Bridging the Perceptual-Academic Gap: How Infographics Enhance Basic Academic Skills by Improving Auditory and Visual Perception in Children with ASD

Bridging the Perceptual-Academic Gap: How Infographics Enhance Basic Academic Skills by Improving Auditory and Visual Perception in Children with ASD | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Bridging the Perceptual-Academic Gap: How Infographics Enhance Basic Academic Skills by Improving Auditory and Visual Perception in Children with ASD Ahmed Fadlallah Shalally, PhD, Mahmoud Aly Elsayed,, Dr Noha Mahmoud Arandas, This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8096304/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective Children with Autism Spectrum Disorder (ASD) often face significant academic challenges linked to underlying perceptual processing deficits. However, interventions that specifically leverage their unique perceptual profiles to foster academic growth remain underexplored. This study investigated the effectiveness of a novel, infographic-based training program designed to enhance visual and auditory perception skills and, consequently, improve basic academic skills (reading and mathematics) in children with ASD. Method A quasi-experimental one-group pretest-posttest-follow-up design was employed. The sample consisted of six children (4 males, 2 females) diagnosed with ASD, aged 6–8 years, enrolled in inclusive school settings. The intervention comprised a 16-week, researcher-developed program utilizing educational infographics. Participants were assessed using researcher-developed scales for visual perception, auditory perception, and a test of basic academic skills at three time points: before the intervention (pre-test), immediately after its completion (post-test), and one month later (follow-up). Data were analyzed using non-parametric Wilcoxon signed-rank and Friedman's tests. Results The analysis revealed statistically significant improvements from pre-test to post-test across all primary outcome measures: visual perception, auditory perception, and basic academic skills ( p < .05). The gains were substantial, indicating a strong and positive intervention effect. Furthermore, no statistically significant decline in performance was observed between the post-test and the one-month follow-up assessments, demonstrating the successful maintenance and sustained impact of the skills acquired. Conclusion The findings provide robust evidence that a targeted, infographic-based intervention is an effective tool for enhancing both foundational perceptual abilities and essential academic skills in children with ASD. By presenting information in a visually structured and perceptually aligned format, infographics can successfully bridge the critical gap between perceptual processing and academic learning. This study offers a practical, theoretically grounded approach for educators and clinicians to support the academic development of this population within inclusive environments. Special Education Visual Perception Auditory Perception Infographics Basic Academic Skills Autism Spectrum Disorder (ASD) Figures Figure 1 Figure 2 Figure 3 1. Introduction Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by persistent challenges in social communication and interaction, alongside restricted, repetitive patterns of behavior, interests, or activities (American Psychiatric Association [APA], 2022). With a rising global prevalence, now estimated by the Centers for Disease Control and Prevention (CDC) to affect approximately 1 in 36 children in the United States (Maenner et al., 2023), the educational and developmental needs of this population represent a critical area of focus for researchers and practitioners. While the core diagnostic criteria are well-documented, the secondary academic challenges faced by children with ASD often pose significant barriers to their success in inclusive educational settings. A substantial body of evidence indicates that these academic difficulties are not merely byproducts of cognitive or behavioral factors but are deeply rooted in fundamental differences in sensory processing and perception (Bolis & Schilbach, 2018 ; Mikkelsen et al., 2018). This phenomenon creates a foundational "perceptual-academic gap," where atypical processing of auditory and visual information obstructs the acquisition and application of basic academic skills, such as literacy and numeracy. The unique perceptual world of individuals with ASD is often explained through prominent theoretical frameworks, including the Weak Central Coherence (WCC) theory and the Enhanced Perceptual Functioning (EPF) model. The WCC theory posits that individuals with ASD exhibit a cognitive style biased toward detail-focused, local processing at the expense of integrating information into a coherent, global whole (Happé & Frith, 2006 ). This can manifest as an exceptional ability to spot details but a significant challenge in understanding the broader context, or "seeing the forest for the trees." Conversely, the EPF model highlights superior performance in simple or detail-oriented perceptual tasks, suggesting an enhancement in local processing (Mottron et al., 2006 ). While this detail-oriented style can be an asset in certain contexts, it often creates obstacles in academic tasks like reading comprehension, which requires integrating letter sounds into words and words into meaningful sentences, and mathematics, which demands understanding holistic concepts beyond rote calculation (Bullen et al., 2020 ; Tonizzi & Usai, 2024 ). These theoretical underpinnings suggest that effective educational interventions should not only present academic content but also structure it in a way that bridges this perceptual divide. Despite a growing recognition of the interplay between perception and academic achievement in ASD, a significant gap persists in the intervention literature. Many traditional educational strategies are designed for neurotypical learners and may inadvertently exacerbate the cognitive and sensory load on children with ASD (Keen et al., 2015 ). While interventions targeting academic skills exist, they often overlook the foundational perceptual deficits that impede learning. A systematic review by Alresheed et al. ( 2018 ) highlighted the need for more interventions that address academic-related skills with robust research designs. Furthermore, there remains a notable scarcity of research investigating tools specifically designed to accommodate the unique perceptual profiles of children with ASD as a direct pathway to academic improvement. This gap is particularly evident concerning the use of modern visual communication tools that are inherently structured and detail-oriented. This study proposes that educational infographics represent a novel and theoretically aligned tool to bridge this perceptual-academic gap. Infographics are visual representations of information, data, or knowledge intended to present complex information quickly and clearly (Dunlap & Lowenthal, 2016 ). Their inherent design principles align remarkably well with the perceptual strengths and challenges of children with ASD. By breaking down complex topics into discrete, visually organized chunks of information, infographics reduce cognitive load and cater to a detail-focused processing style (Aldalalah, 2021 ). The integration of text, icons, charts, and images leverages the visual learning strengths common in this population (Bidin & Omar, 2015) and aligns with Universal Design for Learning (UDL) principles by presenting information in multiple modalities (Carrington et al., 2020 ). This structured, predictable, and visually salient format can help children with ASD organize sensory input, direct their attention, and build connections between details and the overarching concept, thereby facilitating both perceptual processing and academic comprehension. Therefore, the present study aims to investigate the effectiveness of a targeted, infographic-based training program in enhancing auditory and visual perception skills and, consequently, improving basic academic skills (reading and mathematics) in primary school children with ASD in inclusive settings. The study is guided by the following primary hypotheses: Participation in the infographic-based program will result in statistically significant improvements in visual and auditory perception skills from pre-test to post-test. The improvements in visual and auditory perception will be associated with statistically significant gains in basic academic skills. The observed academic and perceptual gains will be maintained at a one-month follow-up assessment, indicating the sustained impact of the intervention. By providing empirical evidence for this novel intervention, this study seeks to offer a practical, theoretically grounded tool for educators and contribute to a deeper understanding of how to effectively support the academic success of children with ASD by addressing their core perceptual needs. 2. Literature Review 2.1 The Perceptual-Academic Nexus in Autism Spectrum Disorder Autism Spectrum Disorder (ASD) is a neurodevelopmental condition defined by core challenges in social communication and the presence of restricted, repetitive behaviors (American Psychiatric Association [APA], 2022). While these diagnostic criteria are central, the landscape of challenges for children with ASD extends profoundly into the academic domain. A persistent and significant body of research demonstrates a strong link between the unique sensory processing profiles of individuals with ASD and their academic outcomes (Marco et al., 2011 ; Robertson & Baron-Cohen, 2017 ). This connection is not incidental; rather, it forms a foundational "perceptual-academic gap," where atypical processing of sensory information creates a bottleneck for acquiring higher-order skills like literacy and numeracy. Difficulties in academic performance, therefore, are often not a primary cognitive deficit but a downstream consequence of a fundamental mismatch between the child's perceptual system and the demands of traditional pedagogy (Bolis & Schilbach, 2018 ; Jones et al., 2021 ). Understanding this nexus is paramount to developing interventions that are not merely palliative but genuinely transformative. 