2006). These regions may include the basal ganglia, cerebellum, and the premotor and supplementary motor cortices, all of which are involved in elaborating movement and internal and external cueing (Mushiake et al., 1991; van Donkelaar & Staub, 2000; van Donkelaar et al., 1999). Therefore, both age-related experience and individual neurological maturation can differentially influence tracing and drawing.

In this study we investigated the use of drawing and tracing tasks to evaluate the development of fine motor control among elementary school children. Specifically, we compared children’s accuracy and speed of execution in either drawing or tracing a circle. We assumed that, similar to adults, there would be no significant correlation between children’s proficiencies of drawing and tracing. Furthermore, considering the gradual maturation of the nervous system during development, as well as the differences in drawing and tracing tasks, we expected to find a gradual improvement for both tracing and drawing, though at different rates, across our sample of 6–11 year old children. With these expectancies in mind, we compared children of different ages in our sample in order to examine age-related differences between tracing and drawing proficiency.

Method

Participants

We recruited 265 elementary school students, ages 6–11 (138 males), for this study (see Table 1). All participants were naive to the tasks and the purpose of the study; and all were free of documented visual, motor, and/or neurological impairments. Parents of all participants reported these children to have a corrected-to-normal visual acuity and to have no previous experience in using a graphic pen tablet. The study protocol was approved by the Institutional Ethics Committee (Comitato Etico Area Vasta Centro AOUCareggi, Florence, Italy). Prior to the start of the experimental procedures, the parents/guardians of each child provided informed consent for their child to participate. The director of the school also signed an agreement that formally allowed the children to be tested in the school. The study protocol and all procedures conformed to the code of ethics of the Declaration of Helsinki.

Table 1.

Participant Characteristics (Grade, Handedness and Sex).

Grade	Total	Left handed	Males	Females
1st grade	73	10	38	35
2nd grade	45	4	24	21
3rd grade	64	8	35	29
4th grade	35	5	20	15
5th grade	48	3	21	27

Study Design and Task Procedure

This study’s design was very similar to the one used in Cohen et al. (2018) and is here briefly summarized. The participants executed both tracings and drawings (that were projected on a monitor) while seated in a way that supported neither their left or right wrist, arm, or elbow so that the only contact with the tablet was made through the pen they held (see Figure 1). All tasks were performed using a graphic pen tablet (Wacom Intuos® CTH-690AK, Tokyo, Japan; active area: 216 × 135 mm), and each participant was tested individually.

Figure 1.

Diagram Illustrating the Experimental Setup.

Our instructions specified that participants were to trace a circle (50 mm radius) or to draw a medium size circle counterclockwise, starting from 12 o’clock as precisely as possible with no emphasis on the speed of execution. Participants were further instructed to trace or draw the circles while keeping the wrist steady. Before starting the task, each participant was asked whether the instructions were understood. Each participant performed both a drawing of a circle as well as a tracing of a circle, with the order of tracing and drawing randomized across participants so as to obtain an equal number of participants that began with each task. There was a 1-minute interval between the two tasks.

Accuracy Analysis

Using Matlab, we developed an algorithm to measure the accuracy of the drawn circles. The algorithm consisted of first finding the centroid of the drawn shape. This was achieved by taking the mean value of all x and y coordinates on the graphic tablet, the result of which would provide a reference center. From the reference center, points were organized according to their angle and were then reduced to 360 points, having one point per degree. This was done in order to reduce the sensitivity to the way the shape was drawn (e.g., parts drawn slower will result in more points and could result in miscalculation of the mean radius as well as the CV). After the point reduction, the mean value of all x and y coordinates were calculated on the remaining point, and the result was considered as the center of the circle. Following that, we calculated the distance of each point (prior to the reduction) of the drawing from the center. These distances were considered as the radii for the drawn circle, the mean value of which would result as the radius of the corresponding perfect circle. Seeing that no indication was provided regarding the size of the circle, we considered the coefficient of variation (CV) of the radii as a measure of the accuracy of the drawn circle, bearing in mind that for a perfect circle the variability would be zero. The same algorithm was used also for CV analysis of the traced circles (Cohen et al., 2018; Cohen, Bravi, & Minciacchi, 2018).

