A Point-Light Display Model for Teaching Motor Skills to Children With Autism Spectrum Disorder: An Eye-Tracking Study

Abstract

People with autism spectrum disorder (ASD) have limitations in their attention and working memory that affect their motor learning. The aim of current study was to compare point-light display (PLD) to video observation as instructional models for teaching motor skills to children with ASD versus typically developing (TD) children. We randomly assigned 24 children with ASD aged 6-17-years-old and 24 age paired typically developing (TD) children to four groups: (a) ASD-Video, (b) ASD-PLD, (c) TD-Video, and (d) TD-PLD. After twenty training blocks (200 trials), all participants entered into late retention and transfer testing. We recorded all participants’ visual gazes when observing each PLD and Video condition. Both PLD groups had better performance in the acquisition phase, and on retention and transfer tests. Also, gaze recordings revealed that children with ASD paid more attention to relevant demonstration points in the PLD than in the video condition. We discuss possible mechanisms and implications of these findings.

Keywords

gaze recording motor learning information load fixation observational learning

Introduction

Observational demonstration is one of the most common instructional methods for teaching motor skills (D’Innocenzo et al., 2016; Williams & Hodges, 2005). The process of adapting an observer’s behavior in accordance with another person’s action has been described as observational learning (OL) (Bandura, 1986). At times the terms, ‘observational learning’ and ‘modeling,’ have been used as synonyms for imitation. However, OL is characterized by constant changes in a person’s actions (Causer et al., 2013). The processes underlying OL efficacy have been studied in recent decades because of research-supported advantages of OL for learning motor skills (Ste-Marie et al., 2012). Bandura’s Social Cognitive Theory (Bandura, 1986; Bandura & McClelland, 1977) and Scully and Carnegie's (1998) ecological approach are both based on a direct perception perspective and are the most influential OL models. While the conceptual frameworks of these models differ, both confirmed the essential role of the attentional process for efficient OL. According to Bandura’s (1986) observational learning theory, four underlying learner functions determine OL effectiveness: (a) paying attention to important (relevant) information; (b) showing retention of captured information; (c) accurately reproducing the desired behavior; and (4) enough motivation for reproduction of the observed action.

Although people with autism spectrum disorder (ASD) are characterized by impaired or deficient social ability, communication problems, and stereotypical behaviors (American Psychological Association [APA], 2013), they also have impaired attention skills (Chevallier et al., 2012; 2015) and show delayed motor skills (Arabameri & Sotoodeh, 2015). While there is an extensive body of literature showing that people with ASD are highly interested in attending to certain categories of objects (Boyd et al., 2007; Sasson & Touchstone, 2014; Turner-Brown et al., 2011), ASD-related attentional problems are associated with difficulty imitating or encoding relevant information from demonstrations (Vivanti et al., 2014). Given Bandura’s emphasis on paying attention to a model as essential to OL (Bandura, 1986; Bandura & McClelland, 1977), these ASD-related attentional difficulties may interfere with OL when used for people with ASD, especially for tasks that have high attentional demands (Craig et al., 2016; Guillon et al., 2014) that are apt to elicit distractibility among children with ASD, perhaps diminishing their learning (Hanley et al., 2017; Hoogerheide et al., 2016).

Johansson (1973) developed the ‘point-light technique’ that makes only a model’s major joints visible to observers. Using this method, researchers can isolate and show observers only the most relevant transformational movement cues, avoiding the presentation of many distracting irrelevant structural cues conveying unnecessary information about the model’s shape, size, or characteristic features. Thus, point-light display (PLD) demonstrates those relative motion components that provide essential information in biological motion perception, helping to make the modeling process more efficient. The relative motion refers to the motion of individual elements of a configuration relative to each other (e.g., the movements of the wrist and shoulder in relation to each other and in relation to the trunk and lower limbs) (Scully & Carnegie, 1998). Furthermore, seductive details presented in normal demonstrations, like background color and other characteristics of the model and the environment that could easily overload people with ASD with too much information, are removed in PLDs (Hayes et al., 2016).

A comparison of motor skill learning among groups of typically developing (TD) participants who watched PLDs or more traditional Video Modeling (VM) have shown us how perceived relative motions modulate motor learning (Al-Abood et al., 2001; Hayes et al., 2007). The underlying hypothesis of these studies has been that, if relative motion information is sufficient for perceiving and reproducing the action, PLDs should be as effective as VM (Rodrigues et al., 2010). PLDs have been used as a useful method for teaching simple motor tasks like a bowling action (Hayes et al., 2007), complex motor tasks such as gymnastic routines (Scully & Newell, 1985), lumbar stabilization (Pellecchia & Garrett, 1997), crunch start (A. Farsi et al., 2016) and the baseball pitch (Ghorbani & Bund, 2016). However, no study has yet used PLDs to model motor skills for people with ASD.