2.2 Atypical Visual Perception and its Academic Implications The visual world of a child with ASD is often qualitatively different from that of their neurotypical peers. Two dominant theories, Weak Central Coherence (WCC) and Enhanced Perceptual Functioning (EPF), provide a robust framework for understanding these differences. The WCC theory posits a cognitive style characterized by a bias towards processing local details at the expense of extracting global meaning or gist (Happé & Frith, 2006 ). This detail-focused bias means a child with ASD might excel at identifying a specific letter in a complex image but struggle to derive the overall meaning of a sentence. Complementing this, the EPF model suggests superior abilities in low-level perceptual tasks, such as detecting visual targets or discriminating patterns (Mottron et al., 2006 ). While this "perceptual signature" confers advantages in tasks requiring precision and detail (e.g., puzzles, visual search), it poses significant hurdles in academic contexts. Reading, for instance, is an inherently integrative process. It requires the rapid, holistic recognition of word shapes and the fluid integration of words into sentences to build meaning—a task that is fundamentally challenged by a piecemeal, detail-by-detail processing style (Evers et al., 2018 ). Similarly, mathematical reasoning often depends on grasping holistic concepts, such as the relationship between quantities, which can be obscured by an intense focus on individual numbers or symbols (Bullen et al., 2020 ; Tonizzi & Usai, 2024 ). Consequently, any effective academic intervention must acknowledge and accommodate this visual processing style, structuring information in a way that guides the learner from local details to global understanding, rather than assuming this integration will occur spontaneously. 2.3 Auditory Processing, Phonological Awareness, and Literacy Parallel to visual processing, auditory perception in ASD is also marked by significant heterogeneity, including both hyper- and hypo-sensitivities to sound (Gonçalves & Monteiro, 2023 ). These sensitivities can make a typical classroom, with its overlapping auditory stimuli, a source of profound sensory overload, impeding attention and learning. Beyond basic sensitivity, a more specific challenge lies in the domain of phonological awareness —the ability to recognize and manipulate the sound structure of spoken language. This skill is a cornerstone of literacy development and a robust predictor of reading success (Zylstra et al., 2023 ). Research consistently indicates that a subgroup of children with ASD demonstrates significant deficits in phonological awareness, impacting their ability to decode words (Aghaz et al., 2018 ; Rimmer, 2022 ). This challenge is often compounded by difficulties in multisensory integration, specifically the ability to bind auditory phonemes with visual graphemes (i.e., sounds with letters), a process essential for fluent reading (Jao Keehn et al., 2016 ). Therefore, interventions aimed at improving reading must not only teach phonics but also present this information in a format that facilitates this crucial audio-visual binding and reduces extraneous auditory noise. 2.4 The Intervention Gap: A Need for Perceptually-Aligned Tools Despite the clear theoretical and empirical links between perception and academics, a critical gap exists in the intervention literature. A majority of academic interventions for ASD are rooted in behavioral approaches (e.g., Applied Behavior Analysis) or direct instruction models that, while effective for teaching discrete skills, often do not explicitly address the underlying perceptual mechanisms (Bond et al., 2016 ). These methods may teach a child what to do but not how to process the information in a way that aligns with their neurotype, leading to rote learning with poor generalization. Systematic reviews of academic interventions have called for more research into strategies that are not only evidence-based but also tailored to the specific cognitive and perceptual profiles of learners with ASD (Alresheed et al., 2018 ). This leaves educators in inclusive settings with a dearth of practical, evidence-based tools designed to bridge the perceptual-academic gap. There is a pressing need for interventions that are: (1) grounded in neurodiversity-affirming principles, leveraging perceptual strengths rather than solely targeting deficits; (2) designed to explicitly structure information in a way that facilitates global-local integration; and (3) easy to implement within a typical classroom context. 2.5 Rationale for Infographics: A Theoretically Grounded Solution The current study posits that educational infographics are a uniquely suited tool to fill this intervention gap. Infographics are visual representations designed to communicate complex information clearly and efficiently by integrating graphics, text, and data (Dunlap & Lowenthal, 2016 ). Their potential efficacy for learners with ASD is strongly supported by several convergent theories of learning and cognition: Cognitive Load Theory (CLT) : CLT suggests that learning is optimized when extraneous cognitive load is minimized (Sweller, 2010 ). Infographics achieve this by segmenting information into manageable chunks, using visual cues (e.g., color, icons) to guide attention, and presenting information in an integrated format, thus reducing the mental effort required to process and organize it (Aldalalah, 2021 ). This is particularly beneficial for children with ASD who are prone to cognitive and sensory overload. Dual-Coding Theory (DCT) : Proposed by Paivio, DCT posits that information is processed through two distinct channels—verbal and non-verbal (visual). When information is presented in both formats simultaneously, it creates stronger, interconnected memory traces (Bi, 2021 ). Infographics are a prime example of dual coding in practice, linking concise text with meaningful images, which can enhance memory and recall, especially for visual learners. Universal Design for Learning (UDL) : UDL principles advocate for providing multiple means of representation to ensure accessibility for all learners (CAST, 2018 ). Infographics embody this principle by offering a visual, non-linear alternative to dense text. Their structured nature provides the predictability and clarity that learners with ASD often require, while their visual appeal can increase engagement and motivation (Carrington et al., 2020 ). Empirically, the use of infographics has been shown to improve information retention (Schechinger, 2023 ) and enhance understanding of complex topics across various domains (Azuka et al., 2024 ). By translating abstract academic concepts into concrete, visually organized formats, infographics directly address the challenges posed by WCC and leverage the strengths highlighted by EPF. They provide the "scaffolding" needed to build from details to a coherent whole. 2.6 The Present Study While the theoretical alignment is strong, there is a striking lack of empirical research testing the efficacy of infographics as a targeted intervention for children with ASD. The present study was designed to address this critical gap. It aims to empirically investigate the effectiveness of a targeted, infographic-based training program in enhancing both auditory and visual perception skills and, subsequently, improving basic academic skills (reading and mathematics) in primary school children with ASD. We hypothesized that by directly targeting the perceptual foundation of learning through a perceptually-aligned tool, we would observe not only improvements in perception but also a significant and sustained transfer of these gains to academic performance. 3. Method This section provides a detailed account of the methodological framework employed to investigate the efficacy of an infographic-based intervention for children with ASD. It outlines the research design, participant characteristics, instrumentation, data collection procedures, and the analytical approach used to address the study's hypotheses. Methodological rigor was prioritized at each stage to ensure the validity and reliability of the findings. 3.1 Research Design A quasi-experimental, one-group pretest-post- test-follow-up design was utilized for this study. This design was deliberately chosen as it is particularly well-suited for intervention research in special education settings where forming a randomized control group can be both practically and ethically challenging (Horner et al., 2005 ; Shadish et al., 2002 ). Withholding a potentially beneficial intervention from a control group of vulnerable children raises significant ethical concerns. Furthermore, the inherent heterogeneity within the ASD population makes matching participants for a control group exceedingly difficult. The one-group design mitigates these issues by allowing each participant to serve as their own control, providing a powerful method for measuring individual change and intervention effects against a stable baseline (Kazdin, 2021 ). The inclusion of a pre-test (T1) establishes baseline performance, the post-test (T2) assesses the immediate impact of the intervention, and the one-month follow-up test (T3) evaluates the maintenance and sustainability of any observed gains, a critical component for determining the long-term clinical significance of an educational intervention (Cook & Cook, 2008 ). 