Speed Analysis

In order to calculate the speed of execution, first the distance travelled during the execution was calculated for each circle. This was done by calculating the distance travelled between each two consecutive points and summing the distances to yield the total distance for each circle. This measure, was later used along with the total time of the execution to calculate the average speed (mm/sec) for each trial, using the formula Distance/Time.

Statistical Analyses

As not all of the dependent measures were found to be normally distributed (see Table 2), we analyzed data using nonparametric methods. In order to evaluate any correlations between performances, we used the Spearman correlation coefficient on the CVs and speed for both the circle drawings and circle tracings. To evaluate any differences among school grades for CVs and for speed, we conducted a Kruskal-Wallis test for independent variables, followed by Dunn-Bonferroni adjusted post-hoc test in case of multiple comparisons. To evaluate potential differences between males and females, we used a Kruskal-Wallis test on the drawing and tracing performances separately for each grade. To evaluate circle size differences between tracing and drawing, we used a Friedman test for dependent variables on the measured radii of the performances separately, for each grade. Finally, to evaluate potential differences due to laterality, we used a Kruskal-Wallis test on the drawing and tracing performances separately, for each grade.

Table 2.

Shapiro–Wilk Data Distribution Normality Tests for Each Variable by Participant Grade Level.

Grade	Tracing		Drawing
Grade	CV	Speed	CV	Speed
1st grade	W(73) = 0.89,p < 0.001	W(73) = 0.31,p < 0.001	W(73) = 0.95,p < 0.05	W(73) = 0.61,p < 0.001
2nd grade	W(45) = 0.82,p < 0.001	W(45) = 0.67,p < 0.001	W(45) = 0.95,p = 0.05	W(45) = 0.82,p < 0.001
3rd grade	W(64) = 0.61,p < 0.001	W(64) = 0.23,p < 0.001	W(64) = 0.89,p < 0.001	W(64) = 0.69,p < 0.001
4th grade	W(35) = 0.73,p < 0.001	W(35) = 0.40,p < 0.001	W(35) = 0.93,p < 0.05	W(35) = 0.69,p < 0.001
5th grade	W(48) = 0.93,p < 0.05	W(48) = 0.69,p < 0.001	W(48) = 0.93,p < 0.05	W(48) = 0.93,p < 0.05

Note. CV is coefficient of variation. With the exception of CVs for the 2nd grade, data were not found to be normally distributed. Normality test results.

Results

Data dispersion within grades was progressively reduced with age for both tracing and drawing performances. However, while this reduction was quite evident for tracing, dispersion of drawing accuracy reduced only moderately (see Figure 2). Interestingly, data dispersion did not align with the adult level of dispersion reported by Cohen et al., 2018, based on 125 observations, although it appeared that certain participants (some as young as 1st graders) had already reached adult level performances for either tracing or drawing or both. CVs in both drawing and tracing showed a gradual reduction with age. Specifically, for 1st graders, drawing accuracy averaged 0.17 (SD = 0.09) and gradually reduced to 0.1 (SD = 0.08) by the 5th grade. A similar, yet more prominent, trend was revealed for tracing accuracy which averaged 0.15 (SD = 0.11) for the 1st graders and gradually reduced to 0.05 (SD = 0.02) by the 5th grade (see Figure 3). For speed, mean speed of drawing averaged 46.9 mm/sec (SD = 47.9 mm/sec) in 1st graders and remained relatively stable, averaging 44.4 mm/sec (SD = 26.9 mm/sec) by the 5th grade. A different trend was found for tracing with speed averaging 32.5 mm/sec (SD = 71.9) for the 1st graders and gradually reduced to 12.0 mm/sec (SD = 6.6 mm/sec) by the 5th grade (see Figure 4).

Figure 2.

Dispersion of Coefficient of Variation (CV) Data for Both Drawing and Tracing Tasks.

Figure 3.

Drawing and Tracing Accuracy.

Figure 4.

Drawing and Tracing Speed.

There was a significant correlation in accuracy (measured as CVs) between performances in circle tracing and drawing only for students in the 1st grade, (SD = 71) = 0.36, p < 0.001, while there were no significant correlations between these performances for students in any other grade (see Table 3). Correlations for speed during tracing and drawing were found to be high for the 1st, 2nd, and 3rd grades, and low for the 4th and 5th grades (Table 3). Finally, Speed and CV presented a low to moderate correlation for the 1st and 2nd grades for both drawing and tracing. From the 3rd to the 5th grade, a moderate to high correlation was found for both drawing and tracing (Table 3).