Our recent studies revealed that people with ASD learn motor skills taught by either live or video models in the same way (Taheri-Torbati & Sotoodeh, 2019). Other research has shown that the effectiveness of demonstrations for learning motor skills depended on the learner’s ability to direct their visual attention to the relevant cues (D’Innocenzo et al., 2016). From this viewpoint, people (and perhaps especially children) with ASD may have problems benefitting from OL for novel and complex motor skills, because they may be unable to focus on the most relevant elements of the demonstration and fail to gather needed information (Takarae et al., 2014), so that, with typical video modeling, they may become distracted by details that are not relevant to the action. We hypothesized that demonstrating target action using PLD would help people with ASD attend to the relevant motion cues. Using minimized relative motion in PLDs to constrain the action in OL, we expected superior learning from people with ASD with PLD in comparison to VM. More specifically, in the current study, we investigated the efficacy of decreased irrelevant information by PLD to lead people with ASD to give their visual attention to the most relevant information and improve their motor skill learning. The current study had two main goals. First, we aimed to decrease the amount of visual irrelevant information in comparisons of visual searches by PLD versus VM. Second, we examined whether OL could be facilitated for children with ASD by manipulating the nature of information presented and then comparing participants’ performance accuracy after training sessions and at retention testing.

Method

Participants

We first conducted a statistical power analysis to estimate a required participant sample size. The effect size for previous relevant studies ranged from d = 0.30 (Emanuel et al., 2008) to 1.78 (Tse, 2019). We assumed an effect size that was the mean value (d = 1.04) of these studies, and we assumed a 5% level of significance, and statistical power of 90%. We calculated a required sample size of 36 participants (nine in each of four groups) using G*Power 3.1 software (Faul et al., 2007). Accordingly, we recruited 24 participants with ASD (three girls) aged 6-17 years and 24 age-matched typically developing (TD) participants (three girls) for this study.

All participants in the ASD group had previously received a clinical diagnosis of ASD according to DSM-5 diagnostic criteria (APA, 2013) and were scored positive for ASD from the Autism Diagnostic Interview-revised (ADI-R) (Rutter et al., 2003) administered by a child psychiatrist or psychologist. We used the Leiter International Performance Scale (Levine & Leiter, 1989) to test participants intellectual ability, and all participants obtained IQ scores above 70 (ASD: M_IQ = 97.12, SD = 7.47; TD: M_IQ = 102, SD = 6.17). All participants were right-handed and had normal or corrected to normal vision. Other exclusion criteria for all participants were: dyslexia, severe behavioral problem, uncontrolled seizure, history of cerebral palsy, tuberous sclerosis, schizophrenia, and/or any other neurological or psychiatric disorders. We obtained informed consent from parents of all participants after a complete study description. The protocol for the study was approved by our local ethical committee.

Procedure

Motor Skill Task To Be Learned, Model, and Instructions

An expert male, aged 30 years, acted as the model. The task involved an under-arm throw of a bean bag, a task used in the Movement Assessment Battery for Children-2 (MABC-2; Henderson, et al., 2008). The target was a red circle with a 0.2-meter diameter that was placed three meters away from the throwing line. The bean bag had a mass of 150 grams, and it was 5 × 5 centimeters (cm) long. Throwing outcome scores served as the dependent variable for the task. The distance from the center of the target to the bean bag’s landing point was calculated (radial error) for each throw, as the outcome score. The model’s throw was recorded in the sagittal plane using a digital camera (Nikon D-3300) to make a video model or VM. To produce the PLD condition, we used 13 reflective markers attached to the model’s head, shoulder, elbows, wrists, hips, knees, and ankles (see Figure 1), and we tracked them using SIMI motion analysis (http://www.simi.com/en/). Data were then exported and converted to PLD animation using motion kinematic and kinetic analyzer (Mokka) software (http://biomechanical-toolkit.github.io/mokka/index.html). The PLD consisted of white dots against a black background, and no structural information was available.

Figure 1.

Marker Placement on Main Joints of Model.