3.2 Participants A purposive sampling strategy was employed to recruit six children (four males, two females) aged 6 to 8 years ( M = 7.08 years, SD = 1.13) from an inclusive primary school in Arish, North Sinai. Purposive sampling is an effective technique in small-N research for selecting information-rich cases that are central to the phenomenon under investigation (Patton, 2015 ).“see Table 1 ” Table 1 : Participant Demographics and Baseline Characteristics Table 1 Participant Demographics and Baseline Characteristics (N = 6) Characteristic Value Age (years) Mean (SD) 7.8 (1.13) Range 6–8 Gender Male, n (%) 4 (66.7%) Female, n (%) 2 (33.3%) IQ (SB-5) Mean (SD) 74.3 (8.5) Range 60–84 ASD Severity (GARS-3) Mean (SD) 102.0 (7.95) Range 90–110 Interpretation Mild to Moderate Note. SD = Standard Deviation; IQ = Intelligence Quotient; SB-5 = Stanford-Binet Intelligence Scales, 5th Edition; ASD = Autism Spectrum Disorder; GARS-3 = Gilliam Autism Rating Scale, 3rd Edition. Inclusion criteria for participation were as follows: (1) a formal clinical diagnosis of Autism Spectrum Disorder (Level 1 or 2 severity) from a certified medical professional, documented in school records; (2) chronological age between 6 and 8 years, corresponding to the first three grades of primary education; (3) enrollment in a mainstream, inclusive classroom setting; (4) absence of severe co-occurring sensory impairments (e.g., blindness, deafness) that would preclude engagement with the visual and auditory components of the intervention; and (5) demonstrated basic prerequisite skills, such as the ability to attend to a task for at least five minutes. Exclusion criteria included the presence of profound intellectual disability or a diagnosis of a primary genetic disorder known to impact development differently from idiopathic ASD. Prior to the commencement of the study, ethical approval was obtained from the university's institutional review board. Written informed consent was secured from the parents or legal guardians of all participants, who were provided with a comprehensive overview of the study's purpose, procedures, potential risks, and benefits. Child assent was also obtained verbally, ensuring that each child was a willing participant. All data were anonymized to protect participant confidentiality. 3.3 Measures and Materials A suite of researcher-developed instruments was created and validated for this study, supplemented by the intervention program itself. The development of bespoke tools was necessary due to the lack of existing standardized measures that specifically align with the study's unique intervention and the Egyptian primary school curriculum. 3.3.1 The Infographic-Based Training Program. The core intervention was a structured training program developed by the researcher, designed to enhance perceptual and academic skills through static and dynamic infographics. The program's content was derived from the national curriculum for first to third graders and was structured around the principles of UDL and cognitive load theory (Sweller, 2010 ). It consisted of 48 sessions delivered over 16 weeks, covering a hierarchy of skills in visual perception (e.g., discrimination, part-whole analysis), auditory perception (e.g., phonological awareness), and basic academics (reading single words and sentences; basic addition and subtraction). Static infographics were used for foundational concepts, while animated infographics were introduced for more dynamic processes, a method supported by research suggesting motion can effectively guide attention and illustrate transformations (Tversky et al., 2002 ). 3.3.2 Visual Perception Skills Scale (Illustrated). This researcher-developed scale was designed to assess the specific visual perception skills targeted by the intervention. Drawing on established theories of visual processing (e.g., Marr's theory of vision), the scale comprises 54 items across three primary subscales: Visual Processing (e.g., identifying objects, colors, motion), Visual Discrimination (e.g., matching, sorting, recognizing figure-ground), and Part-Whole Relationships (e.g., identifying parts of a whole, visual closure). The instrument's content validity was established through review by a panel of ten experts in special education and educational psychology. As detailed in the dissertation, the scale demonstrated strong internal consistency (Cronbach's α = .849) and test-retest reliability. 3.3.3 Auditory Perception Skills Scale. This 22-item researcher-developed scale was created to measure auditory processing abilities relevant to academic learning. The scale is divided into two core domains: Auditory Discrimination (distinguishing between different environmental and phonetic sounds) and Phonological Awareness (understanding the sound structure of language, such as identifying syllables and rhymes). The development was informed by research highlighting the critical link between these skills and literacy acquisition, particularly in populations with developmental disorders (Aghaz et al., 2018 ). The instrument underwent the same rigorous expert validation process as the visual scale and demonstrated excellent psychometric properties, including high internal consistency (Cronbach's α = .890). 3.3.4 Basic Academic Skills Test (Illustrated). This criterion-referenced test was designed to measure foundational skills in reading and mathematics, serving as the primary academic outcome measure. The 60-item test is divided into three proficiency levels corresponding to grades 1, 2, and 3, allowing for the assessment of progress across a developmental continuum. The Reading subtest assesses skills from letter-sound correspondence to sentence comprehension. The Mathematics subtest evaluates skills from number recognition to simple arithmetic operations. The test items, presented in an illustrated format to reduce language load, were directly aligned with the national curriculum objectives and the intervention content, ensuring strong content and instructional validity. The test demonstrated high overall reliability (Cronbach's α = .887 across all levels). 3.4 Procedure The study was conducted over a period of approximately five months and was structured in five distinct phases: Phase 1: Baseline and Pre-testing (T1). Following recruitment and consent, each child was assessed individually in a quiet room within the school. The researcher administered the Visual Perception Skills Scale, the Auditory Perception Skills Scale, and the Basic Academic Skills Test. This phase established the baseline performance for all dependent variables. Phase 2: Intervention. The infographic-based training program was implemented over 16 weeks, with three individual sessions per week for each child. Each session lasted between 30 and 40 minutes and was conducted by the researcher. Sessions were highly structured, typically including a brief warm-up activity, introduction of a new concept via an infographic, several interactive practice exercises (e.g., pointing, sorting, verbal response), and positive reinforcement for effort and success. Phase 3: Post-testing (T2). Within one week of completing the final intervention session, the full battery of assessments was re-administered to each child under the same conditions as the pre-test. This phase measured the immediate effects of the intervention. Phase 4: No-Intervention Period. A one-month period followed the post-test during which participants received no intervention from the researcher and continued with their standard school curriculum. Phase 5: Follow-up Testing (T3). At the end of the one-month no-intervention period, the assessments were administered for a third and final time. This phase was crucial for determining the maintenance of skills over time. 3.5 Data Analysis All data were analyzed using IBM SPSS Statistics, Version 28. Given the small sample size (N = 6), which violates the assumptions of normality required for parametric tests, a non-parametric analytical approach was adopted, consistent with best practices for small-N educational research (Kratochwill et al., 2010 ). Descriptive statistics (means, standard deviations, medians, and ranges) were calculated for all variables at the three time points (T1, T2, and T3) to summarize performance and track changes. The Wilcoxon signed-rank test was used to analyze the differences between pre-test (T1) and post-test (T2) scores for all dependent variables (visual perception, auditory perception, and academic skills). This test is the non-parametric equivalent of a paired-samples t-test and is appropriate for comparing two related measurements from a single sample. To assess skill maintenance, the Wilcoxon signed-rank test was also used to compare post-test (T2) and follow-up (T3) scores. To analyze the overall change in academic skills across all three time points simultaneously, a Friedman's test was conducted. This test is the non-parametric alternative to a one-way repeated measures ANOVA. The significance level for all inferential tests was set at α = .05 . 