Table 3.

Results of Spearman Correlational Analyses Between Tracing and Drawing and Between Speed and CVs by Grade Level.

Grade	Correlation tracing vs drawing		Correlation speed-CV
	CV	Speed	Tracing	Drawing	d.f
1st grade	0.36 (p < 0.001)	0.78 (p < 0.001)	0.34 (p < 0.05)	0.31 (p < 0.05)	71
2nd grade	0.16 (p = 0.27)	0.65 (p < 0.001)	0.03 (p = 0.80)	0.19 (p = 0.18)	43
3rd grade	0.13 (p = 0.38)	0.77 (p < 0.001)	0.40 (p < 0.05)	0.6 (p < 0.001)	62
4th grade	−0.29 (p = 0.08)	−0.09 (p = 0.59)	0.70 (p < 0.001)	0.51 (p < 0.05)	35
5th grade	0.03 (p = 0.82)	0.34 (p < 0.05)	0.43 (p < 0.05)	0.41 (p < 0.05)	46

Kruskail-Wallis analyses performed on the CV’s of drawing and tracing confirmed a significant difference among grades for both drawing (χ²(4) = 18.12, p < 0.001) and tracing (χ²(4) = 68.83, p < 0.001). Post-hoc analyses revealed no significant differences in drawing for all pairs of grades with the exception of 1st vs 3rd (p < 0.05) and 1st vs 5th (p < 0.05). For tracing, no significant differences were found between these grade pairs: 1st vs 2nd (p = 0.9), 3rd vs 4th (p = 0.9), 3rd vs 5th (p = 0.9), and 4th vs 5th (p = 0.8). All other associations for tracing were found to be statistically significant (p < 0.001).

Similarly, no significant differences in speed were found among grades for drawing (χ²(4) = 7.82, p = 0.09), whereas significant differences among grades were found for tracing (χ²(4) = 37.5, p < 0.001). Post hoc analyses revealed significant differences between 1st vs 3rd grade (p < 0.009), 1st vs 4th grade (p < 0.001), 1st vs 5th grade (p < 0.05), 2nd vs 3rd grade (p < 0.001), 2nd vs 4th grade (p < 0.001), 2nd vs 5th grade (p < 0.05). No significant differences were found between 1st vs 2nd grade (p = 0.91), 3rd vs 4th grade (p = 0.87), 3rd vs 5th grade (p = 0.99) and 4th vs 5th grade (p = 0.76). Of note, while there were no significant drawing differences between consecutive grades (e.g., 1st vs 2nd, 2nd vs 3rd, etc.) for both CVs and speed, there were significant tracing differences between 2nd vs 3rd graders for both variables (p < 0.001).

To examine sex differences, we used the Kruskal-Wallis test for each grade, comparing each parameter separately. No significant differences between males and females were found for tracing or drawing in all grades for both CV and speed (Tables 4 and 5). Also, the size of the participants’ traced and drawn circles, according to the Friedman test results, did not differ significantly between tracing and drawing for all grades (Table 6), with the exception of the 4th grade where there was a significant difference between performances (M = 49.3, SD = 4.9 mm trace; M = 46.1, SD = 10mm drawing; χ²(1) = 6.43, p < 0.05).

Table 4.

Kruskal–Wallis Test Male Versus Female CV Comparisons.

	CVs - Male vs females
	Tracing					Drawing
Grade	Male CV	Female CV	p-value	χ²	d.f.	Male CV	Female CV	p-value	χ²	d.f.
1st grade	0.18 ± 0.13	0.16 ± 0.11	0.69	0.15	1	0.23 ± 0.09	0.20 ± 0.08	0.21	1.0	1
2nd grade	0.21 ± 0.15	0.16 ± 0.15	0.15	2.05	1	0.21 ± 0.07	0.18 ± 0.06	0.27	1.19	1
3rd grade	0.08 ± 0.05	0.08 ± 0.08	0.93	0.33	1	0.17 ± 0.08	0.17 ± 0.09	0.66	0.18	1
4th grade	0.06 ± 0.03	0.08 ± 0.04	0.13	2.25	1	0.17 ± 0.07	0.18 ± 0.09	0.61	0.25	1
5th grade	0.05 ± 0.02	0.05 ± 0.01	0.84	0.04	1	0.14 ± 0.05	0.17 ± 0.07	0.32	0.97	1

Table 5.