Participant Pre-Testing, Training, and Post-Testing

We recorded the participants’ gaze behavior using eye-tracking glasses (SMI ©). Participants performed 10 bean bag throw trials at pre-testing, and we recorded their radial errors and assigned participants randomly to PLD or VM groups. All participants performed the task with their non-dominant hand to eliminate the effect of their previous throwing experiences. After pre-testing, the participants engaged in 20 training blocks (10 trials for each block) in which they observed the model (by PLD or VM, depending upon their group assignment) followed by practice in two consecutive training days. The participants had 2-minute rest periods between each block. The participants initiated each trial with a ‘ready’ command given by the experimenter before the ‘throw’ command. In each block, knowledge of performance was provided after one trial for each participant in order to motivate them for performing the task. Before each block, participants watched their model five times on a 14” laptop LCD (HP, DV4). All participants were instructed to pay attention to the demonstrated model and use the available information to help perform the task and improve their performance. Then all participants performed a post-test a retention test (one week later), and a transfer test was administered to measure their learning. For the transfer test, the participants were asked to throw from a distance of four meters, five minutes after the retention test.

Gaze Recording

During the time participants observed the model, participants were seated in a quiet room, 70 cm from a computer monitor. A fixation cross (2 × 2 cm) was presented at the center of the screen for 1500 milliseconds (ms), followed by a model (Video or PLD) displayed up to four times (2000 ms per instance, see Figure 2A). Each stimulus was repeated four times in each trial, and each trial repeated three times in random order to decrease the participants’ ability to predict the stimuli. After watching the stimuli, the examiner asked children to name and perform the movement to ensure that they had no imitation problem. Participants’ gaze behavior was captured using a mobile eye-tracking system (SensoMotoricInstruments ETG-2 binocular mobile eye-tracking www.smivision.com). Eye movements were recorded by two small cameras in the septum of the glasses and matched to the video-recordings from a scene camera located in front of the glasses (Vabalas & Freeth, 2016). A three-point calibration procedure was used. Eye movements (fixations, saccades, and blinks) were defined using the standard algorithms of the manufacturer. Eye-tracking data was further processed with the SMI BeGaze 3.7 software (Vabalas & Freeth, 2016). Figure 2B presents the Area Of Interests (AOIs) were the throwing arm (broadly defined as shoulder, elbow, and wrist), head, body (trunk, other hand, and lower limb), and Background (any other places of the screen).

Figure 2.

A: Stimuli Presentation and Gaze Recording. B: AOI Definitions in Both PLD and Video Conditions.

Data Analysis

To analyze throwing accuracy, we used means and standard deviations of each participant’s radial error measurements for each block to determine the effect of different demonstration methods (PLD vs. VM) on movement outcomes. We recorded data for the 20 training blocks, one retention, and one transfer block for statistical analysis. We used a four Group (PLD-ASD, Video-ASD, PLD-TD, and Video-TD) × 11 Block (pre-test, 2, 4, 6, 8, 10, 12, 14, 16, 18 and 20) repeated measure ANOVA to analyze data during the acquisition phase. We used one-way ANCOVA to compare the performance of the different groups on the retention and transfer tests, with the baseline (first block of acquisition) performance entered as a co-variate. A Tukey post-hoc test was used for any significant main effects.

To analyze participants’ gaze behavior, we first calculated the proportion of time participants spent fixating their gaze on the throwing arm, head, body, and background AOIs (dwell time) and the number of participants’ saccades that landed on these areas (fixations). We used these values for each condition and each participant. We then used a two-way mixed ANOVA to analyze Groups (ASD/TD) × Condition (PLD/Video) and AOIs (Throwing arm, Head, Body, and Background) on the proportion of dwell time and fixations to AOIs.

Results

Throwing Accuracy

Acquisition

During acquisition, a repeated measure ANOVA revealed a significant effect of time for radial error: Greenhouse–Geisser adjusted F_{(5.58, 245.85)} = 39.41, p < .001, η² = .47, such that all groups decreased their radial error (improving throwing accuracy) across training blocks. There was also a significant main effect of Group, F_(1,44) = 9.57, ^ < .001, η² = .39. Results of the Bonferroni post-hoc test revealed that there was a significant difference between TD-PLD and ASD-PLD (p < .001) and ASD-Video (p < .001). The interaction of Group × Block was significant, F_{(16.76, 245.85)} = 2.77, p < .001, η² = .15. Thus, different groups had different improvement patterns during the acquisition phase. Separate t-tests revealed that all groups showed improvement from pre-test to the last block of acquisition [ASD-PLD: t₍₁₁₎ = 10.81, p < .0001; ASD-Video: t₍₁₁₎ = 5.01, p < .0001; TD-PLD: t₍₁₁₎ = 11.30, p < .0001; TD-Video: t₍₁₁₎ = 9.43, p < .0001].