4. Results This section presents the statistical analyses of the data collected at pre-test (T1), post-test (T2), and the one-month follow-up (T3). The findings are organized sequentially to address the study's primary hypotheses concerning the impact of the infographic-based intervention on participants' perceptual skills, academic skills, and the subsequent maintenance of these effects. Given the sample size (N = 6), non-parametric tests were employed for all inferential analyses as specified in the Method section. A summary of descriptive and inferential statistics is provided in Table 2 . and Fig. 1 4.1 Impact of the Intervention on Perceptual Skills The first hypothesis predicted that the infographic-based intervention would lead to statistically significant improvements in both visual and auditory perception skills from pre-test to post-test. Descriptive statistics revealed substantial gains in visual perception. The group's mean total score on the Visual Perception Skills Scale increased dramatically from pre-test ( M = 34.80, SD = 6.85) to post-test ( M = 79.83, SD = 15.58). A Wilcoxon signed-rank test confirmed that this increase was statistically significant, Z = 2.21, p = .027. The calculated effect size for this change was large ( r = .90), indicating that the intervention had a highly impactful and positive effect on participants' visual processing abilities. A similar and equally strong pattern was observed for auditory perception. Mean scores on the Auditory Perception Skills Scale rose from M = 8.17 ( SD = 4.07) at pre-test to M = 23.17 ( SD = 9.62) at post-test. This improvement was also found to be statistically significant via a Wilcoxon signed-rank test, Z = 2.20, p = .028. The effect size was identical to that for visual perception ( r = .90), demonstrating a large and meaningful intervention effect on auditory processing skills. 4.2 Impact of the Intervention on Basic Academic Skills The second hypothesis posited that the observed improvements in perceptual skills would translate into significant gains in basic academic skills. This hypothesis was strongly supported by the data. A Friedman's test was conducted to evaluate overall changes in academic performance across the three time points (T1, T2, T3) for each of the three curriculum levels tested. The results were statistically significant for Level 1 (χ²(2) = 7.00, p = .030), Level 2 (χ²(2) = 10.37, p = .006), and Level 3 (χ²(2) = 10.14, p = .006), indicating a significant overall effect of the intervention across all academic proficiency levels. To specifically assess the pre-test to post-test gain, post-hoc Wilcoxon signed-rank tests were performed. A statistically significant increase was found in the Basic Academic Skills Test scores at Level 1 ( Z = 2.20, p = .028, r = .90), Level 2 ( Z = 2.23, p = .026, r = .91), and Level 3 ( Z = 2.20, p = .028, r = .90). The large effect sizes across all levels confirm that the intervention led to substantial and practically significant improvements in participants' reading and mathematics abilities. See Table 2 . and Fig. 2 . 4.3 Maintenance of Intervention Effects on Follow-Up The final hypothesis addressed the sustainability of the intervention's impact by assessing the maintenance of skills at the one-month follow-up. Wilcoxon signed-rank tests were used to compare the scores from the post-test (T2) with those from the follow-up assessment (T3). See Table 2 . and Fig. 2 . Figure 3. Academic Skills performance by levels (Level 1, Level 2, Level 3) across Pretest, Posttest, and Follow-up assessments. The analysis revealed no statistically significant differences between post-test and follow-up scores for the total score on the Visual Perception Scale ( Z = 1.58, p = .115) or the Auditory Perception Scale ( Z = 1.41, p = .157). Similarly, no significant decline was observed in the Basic Academic Skills Test at Level 1 ( Z = 0.58, p = .564), Level 2 ( Z = 1.41, p = .157), or Level 3 ( Z = 1.00, p = .317). The stability of the scores from post-test to follow-up demonstrates that the perceptual and academic gains achieved during the intervention were successfully maintained one month after its conclusion. In summary, the data provide robust, statistically significant support for all three study hypotheses. The infographic-based intervention was effective in enhancing perceptual and academic skills, and these gains were shown to be durable over time. Table 2 Summary of Descriptive and Inferential Statistics for All Measures (N = 6) Measure and Time Point Mean (M) Std. Deviation (SD) Wilcoxon Test (vs. Previous) Effect Size ( r ) Visual Perception Scale Pre-Test (T1) 34.80 6.85 - - Post-Test (T2) 79.83 15.58 Z = 2.21, p = .027 .90 Follow-Up (T3) 77.17 15.41 Z = 1.58, p = .115 - Auditory Perception Scale Pre-Test (T1) 8.17 4.07 - - Post-Test (T2) 23.17 9.62 Z = 2.20, p = .028 .90 Follow-Up (T3) 22.83 9.28 Z = 1.41, p = .157 - Academic Skills Test (L1) Pre-Test (T1) 12.50 3.62 - - Post-Test (T2) 18.17 7.25 Z = 2.20, p = .028 .90 Follow-Up (T3) 16.67 7.26 Z = 0.58, p = .564 - Academic Skills Test (L2) Pre-Test (T1) 9.00 3.29 - - Post-Test (T2) 19.50 4.28 Z = 2.23, p = .026 .91 Follow-Up (T3) 19.00 4.05 Z = 1.41, p = .157 - Academic Skills Test (L3) Pre-Test (T1) 6.50 3.89 - - Post-Test (T2) 16.50 5.68 Z = 2.20, p = .028 .90 Follow-Up (T3) 16.00 5.10 Z = 1.00, p = .317 - Note . L1, L2, L3 refer to Levels 1, 2, and 3 of the Basic Academic Skills Test. Effect size r is calculated as Z/√N for pre-post comparisons. A non-significant p -value for follow-up tests indicates maintenance of skills. 5. Discussion The findings of this study provide compelling evidence that a targeted, infographic-based intervention can significantly enhance both foundational perceptual skills and basic academic abilities in children with ASD. The statistically significant improvements observed from pre-test to post-test, coupled with the remarkable maintenance of these gains at the one-month follow-up, offer a robust validation of our primary hypotheses. This discussion will interpret these findings within the context of established neurocognitive theories of autism, situate them within the broader landscape of educational intervention research, and explore the study's profound implications for both theory and practice. 5.1 Bridging the Perceptual Divide: The Mechanism of Infographic Efficacy The primary contribution of this study is the demonstration of a successful, theory-driven intervention that directly addresses the perceptual-academic gap. The significant improvements in visual and auditory perception are not surprising when viewed through the lens of the core design principles of the infographic program. The intervention’s structure—segmenting complex information into discrete, visually organized units—is a direct pedagogical response to the challenges predicted by the Weak Central Coherence (WCC) theory (Happé & Frith, 2006 ). Instead of requiring children to spontaneously derive global meaning from a cluttered field, the infographics provided a pre-organized structure, allowing them to leverage their detail-oriented processing style (an aspect of Enhanced Perceptual Functioning) in a productive manner. By presenting information in a clear, predictable, and visually salient format, the program likely reduced extraneous cognitive load, freeing up cognitive resources for processing and encoding the core content, a principle central to Cognitive Load Theory (Sweller, 2010 ; Aldalalah, 2021 ). Crucially, the intervention did not merely enhance perceptual skills in isolation; it facilitated their application in academic tasks. The observed transfer of gains to reading and mathematics supports the central premise of this paper: that for many children with ASD, the primary bottleneck to academic learning is perceptual, not conceptual. The infographics functioned as a "cognitive bridge." In line with Dual-Coding Theory (Bi, 2021 ), the simultaneous presentation of visual icons and concise text (e.g., a numeral paired with a graphic representation of that quantity) created stronger, multi-modal memory engrams. This audio-visual binding is particularly critical for foundational literacy, where mapping graphemes to phonemes is essential (Jao Keehn et al., 2016 ). Our findings suggest that by making this mapping explicit and visually anchored, the infographics provided the necessary scaffold for children who struggle with this integrative process, moving them beyond rote memorization to meaningful comprehension. 5.2 The Durability of Learning: From Intervention to Internalization Perhaps the most significant finding of this study is the durability of the observed effects. The absence of a statistically significant decline in skills at the one-month follow-up stands in contrast to many educational interventions where skills regress once the structured support is withdrawn (Lovaas, 1987 ). This suggests that the infographic program facilitated not just performance but genuine learning and skill internalization. This sustained impact can be attributed to the intervention's alignment with the learners' intrinsic perceptual mechanisms. Rather than teaching a compensatory strategy that requires constant effort, the program presented information in a format that was more naturally processed. This likely led to a more efficient and deeper encoding of both the academic content and the perceptual strategies themselves. This finding underscores a critical point: interventions that work with the neurotype of the learner, rather than against it, have a far greater potential for producing lasting change (Pellicano & den Houting, 2022 ). The stability of these gains provides a strong argument for the clinical and educational significance of this approach, moving it beyond a mere classroom activity to a potent tool for developmental change. 