Kruskal–Wallis Male Versus Female Speed Comparisons.

	Speed - male vs females
	Tracing					Drawing
Grade	Male speed	Female speed	p-value	χ²	d.f.	Male speed	Female speed	p-value	χ²	d.f.
1st grade	33.6 ± 89.8	31.3 ± 46.7	0.79	0.06	1	46.9 ± 58.8	46.9 ± 33.1	0.35	0.84	1
2nd grade	30.8 ± 29.3	25.8 ± 31.4	0.10	2.68	1	69.3 ± 58.5	57.0 ± 52.7	0.30	1.05	1
3rd grade	25.2 ± 64.5	13.0 ± 8.9	0.55	0.35	1	46.0 ± 53.3	37.3 ± 24.9	0.97	0.01	1
4th grade	9.3 ± 5.1	15.8 ± 22.3	0.46	0.54	1	71.5 ± 90.6	69.2 ± 67.6	0.86	0.03	1
5th grade	12.0 ± 4.4	12.0 ± 8.1	0.26	1.24	1	36.4 ± 23.2	50.7 ± 28.3	0.07	3.23	1

Table 6.

Friedman Test Circle Size Tracing Versus Drawing Comparisons.

	Circle size comparison
Grade	Tracing	Drawing	p-value	χ²	d.f.
1st grade	M = 45.2 mm SD = 7.7 mm	M = 43.8 mm SD = 11.1 mm	0.19	1.66	1
2nd grade	M = 47.8 mm SD = 9.2 mm	M = 45.2 mm SD = 9.7 mm	0.17	1.8	1
3rd grade	M = 48.7 mm SD = 5.5 mm	M = 45.3 mm SD = 10mm	0.3	1.07	1
4th grade	M = 49.3 mm SD = 4.9 mm	M = 46.1 mm SD = 10mm	p < 0.05	6.43	1
5th grade	M = 49.4 mm SD = 1.1 mm	M = 44.4 mm SD = 10.7 mm	0.08	3.0	1

Note. Only 4th graders showed, statistical differences in circle size between tracing and drawing.

Regarding results for any differences between right-handed and left-handed students, there were no significant laterality differences for CV among 1st graders (drawing χ²(1) = 0.05, p = 0.82; tracing χ²(1) = 0.25, p = 0.61), 3rd graders (drawing χ²(1) = 0.01, p = 0.94; tracing χ²(1) = 0.32, p = 0.57) or 4th graders (drawing χ²(1) = 0.22, p = 0.63; tracing χ²(1) = 1.28, p = 0.25). For speed, no significant differences were found among 1st graders (drawing χ²(1) = 0.84, p = 0.36,; tracing χ²(1) = 0.50, p = 0.58), 3rd graders (drawing χ²(1) = 0.32, p = 0.57; tracing χ²(1) = 1.76, p = 0.18) or 4th graders (drawing χ²(1) = 0.38, p = 0.54; tracing χ²(1) = 1.62, p = 0.20). Laterality differences were not evaluated for the 2nd and 5th graders due to the small number of left-handed participants in those grade groups.

Discussion

This study investigated the development of drawing and tracing skills in elementary school children. Mostly as expected, with the exception of the 1st graders, we found no correlation between the students’ proficiencies in drawing and tracing. As expected, we observed an age-related improvement for both tracing and drawing across development. Most prominent differences were evident between the 2nd (ages 7–8) and the 3rd (ages 8–9) graders for tracing, with 3rd graders more proficient. For drawing, even though there were no significant consecutive grade performance improvements, general performance improvements with age were apparent, suggesting that drawing improvement is more gradual, compared to tracing improvement. We found no sex differences in these skills, confirming previous findings with simple drawing tasks (Blank et al., 1999). In terms of execution, we found a high correlation for speed between tracing and drawing from the 1st to the 3rd grade, but not for the 4th and 5th grades. Moreover, similarly to accuracy results, also for speed, most prominent differences were evident between the 2nd and the 3rd graders for tracing, whereas no significant differences were found between consecutive grades for drawing. Finally, speed and accuracy correlations increased with age for both tracing and drawing, with moderate to high correlations from the 3rd grade. Taken together, both the reduction in speed (Figure 4) along with the decrease in CV seen with age (Figure 3), go in line with what would be expected from a speed accuracy tradeoff, meaning a reduction in speed along with an increase in accuracy (Heitz, 2014). There is an inverse relationship between speed and accuracy known as the speed-accuracy trade off (Heitz, 2014). Interestingly, in this study, this trend was more evident from the 3rd grade onwards, when performances tend to become slower for both tracing and drawing and after which the speed-accuracy tradeoff shifted toward more accuracy with age. Though it might be considered somewhat counter-intuitive that the older children became, the slower their performances were (Rothenberg-Cunningham & Newell, 2013), a shift toward an accuracy emphasis helps explain this phenomenon.