Retention

At retention testing, an ANCOVA revealed a significant difference between groups in throwing accuracy (F_(4,43) = 23.34, p < .0001, η² = .62). Further pairwise comparisons using Tukey HSD revealed that the ASD-PLD group (M = 33.5, SD = 9.17) performed better than did the ASD-Video group (M = 42.9, SD = 7.31) at retention testing (p < .0001); however their performance was not better than the TD-PLD group (M = 19.75, SD = 4.02; p = .024). There was also a significant difference between the ASD-Video and TD-Video groups (p < .0001) and the TD-PLD (p < .0001) indicating that participants in the ASD-Video group had larger errors on the retention test than the two TD groups. However, the difference between the ASD-PLD and TD-Video groups (M = 29.33, SD = 9.36) was not significant (p>.05).

Transfer

For the transfer test, the ANCOVA revealed a significant difference between groups (F(4,43) = 7.39, p < .0001, η² = .34). Two by two post-hoc analyses using Tukey HSD tests showed a significant difference between the ASD-Video and TD-Video groups (p = .012) and between the ASD-Video and TD-PLD groups (p < .001), indicating that participants in the ASD-Video group had larger errors on the transfer test than the two TD groups. However, there was also a significant difference between the ASD-PLD and TD-PLD groups (p = .004), indicating that TD participants had better performance than the ASD groups (Figure 3).

Figure 3.

Error Scores on Blocks During Acquisition, Retention, and Transfer for Different Groups. Note: error bars indicate standard errors.

Visual Attention (Gaze Analysis)

Figure 4 illustrates the percentage of dwell time for each AOI of participants in the ASD and TD groups for each PLD and Video Condition. Both ASD and TD groups in the PLD condition gave more visual attention to the Throwing Arm than to the Body, Background, and Head AOIs. However, in the Video condition, ASD and TD groups showed a different visual attention preference pattern. The TD group paid better attention to the Head, Body, Throwing arm, and Background, while the ASD group paid better attention to the Background, Throwing arm, Head, and Body.

Figure 4.

Percent of Dwell Time in Different Groups and Conditions.

Fixations

A 2 Group (ASD and TD) × 2 Condition (PLD and Video) model of ANOVA was used for Fixation and Percent of Dwell time data in each Area of Interests (AOIs). For, Body AOI results of ANOVA revealed a significant main effect of group (F_(1,44) = 147.63, p = .001, η² = .77). That means TD participants had more fixations (M = 10.752, SD = 1.1) than participants with ASD (M = 7.45, SD = .88). Also, the interaction of Group in Condition was significant (F_(1,44) = 8.54, p = .005, η² = .16). Further analysis revealed a significant difference between ASD-PLD and TD-PLD (p < .001), and between ASD-Video and TD-Video (p < .001). However the main effect of Condition was not significant (F_(1,44) = .21, p = .64) (Figure 5A). Another ANOVA performed for Head AOI revealed that the main effect of the Group was not significant (F_(1,44) = .59, p = .59). However the main effect of the Condition was significant (F_(1,44) = 326.05, p < .001, η² = 0.88), which means that participants had more fixations to the Head AOI in the Video condition (M = 7.91, SD = 1.28) than the PLD condition (M = 2.25, SD = 1.07). Also, the interaction of Condition in the Group was significant (F_(1,44) = 10.15, p = .003, η² = .18). Further analysis revealed that there was a significant difference between ASD-PLD and ASD-Video (p < .001) and between ASD-Video and TD-Video (p = .05) (Figure 5B). For Throwing arm AOI the main effect of group was not significant (F_(1,44) = .27, p = .601). However the main effect of condition was significant (F_(1,44) = 180.51, p < .001, η² = .80), which means participants had more fixations on the PLD (M = 6.16, SD = 2.29) than the Video condition (M = 11.91, SD = 2.32). Also, the interaction of Group in Condition was significant (F_(1,44) = 159.89, p < .001, η² = .78). Further analysis revealed that there was a significant difference between ASD-PLD and ASD-Video (p < .001), between ASD-PLD and TD-PLD (p < .001), and between ASD-Video and TD-Video (p < .001) (Figure 5C). For Background AOI results of ANOVA revealed a main effect of Group (F_(1,44) = 747.88, p < .001, η² = 0.94), that means participants with ASD had more fixations (M = 10.37, SD = 5.71) than TD participants (M = 3.62, SD = 5.48). Also, the main effect of condition was significant (F_(1,44) = 943.94, p < .001, η² = .95), which means that participants had more fixations in the Video condition (M = 10.79, SD = 5.31) than in the PLD condition (M = 3.20, SD = 1.81). Furthermore, the interaction effect of Group in Condition was significant (F_(1,44) = 201.07, p < .001, η² = .21). Further analysis revealed that there was a significant difference between ASD-PLD and ASD-Video (p < .001), between ASD-PLD and TD-PLD (p < .001), and between ASD-Video and TD-Video (p < .001) (Figure 5D).