5.3 Contextualizing the Findings within the Broader Literature The results of this study both confirm and extend the existing literature. They align with a long-standing body of research advocating for the use of visual supports for individuals with ASD, which have been shown to improve understanding, reduce anxiety, and promote independence (Macoskey, 2023 ). Our findings are also consistent with studies demonstrating the benefits of UDL principles in creating more accessible learning environments for neurodiverse students (Carrington et al., 2020 ). However, this study makes several novel contributions. First, while the benefit of "visual supports" is a broad concept, our research isolates and empirically validates a specific, modern, and highly adaptable tool: the educational infographic. Second, unlike much of the previous research which has been descriptive or correlational, our quasi-experimental design provides causal evidence linking a targeted perceptual intervention directly to academic outcomes. We did not just show that children with better perception have better academic skills; we demonstrated that improving perception via a targeted intervention leads to improved academic skills. This establishes a clear, evidence-based pathway for intervention that has been largely absent from the literature. Finally, the focus on both static and dynamic infographics speaks to an emerging area of research on how different presentation modalities impact learning in this population (van Rijssel, 2020 ), offering a nuanced contribution to the field of educational technology. 5.4 Strengths, Limitations, and Future Directions The primary strength of this study lies in its innovative, theory-driven intervention and its rigorous single-group, pre-post-follow-up design, which provides a strong signal of the intervention's efficacy and durability. The development of bespoke, curriculum-aligned assessment tools also ensures a high degree of content validity. Nevertheless, the study's limitations must be acknowledged. The most significant is the small, purposive sample (N = 6). While appropriate for an intensive, exploratory study of this nature, the small sample size limits the generalizability of the findings and necessitates a non-parametric analytical approach. Future research should seek to replicate these results with a larger, more diverse sample of children with ASD across different age groups and support levels. A randomized controlled trial (RCT) would provide the gold-standard evidence for causal inference, allowing for a direct comparison between the infographic intervention and a traditional teaching or alternative intervention group. Future research could also explore several promising avenues. It would be valuable to investigate the differential effects of static versus animated infographics on specific skills, or to integrate interactive elements to enhance engagement further. Additionally, exploring the application of this methodology to more complex academic subjects (e.g., science, social studies) and older students is a logical next step. Finally, neuroimaging studies (e.g., fMRI or EEG) could be employed to investigate the neural mechanisms underlying these behavioral changes, potentially providing objective biomarkers of improved perceptual integration and cognitive efficiency. 5.5 Implications for Educational Practice The findings of this study have profound and immediately applicable implications for inclusive education. They suggest a critical need for a paradigm shift, moving away from a purely content-driven curriculum toward one that is perceptually informed. For Educators : Teachers can and should integrate infographics into their daily instruction. This does not require a complete overhaul of their curriculum but rather a transformation of how key concepts are presented. Infographics can be used to introduce new topics, summarize complex information, and provide visual instructions for assignments. For Curriculum Developers : There is a clear mandate to develop and embed perceptually-aligned materials, like infographics, directly into core curricula. Textbooks and digital learning platforms should offer visual alternatives to dense text as a standard feature, in line with UDL principles. For School Psychologists and Special Educators : The researcher-developed scales used in this study provide a template for creating functional assessment tools that can help identify specific points of breakdown in a child's perceptual-academic pathway, allowing for more precise and targeted intervention planning. 5.6 Conclusion This study successfully demonstrated that an infographic-based intervention is a powerful tool for bridging the perceptual-academic gap in children with ASD. By aligning instructional design with the inherent neurocognitive profiles of the learners, the program not only enhanced foundational perceptual skills but also fostered significant and durable gains in essential academic abilities. The results champion a move towards neurodiversity-affirming pedagogies that leverage students' strengths and provide the necessary scaffolds to navigate their challenges. Ultimately, this research suggests that to help a child with ASD succeed academically, we may not need to change the child, but rather, change the way we present the world of knowledge to them. 6. Limitations and Future Directions While this study provides a robust proof-of-concept for the efficacy of infographic-based interventions, its contributions must be contextualized within its methodological limitations. The primary limitation is the small, purposive sample (N = 6). Although the one-group pretest-posttest-follow-up design allows each participant to serve as their own control, providing a strong signal of individual change (Kazdin, 2021 ), the small N restricts the statistical power and limits the generalizability of the findings to the broader, highly heterogeneous ASD population. The results, while compelling, should be interpreted as a foundational rather than a definitive statement on the intervention's universal efficacy. Second, the study was conducted by the researcher, who also developed the intervention and assessment materials. While this ensures a high degree of fidelity in implementation, it introduces the potential for experimenter bias. Although standardized procedures were strictly followed, the lack of blind assessment is a limitation. Future replications would be strengthened by employing independent assessors who are blind to the study's hypotheses and the participants' intervention status. Finally, while the study successfully demonstrated a transfer of skills to academic tasks, these tasks were measured via a researcher-developed test aligned with the intervention content. To establish broader generalization, future studies should include standardized, norm-referenced academic achievement tests and observational measures of classroom performance as outcome variables. These limitations pave a clear path for future research. The immediate next step is to replicate this study with a larger, more diverse sample within a randomized controlled trial (RCT) design. An RCT would allow for a direct comparison against a control group receiving traditional instruction, providing the gold-standard evidence needed for widespread adoption. Furthermore, future investigations could employ a component analysis to dismantle the intervention and determine the relative contributions of its specific elements (e.g., static vs. dynamic infographics, color-coding, textual brevity). Lastly, leveraging neuroimaging technologies like EEG to track changes in neural processing during infographic-based tasks could provide invaluable objective evidence of the intervention’s impact on the underlying perceptual mechanisms, moving the field from behavioral observation to neurocognitive validation. 7. Conclusion and Implications This study was conceptualized to address a fundamental, yet often overlooked, challenge in autism education: the chasm between atypical perceptual processing and the demands of academic learning. The findings unequivocally demonstrate that a targeted, infographic-based intervention serves as a powerful bridge across this gap. By systematically enhancing visual and auditory perception, the program produced not only significant and durable improvements in these foundational domains but also facilitated a remarkable and sustained transfer of these gains to essential academic skills in reading and mathematics. The implications of this research are both profound and pragmatic. For educational theory, it provides strong empirical support for a perceptually-driven pedagogical model for ASD. It affirms that to unlock the academic potential of these learners, we must first address the foundational level at which they process information. The study repositions perceptual support not as a mere accommodation, but as a core mechanism for enabling higher-order cognition. It strongly suggests that for children on the spectrum, the path to academic competence is paved with perceptual clarity. For educational practice, this study offers a readily implementable, evidence-based tool that respects the neurotype of the learner. It moves beyond abstract principles and provides a concrete methodology that educators can adopt to make curricula more accessible and effective. The success of this intervention serves as a cornerstone, a foundational piece of evidence arguing that by redesigning the delivery of information to align with the autistic mind, we can foster authentic learning and create truly inclusive educational ecosystems. This work does not merely add another intervention to the existing repertoire; it provides a new lens through which to view and approach autism education—one that begins with perception. Declarations Author Note This research article is derived from the doctoral dissertation titled “Using Infographics to Develop Visual and Auditory Perception Skills and Their Effect on Improving Basic