Our finding of a moderate correlation between drawing and tracing performance among 1st graders may indicate that, for children of this age, fine motor development is still too immature and limited to be associated with different performances on tasks of this kind. In fact, the corticospinal tract, fundamental for movement execution, undergoes a rapid maturation process up to the age of 10, with more rapid changes occurring at younger ages (Fietzek et al., 2000; Müller et al., 1991). Also, evidence from corticospinal tract lesions in clinical cases illustrates the importance of the integrity of the corticospinal tract for movement dexterity (Bleyenheuft et al., 2007; Duque, 2003). Therefore, considering the maturation pattern of the corticospinal tract, it is very likely that the younger subjects in this study were more limited in their motor output. Indeed, writing control between the ages of 5–7 years is characterized by a shift from an inability to use sensory feedback to motor control that is mainly based on visual feedback (Palmis et al., 2017). The 1st graders in this study included children between the ages of 6–7 years, falling within this period of shifting toward a more visual oriented motor control. As such, it is possible that the moderate correlation we observed between tracing and drawing for children of this age was due to this increased shared visual reliance for drawing and tracing performances. At older ages, other cognitive processes help differentiate these performances.

Interestingly, improvement in tracing, compared to drawing, was relatively rapid. The improvement pattern for tracing across consecutive grades fits very well with previously reported results for children’s handwriting (Palmis et al., 2017). Specifically, greater differences in writing skills are expected between the ages of 7–10 years, a suspected turning point toward a more concrete representation of motor movement that is less reliant on immediate visual feedback (Palmis et al., 2017). Accordingly, our study revealed that the most significant differences between tracing abilities were between 2nd (ages 7–8) and 3rd (ages 8–9) graders.

Though both tracing and drawing utilize the same effectors, the cardinal difference between drawing and tracing is the presence of an external template, reducing the need for a mental representation of the figure being drawn. Since any deviation from the template is readily evidenced when a template is present, the template favors an external focus (i.e., on the movement effect) during performance (Marchant, 2010; Wulf, 2007; Wulf & Lewthwaite, 2010). In fact, it has been argued that the mere presence of a target during dart throwing may facilitate an external focus (Marchant et al., 2007; Wulf, 2013). It should be noted that when tasks are more automatic in nature or relatively simple, the clear benefit of external focus may not be readily observable (Wulf, 2013). This may explain why the effect was less prominent in adults (Cohen et al., 2018) who are likely to have both a more automatic control of writing instruments and a more readily available mental representation of the figure being drawn. However, the lack of automatic processes does not guarantee employment of external focus. Past researchers have shown that participants of similar age with different skill levels benefit from internal and external foci differently, with the less skilled participants adopting the former (Castaneda & Gray, 2007). In addition, it has been argued that when automatic processes are lacking, for example in novice performers, a more conscious control might be necessary in order to avoid gross performance errors (Kal et al., 2015). Therefore, drawing by young children, for which there is both no visual anchor for the task and an undeveloped automatic motor execution process in the performer, is likely to elicit a shift in attention toward a more internal focus. As the internal focus is known to cause only moderate performance improvement compared to an external focus (Wulf, 2007), we should expect that drawing performances would improve more gradually. On the other hand, it should be considered that adults participants present the necessary maturation to perform the task, consequently, any differences found between participants could be attributed to differences in skill level. This is not the case for the present study in that, if maturation is not complete yet, then the task might quantify maturational rather than skill differences.