Figure 5.

The Number of Fixations on Each AOI: (A) Body AOI, (B) Head AOI, (C) Throwing arm AOI, and (D) Background AOI.

Percent of Dwell Time

A 2 Group (ASD and TD) × 2 Condition (PLD and Video) model of ANOVA was used for Fixation and Percent of Dwell time data in each Area of Interests (AOIs). For, Body AOI results of ANOVA revealed a significant main effect of group (F_(1,44) = 2588.12, p < .001, η² = .98). That means TD participants had a longer dwell time (M = 28.16, SD = 8.3) than participants with ASD (M = 12.7, SD = 1.19). Also, the main effect of Condition was significant (F_(1,44) = 774.87, p < .001, η² = .94), which means participants had longer dwell time on PLD (M = 26.66, SD = 11.86) than Video (M = 16.20, SD = 4.11). Furthermore, the interaction of Group in Condition was significant (F_(1,44) = 643.54, p < .001, η² = .93). Further analysis revealed a significant difference between ASD-PLD and TD-PLD (p < .001), and between ASD-Video and TD-Video (p < .001) (Figure 6A). Another ANOVA performed for Head AOI revealed that the main effect of Group was significant (F_(1,44) = 198.95, p < .001, η² = .81). That means that TD participants had a longer dwell time (M = 13.83, SD = 11.36) than ASD participants (M = 9.37, SD = 6.52). Also, the main effect of Condition was significant (F_(1,44) = 3021.76, p < .001, η² = 0.98), which means that participants had longer dwell time in the Video condition (M = 20.29, SD = 4.84) than the PLD condition (M = 2.91, SD = 1.37). Furthermore, the interaction of Condition in Group was significant (F_(1,44) = 229.81, p < .001, η² = .83). Further analysis revealed that there was a significant difference between ASD-PLD and ASD-Video (p < .001) and between ASD-Video and TD-Video (p < .001) (Figure 6B). For Throwing arm AOI the main effect of group was significant (F_(1,44) = 368.44, p < .001, η² = .89), which means participants with ASD had longer dwell time (M = 35.79, SD = 18.55) than TD participants (M = 29.87, SD = 10.20). Also, the main effect of condition was significant (F_(1,44) = 8300.72, p < .001, η² = .99), which means participants had longer dwell time on PLD (M = 46.87, SD = 7.30) than Video (M = 18.79, SD = 1.38). Furthermore, the interaction of Group in Condition was significant (F_(1,44) = 701.95, p < .001, η² = .94). Further analysis revealed that there was a significant difference between ASD-PLD and ASD-Video (p < .001), between ASD-PLD and TD-PLD (p < .001), and between ASD-Video and TD-Video (p < .001) (Figure 6C). For Background AOI results of ANOVA revealed a significant main effect of Group (F_(1,44) = 1148.94, p < .001, η² = 0.96), that means participants with ASD had longer dwell time (M = 18.91, SD = 11.12) than TD participants (M = 8.75, SD = 5.76). Also, the main effect of condition was significant (F_(1,44) = 3234.78, p < .001, η² = .98), which means that participants had longer dwell time in Video condition (M = 22.04, SD = 7.96) than in the PLD condition (M = 5.62, SD = 2.63). Furthermore, the interaction effect of Group in Condition was significant (F_(1,44) = 306.37, p < .001, η² = .87). Further analysis revealed that there was a significant difference between ASD-PLD and ASD-Video (p < .001), between ASD-PLD and TD-PLD (p < .001), and between ASD-Video and TD-Video (p < .001) (Figure 6D).

Figure 6.

Percent of Dwell Time for Each AOI: (A) Body AOI, (B) Head AOI, (C) Throwing arm AOI, and (D) Background AOI.