Academic Skills among Integrated Children with Autism Spectrum Disorder” , submitted to the Faculty of Education, University of Al-Arish, Arab Republic of Egypt, in partial fulfillment of the requirements for the Ph.D. degree in Special Education. The authors gratefully acknowledge the support and guidance provided by the Faculty of Education at the University of Al-Arish and extend sincere thanks to the participating schools, teachers, and families who made this research possible. Correspondence concerning this article should be addressed to Dr. Ahmed Fadlallah Shalally Hassan, Department of Special Education, Faculty of Education, University of Al-Arish, Arab Republic of Egypt. Email: [email protected] (Data tables and full measurement specifications are excerpted from the doctoral dissertation. Acknowledgements The author wishes to express sincere gratitude to the children and educators who participated in this study, whose insights enriched the validation process of the pictorial visual perception scale. Special thanks are due to the administration of inclusive primary schools for their cooperation during data collection. The author also acknowledges the valuable linguistic support provided. Appreciation is extended to peer reviewers whose constructive feedback will help enhance the clarity and impact of this work. Ethics approval and consent to participate This study was conducted in accordance with the principles of the Declaration of Helsinki. Ethical approval was obtained from the Research Ethics Committee of the Faculty of Education, Arish University (Approval No. EDU/REC/2024/07; dated September 22, 2024). Written informed consent was obtained from the parents or legal guardians of all children participating in the study. Verbal assent was also obtained from the children where possible. Consent for publication Not applicable. (This study does not contain any individual person’s data in any form, such as individual details, images, or videos). Availability of data and materials The datasets generated and/or analyzed during the current study are not publicly available due to privacy and ethical restrictions concerning child participants but are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Authors' contributions A.F.S.H. conceived the study, designed the instrument and the intervention, collected and analyzed the data, and wrote the manuscript. M.A.A.E. supervised the research, contributed to the study design and data interpretation, and critically revised the manuscript. N.M.A.A. co-supervised the research, assisted in the methodological design, and reviewed the final manuscript. All authors read and approved of the final manuscript. 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Tilburg University Theses Zylstra JS, Hamilton ST, De Korte M (2023) Phonological awareness and rapid automatized naming as predictors of word reading for students with autism spectrum disorder. J Autism Dev Disord 53(1):307–319. https://doi.org/10.1007/s10803-021-05381-z Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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14:54:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":166958,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of mean scores for Visual Perception, Auditory Perception, and Academic Skills at Pretest, Posttest, and Follow-up.\u003c/p\u003e","description":"","filename":"Picture22.png","url":"https://assets-eu.researchsquare.com/files/rs-8096304/v1/f8f182d66d9cd0000670cd14.png"},{"id":95847081,"identity":"7d6ca080-e28a-4d73-8e0c-109f0414dcda","added_by":"auto","created_at":"2025-11-13 14:54:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":158351,"visible":true,"origin":"","legend":"\u003cp\u003eAcademic Skills performance by levels (Level 1, Level 2, Level 3) across Pretest, Posttest, and Follow-up assessments.\u003c/p\u003e","description":"","filename":"Picture33.png","url":"https://assets-eu.researchsquare.com/files/rs-8096304/v1/df888d9561344c77e94e6b4f.png"},{"id":96362757,"identity":"d153d7ac-efeb-41c6-8e7c-2cc4899aa386","added_by":"auto","created_at":"2025-11-20 09:48:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6037963,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8096304/v1/2249e803-f336-489e-901a-4b79ade7fadb.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eBridging the Perceptual-Academic Gap: How Infographics Enhance Basic Academic Skills by Improving Auditory and Visual Perception in Children with ASD\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAutism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by persistent challenges in social communication and interaction, alongside restricted, repetitive patterns of behavior, interests, or activities (American Psychiatric Association [APA], 2022). With a rising global prevalence, now estimated by the Centers for Disease Control and Prevention (CDC) to affect approximately 1 in 36 children in the United States (Maenner et al., 2023), the educational and developmental needs of this population represent a critical area of focus for researchers and practitioners. While the core diagnostic criteria are well-documented, the secondary academic challenges faced by children with ASD often pose significant barriers to their success in inclusive educational settings. A substantial body of evidence indicates that these academic difficulties are not merely byproducts of cognitive or behavioral factors but are deeply rooted in fundamental differences in sensory processing and perception (Bolis \u0026amp; Schilbach, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Mikkelsen et al., 2018). This phenomenon creates a foundational \"perceptual-academic gap,\" where atypical processing of auditory and visual information obstructs the acquisition and application of basic academic skills, such as literacy and numeracy.\u003c/p\u003e\u003cp\u003eThe unique perceptual world of individuals with ASD is often explained through prominent theoretical frameworks, including the Weak Central Coherence (WCC) theory and the Enhanced Perceptual Functioning (EPF) model. The WCC theory posits that individuals with ASD exhibit a cognitive style biased toward detail-focused, local processing at the expense of integrating information into a coherent, global whole (Happ\u0026eacute; \u0026amp; Frith, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). This can manifest as an exceptional ability to spot details but a significant challenge in understanding the broader context, or \"seeing the forest for the trees.\" Conversely, the EPF model highlights superior performance in simple or detail-oriented perceptual tasks, suggesting an enhancement in local processing (Mottron et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). While this detail-oriented style can be an asset in certain contexts, it often creates obstacles in academic tasks like reading comprehension, which requires integrating letter sounds into words and words into meaningful sentences, and mathematics, which demands understanding holistic concepts beyond rote calculation (Bullen et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Tonizzi \u0026amp; Usai, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These theoretical underpinnings suggest that effective educational interventions should not only present academic content but also structure it in a way that bridges this perceptual divide.\u003c/p\u003e\u003cp\u003eDespite a growing recognition of the interplay between perception and academic achievement in ASD, a significant gap persists in the intervention literature. Many traditional educational strategies are designed for neurotypical learners and may inadvertently exacerbate the cognitive and sensory load on children with ASD (Keen et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). While interventions targeting academic skills exist, they often overlook the foundational perceptual deficits that impede learning. A systematic review by Alresheed et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) highlighted the need for more interventions that address academic-related skills with robust research designs. Furthermore, there remains a notable scarcity of research investigating tools specifically designed to accommodate the unique perceptual profiles of children with ASD as a direct pathway to academic improvement. This gap is particularly evident concerning the use of modern visual communication tools that are inherently structured and detail-oriented.\u003c/p\u003e\u003cp\u003eThis study proposes that educational infographics represent a novel and theoretically aligned tool to bridge this perceptual-academic gap. Infographics are visual representations of information, data, or knowledge intended to present complex information quickly and clearly (Dunlap \u0026amp; Lowenthal, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Their inherent design principles align remarkably well with the perceptual strengths and challenges of children with ASD. By breaking down complex topics into discrete, visually organized chunks of information, infographics reduce cognitive load and cater to a detail-focused processing style (Aldalalah, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The integration of text, icons, charts, and images leverages the visual learning strengths common in this population (Bidin \u0026amp; Omar, 2015) and aligns with Universal Design for Learning (UDL) principles by presenting information in multiple modalities (Carrington et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This structured, predictable, and visually salient format can help children with ASD organize sensory input, direct their attention, and build connections between details and the overarching concept, thereby facilitating both perceptual processing and academic comprehension.