Beyond the possible contribution of an external focus when comparing tracing to drawing, there may be other factors responsible for the trend we observed for the more rapid changes in tracing skills. In fact, internally and externally driven motor movements are thought to involve functioning in different brain regions. The basal ganglia are thought to play a prominent role in internally cued movements, while the cerebellum is considered to be an important brain activation region for externally cued movement (van Donkelaar & Staub, 2000; van Donkelaar et al., 1999). More recently, greater involvement of the supplementary motor cortex was found to be relevant for internally guided tasks, whereas greater premotor cortex involvement was primary during visually guided tasks (Mushiake et al., 1991). Surprisingly, when cerebral activation patterns for drawing and tracing tasks have been directly compared, basal ganglia and cerebellar activity did not differentiate tracing from drawing in the expected manner; drawing appeared to recruit areas that were more typically associated with cognitively demanding tasks, such as attention and memory (Gowen & Miall, 2007). Therefore, given known regional differences in brain maturation patterns (Toga et al., 2006) suggesting specifically that brain areas related to more advanced functions mature later (some in late adolescence) than those related to more basic functions (Gogtay et al., 2004), it is likely that later maturing brain areas that are more involved in drawing compared to tracing help account for the rate of improvement differences we observed in the performances of these two tasks among different aged children. This idea gains further support from others’ demonstrations that default networks of the brain (i.e., regions of decreased activity during goal oriented tasks) are sparsely functionally connected at age 7–9 years, and only later become functionally interconnected (Fair et al., 2008). This maturation pattern is consistent with our observation that consecutive grade performance differences for tracing were greatest between 2nd and 3rd grade.

Limitations and Directions for Future Research

While it is important to consider that, on average, our participants’ performances did not align with typical adult performances, some of our participants did reach an adult level of performance (some even as early as the first grade). These individual performances may have been due to other factors that were not considered in this study, including, for example, the participant’s general intelligence quotient (Smits-Engelsman & Hill, 2012), socioeconomic status (Klein et al., 2016), and/or specific fine motor training (Costa-Giomi, 2005), all of which might influence individual motor abilities. A failure to have examined and analyzed these and many other variables represents a limitation, but the results of this study provide a clear and congruent image of the developmental patterns for separate component skills of fine motor control.

Among other limitations of this study, we did not specifically control for the circle size being drawn or traced as we wished to avoid conditioning participants prior to their execution of the drawings and tracings. Our instructions to draw “medium sized” circles were admittedly ambiguous, as they were only intended to help avoid having participants draw circles that were too small. Though, we encountered some cases in which the differences in radii between participants’ drawings were apparent, they were not large, and the average radius difference was between 1–4 mm, with the drawn circles generally smaller than the traced template.

Among other limitations of this study, was our choice to not control for the participant’s speed of execution, as the study was concentrated mainly on the accuracy of performance. In fact, the instructions given for the task were those of drawing/tracing as precisely as possible, which is considered a common manipulation method in speed-accuracy tradeoff paradigms (Heitz, 2014). Though, for lengthy tasks, such as those consisting of serial repetitions, participants may modify their behavior only initially and later would settle into a distinct mode, favoring either speed or accuracy (Heitz, 2014), the task in this study consisted of a single drawing and tracing, with a 1-minute interval between them. This, along with the instruction (i.e., draw/trace as precisely as possible), greatly reduces the possibility of subjects settling in to distinct patterns. That being said, as the focus of this present study was that of performance accuracy, the results provided for specific speed accuracy tradeoff here may be only partially representative, and could be better examined in future studies. Also, we sought to develop and use a simple paper and pencil tool (for data collection, which could be scanned for later analysis) that could be widely applied for estimating fine motor control without the additional constraints of controlling for size and execution speed future researchers might better address these various methodological concerns.

Conclusions

Assessing fine motor control during development is important for both asserting normal developmental patterns and identifying delays or incongruent development. In this study we showed that fine motor control can be quantified in school age children using very simple tasks of drawing and tracing. Our comparative results for tracing by children of varied ages align with previous findings regarding motor and brain development patterns. Furthermore, results for drawing provide additional insights regarding the development of internally driven movements and mental representations in children of different ages. Certainly, there would be a need for extensive validity and reliability studies, such as comparison of results obtained with this approach with consolidated tests used for quantification of fine motor control, prior to implementation of this novel procedure as an evaluation tool. Though our suggested approach may not substitute for a thorough examination of individual children’s motor skills during development, we believe that simple and economic tools of this kind may be well suited for widespread implementation and population screening.

Footnotes

Acknowledgments

We would like to thank Erica Orsi for all her help in organizing and conducting the experiments.

Author Biographies

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Erez J. Cohen

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