Discussion

The primary aim of the current study was to examine the effect of removing irrelevant information on motor learning when demonstrating a motor skill (throwing a bean bag with the non-dominant hand) to children with ASD by having them observe models via a point-light display (PLD) versus traditional video modeling (VM). We hypothesized that the PLD method would remove irrelevant information and result in better motor learning in comparison to demonstrating through real videos, especially for children with ASD versus typically developing (TD) children. Our results supported our hypothesis because participants with ASD learning through PLD performed better than participants with ASD learning through VM in the acquisition phase, and at retention and transfer testing.

It seems that the PLD model supplied the necessary topological properties of relative motion to the participants with ASD (Cutting & Proffitt, 1982; Sotoodeh et al., 2019; Sotoodeh et al., 2021). These results are in agreement with the Visual Perception Perspective (VPP) of observational learning (Scully & Newell, 1985). According to VPP while observing a movement, the visual system perceives relative motion information directly to reproduce it in the future. However, participants in the TD group didn’t show any learning differences between PLD and VM training conditions. These findings are in accordance with the results of Ghorbani and Bund (2016), Horn et al. (2005), and Breslin et al. (2005), who found no superiority for PLD over VM in OL among typically developing participants.

Our results reveal that although highlighting relative motion information within a modeled demonstration of a motor skill is not necessary for motor learning among TD children, it may have an important role in guiding children with ASD toward better learning. The main reason for these results may be a reduced cognitive load of stimuli presented, permitting these participants to better transfer what they observed from working memory (WM) to long-term memory (LTM). Since, participants with ASD have limitations in their WM capacity (Vogan et al., 2014), the PLD model benefitted them more, in comparison to TD children who do not have this WM problem. PLDs reduced irrelevant information by highlighting relative motion information; PLDs helped participants with ASD ignore task-irrelevant information (model characters, familiarity with model) and enhanced their reception of task-relevant information (relative motion information). Removing task-irrelevant information may be essential for people with ASD due to their WM difficulties related to abnormalities in the prefrontal cortex (Vogan et al., 2014). Since WM has an important role for learning, for social ability (Dennis et al., 2009) and for many complex cognitive tasks (Engle et al., 1999; Vogan et al., 2014), using PLD in observational learning to demonstrate target motor skills for people with ASD may have an important training advantage.

Several studies revealed that seductive extraneous information affects learner’s perceptual; processing by inviting their eye movements toward various specific stimuli (Korbach et al., 2016; Mayer, 2010). Our gaze analysis results revealed that children with ASD in the PLD versus VM condition paid three times more attention to the most relevant AOI (PLD: Throwing arm = 68%; VM: Throwing arm = 23%). In the VM condition, children with ASD paid more attention to background AOI (40%). Interestingly, gaze analysis showed that TD participants also spent a higher percentage of time attending to the throwing arm in the PLD condition (49%) than in the VM condition (24%). For individuals with WM difficulties, paying attention to seductive but extraneous details seems to distract the attention and cause a relatively superficial processing of relevant information (relative movement) that then disrupts the learning process. The ASD group showed more fixation and dwell time on the throwing arm in the PLD condition than did the TD participants.

Limitations and Directions for Future Research

The results of the current study must be viewed in the context of several limitations. First, this study was completed by participants within a limited age range, restriciting the generalizability of the results to other age ranges. Second, since our study was the first study using PLDs to teach motor skills to children with ASD, we chose simple under-arm throwing as our main task. Future studies might address different tasks with different difficulties. Also, future studies might give more attention to the throwing arm in the PLD condition to support our hypothesis that presenting instruction through a PLD model helps children with ASD by leading their visual attention to more relevant information and decreasing cognitive load associated with attending to excessive extraneous stimuli. Future studies might also test our findings in other age ranges, with other motor skills, and among other domains of disabilities.

Conclusions

In summary, current findings showed that removing irrelevant modeling information for children with ASD who were engaged in observational learning by using PLDs rather than traditional videos assisted motor learning for children with ASD. These findings have significant implications for the observational learning of people with ASD and should trigger a great deal of further research in this regard.

Footnotes

Acknowledgments

The authors would thank all children that participate in the study and their parents. We also would thank Dr. Fred Paas for his help in shaping theoretical framework of the study.

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

Mohammad Saber Sotoodeh

Author Biographies

Mohammad Saber Sotoodeh has a PhD in Motor Behavior and works with people with developmental disorders since 2010. His main research areas are neuroscience of perception and action, observational learning and Autism Spectrum Disorders.

Hamidreza Taheri-Torbati is a full professor of motor behavior at Ferdowsi University of Mashhad, Iran.

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