\u003c/p\u003e\u003cp\u003eTherefore, the present study aims to investigate the effectiveness of a targeted, infographic-based training program in enhancing auditory and visual perception skills and, consequently, improving basic academic skills (reading and mathematics) in primary school children with ASD in inclusive settings. The study is guided by the following primary hypotheses:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eParticipation in the infographic-based program will result in statistically significant improvements in visual and auditory perception skills from pre-test to post-test.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eThe improvements in visual and auditory perception will be associated with statistically significant gains in basic academic skills.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eThe observed academic and perceptual gains will be maintained at a one-month follow-up assessment, indicating the sustained impact of the intervention.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eBy providing empirical evidence for this novel intervention, this study seeks to offer a practical, theoretically grounded tool for educators and contribute to a deeper understanding of how to effectively support the academic success of children with ASD by addressing their core perceptual needs.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e"},{"header":"2. Literature Review","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 The Perceptual-Academic Nexus in Autism Spectrum Disorder\u003c/h2\u003e\u003cp\u003eAutism Spectrum Disorder (ASD) is a neurodevelopmental condition defined by core challenges in social communication and the presence of restricted, repetitive behaviors (American Psychiatric Association [APA], 2022). While these diagnostic criteria are central, the landscape of challenges for children with ASD extends profoundly into the academic domain. A persistent and significant body of research demonstrates a strong link between the unique sensory processing profiles of individuals with ASD and their academic outcomes (Marco et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Robertson \u0026amp; Baron-Cohen, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This connection is not incidental; rather, it forms a foundational \"perceptual-academic gap,\" where atypical processing of sensory information creates a bottleneck for acquiring higher-order skills like literacy and numeracy. Difficulties in academic performance, therefore, are often not a primary cognitive deficit but a downstream consequence of a fundamental mismatch between the child's perceptual system and the demands of traditional pedagogy (Bolis \u0026amp; Schilbach, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Jones et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Understanding this nexus is paramount to developing interventions that are not merely palliative but genuinely transformative.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Atypical Visual Perception and its Academic Implications\u003c/h2\u003e\u003cp\u003eThe visual world of a child with ASD is often qualitatively different from that of their neurotypical peers. Two dominant theories, Weak Central Coherence (WCC) and Enhanced Perceptual Functioning (EPF), provide a robust framework for understanding these differences. The WCC theory posits a cognitive style characterized by a bias towards processing local details at the expense of extracting global meaning or gist (Happ\u0026eacute; \u0026amp; Frith, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). This detail-focused bias means a child with ASD might excel at identifying a specific letter in a complex image but struggle to derive the overall meaning of a sentence. Complementing this, the EPF model suggests superior abilities in low-level perceptual tasks, such as detecting visual targets or discriminating patterns (Mottron et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWhile this \"perceptual signature\" confers advantages in tasks requiring precision and detail (e.g., puzzles, visual search), it poses significant hurdles in academic contexts. Reading, for instance, is an inherently integrative process. It requires the rapid, holistic recognition of word shapes and the fluid integration of words into sentences to build meaning\u0026mdash;a task that is fundamentally challenged by a piecemeal, detail-by-detail processing style (Evers et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Similarly, mathematical reasoning often depends on grasping holistic concepts, such as the relationship between quantities, which can be obscured by an intense focus on individual numbers or symbols (Bullen et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Tonizzi \u0026amp; Usai, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Consequently, any effective academic intervention must acknowledge and accommodate this visual processing style, structuring information in a way that guides the learner from local details to global understanding, rather than assuming this integration will occur spontaneously.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Auditory Processing, Phonological Awareness, and Literacy\u003c/h2\u003e\u003cp\u003eParallel to visual processing, auditory perception in ASD is also marked by significant heterogeneity, including both hyper- and hypo-sensitivities to sound (Gon\u0026ccedil;alves \u0026amp; Monteiro, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These sensitivities can make a typical classroom, with its overlapping auditory stimuli, a source of profound sensory overload, impeding attention and learning. Beyond basic sensitivity, a more specific challenge lies in the domain of \u003cb\u003ephonological awareness\u003c/b\u003e\u0026mdash;the ability to recognize and manipulate the sound structure of spoken language. This skill is a cornerstone of literacy development and a robust predictor of reading success (Zylstra et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eResearch consistently indicates that a subgroup of children with ASD demonstrates significant deficits in phonological awareness, impacting their ability to decode words (Aghaz et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Rimmer, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This challenge is often compounded by difficulties in multisensory integration, specifically the ability to bind auditory phonemes with visual graphemes (i.e., sounds with letters), a process essential for fluent reading (Jao Keehn et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Therefore, interventions aimed at improving reading must not only teach phonics but also present this information in a format that facilitates this crucial audio-visual binding and reduces extraneous auditory noise.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 The Intervention Gap: A Need for Perceptually-Aligned Tools\u003c/h2\u003e\u003cp\u003eDespite the clear theoretical and empirical links between perception and academics, a critical gap exists in the intervention literature. A majority of academic interventions for ASD are rooted in behavioral approaches (e.g., Applied Behavior Analysis) or direct instruction models that, while effective for teaching discrete skills, often do not explicitly address the underlying perceptual mechanisms (Bond et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). These methods may teach a child \u003cem\u003ewhat\u003c/em\u003e to do but not \u003cem\u003ehow\u003c/em\u003e to process the information in a way that aligns with their neurotype, leading to rote learning with poor generalization. Systematic reviews of academic interventions have called for more research into strategies that are not only evidence-based but also tailored to the specific cognitive and perceptual profiles of learners with ASD (Alresheed et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis leaves educators in inclusive settings with a dearth of practical, evidence-based tools designed to bridge the perceptual-academic gap. There is a pressing need for interventions that are: (1) grounded in neurodiversity-affirming principles, leveraging perceptual strengths rather than solely targeting deficits; (2) designed to explicitly structure information in a way that facilitates global-local integration; and (3) easy to implement within a typical classroom context.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Rationale for Infographics: A Theoretically Grounded Solution\u003c/h2\u003e\u003cp\u003eThe current study posits that \u003cb\u003eeducational infographics\u003c/b\u003e are a uniquely suited tool to fill this intervention gap. Infographics are visual representations designed to communicate complex information clearly and efficiently by integrating graphics, text, and data (Dunlap \u0026amp; Lowenthal, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Their potential efficacy for learners with ASD is strongly supported by several convergent theories of learning and cognition:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eCognitive Load Theory (CLT)\u003c/b\u003e: CLT suggests that learning is optimized when extraneous cognitive load is minimized (Sweller, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Infographics achieve this by segmenting information into manageable chunks, using visual cues (e.g., color, icons) to guide attention, and presenting information in an integrated format, thus reducing the mental effort required to process and organize it (Aldalalah, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This is particularly beneficial for children with ASD who are prone to cognitive and sensory overload.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eDual-Coding Theory (DCT)\u003c/b\u003e: Proposed by Paivio, DCT posits that information is processed through two distinct channels\u0026mdash;verbal and non-verbal (visual). When information is presented in both formats simultaneously, it creates stronger, interconnected memory traces (Bi, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Infographics are a prime example of dual coding in practice, linking concise text with meaningful images, which can enhance memory and recall, especially for visual learners.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eUniversal Design for Learning (UDL)\u003c/b\u003e: UDL principles advocate for providing multiple means of representation to ensure accessibility for all learners (CAST, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Infographics embody this principle by offering a visual, non-linear alternative to dense text. Their structured nature provides the predictability and clarity that learners with ASD often require, while their visual appeal can increase engagement and motivation (Carrington et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eEmpirically, the use of infographics has been shown to improve information retention (Schechinger, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and enhance understanding of complex topics across various domains (Azuka et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). By translating abstract academic concepts into concrete, visually organized formats, infographics directly address the challenges posed by WCC and leverage the strengths highlighted by EPF. They provide the \"scaffolding\" needed to build from details to a coherent whole.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6 The Present Study\u003c/h2\u003e\u003cp\u003eWhile the theoretical alignment is strong, there is a striking lack of empirical research testing the efficacy of infographics as a targeted intervention for children with ASD. The present study was designed to address this critical gap. It aims to empirically investigate the effectiveness of a targeted, infographic-based training program in enhancing both auditory and visual perception skills and, subsequently, improving basic academic skills (reading and mathematics) in primary school children with ASD. We hypothesized that by directly targeting the perceptual foundation of learning through a perceptually-aligned tool, we would observe not only improvements in perception but also a significant and sustained transfer of these gains to academic performance.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Method","content":"\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThis section provides a detailed account of the methodological framework employed to investigate the efficacy of an infographic-based intervention for children with ASD. It outlines the research design, participant characteristics, instrumentation, data collection procedures, and the analytical approach used to address the study's hypotheses. Methodological rigor was prioritized at each stage to ensure the validity and reliability of the findings.\u003c/p\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Research Design\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eA quasi-experimental, \u003cb\u003eone-group pretest-post- test-follow-up design\u003c/b\u003e was utilized for this study. This design was deliberately chosen as it is particularly well-suited for intervention research in special education settings where forming a randomized control group can be both practically and ethically challenging (Horner et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Shadish et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Withholding a potentially beneficial intervention from a control group of vulnerable children raises significant ethical concerns. Furthermore, the inherent heterogeneity within the ASD population makes matching participants for a control group exceedingly difficult. The one-group design mitigates these issues by allowing each participant to serve as their own control, providing a powerful method for measuring individual change and intervention effects against a stable baseline (Kazdin, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The inclusion of a pre-test (T1) establishes baseline performance, the post-test (T2) assesses the immediate impact of the intervention, and the one-month follow-up test (T3) evaluates the maintenance and sustainability of any observed gains, a critical component for determining the long-term clinical significance of an educational intervention (Cook \u0026amp; Cook, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Participants\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eA purposive sampling strategy was employed to recruit six children (four males, two females) aged 6 to 8 years (\u003cem\u003eM\u003c/em\u003e = 7.08 years, \u003cem\u003eSD\u003c/em\u003e = 1.13) from an inclusive primary school in Arish, North Sinai. Purposive sampling is an effective technique in small-N research for selecting information-rich cases that are central to the phenomenon under investigation (Patton, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).“see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e”\u003c/p\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e: \u003cb\u003eParticipant Demographics and Baseline Characteristics\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cem\u003eParticipant Demographics and Baseline Characteristics (N = 6)\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eValue\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.8 (1.13)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRange\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6–8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (66.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (33.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIQ (SB-5)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e74.3 (8.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRange\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60–84\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eASD Severity (GARS-3)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e102.0 (7.95)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRange\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e90–110\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInterpretation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMild to Moderate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eNote.\u003c/em\u003e SD = Standard Deviation; IQ = Intelligence Quotient; SB-5 = Stanford-Binet Intelligence Scales, 5th Edition; ASD = Autism Spectrum Disorder; GARS-3 = Gilliam Autism Rating Scale, 3rd Edition.\u003c/p\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eInclusion criteria for participation were as follows: (1) a formal clinical diagnosis of Autism Spectrum Disorder (Level 1 or 2 severity) from a certified medical professional, documented in school records; (2) chronological age between 6 and 8 years, corresponding to the first three grades of primary education; (3) enrollment in a mainstream, inclusive classroom setting; (4) absence of severe co-occurring sensory impairments (e.g., blindness, deafness) that would preclude engagement with the visual and auditory components of the intervention; and (5) demonstrated basic prerequisite skills, such as the ability to attend to a task for at least five minutes. Exclusion criteria included the presence of profound intellectual disability or a diagnosis of a primary genetic disorder known to impact development differently from idiopathic ASD.\u003c/p\u003e\u003cp\u003e Prior to the commencement of the study, ethical approval was obtained from the university's institutional review board. Written informed consent was secured from the parents or legal guardians of all participants, who were provided with a comprehensive overview of the study's purpose, procedures, potential risks, and benefits. Child assent was also obtained verbally, ensuring that each child was a willing participant. All data were anonymized to protect participant confidentiality.\u003c/p\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Measures and Materials\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eA suite of researcher-developed instruments was created and validated for this study, supplemented by the intervention program itself. The development of bespoke tools was necessary due to the lack of existing standardized measures that specifically align with the study's unique intervention and the Egyptian primary school curriculum.\u003c/p\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003e3.3.1 The Infographic-Based Training Program.\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe core intervention was a structured training program developed by the researcher, designed to enhance perceptual and academic skills through static and dynamic infographics. The program's content was derived from the national curriculum for first to third graders and was structured around the principles of UDL and cognitive load theory (Sweller, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). It consisted of 48 sessions delivered over 16 weeks, covering a hierarchy of skills in visual perception (e.g., discrimination, part-whole analysis), auditory perception (e.g., phonological awareness), and basic academics (reading single words and sentences; basic addition and subtraction). Static infographics were used for foundational concepts, while animated infographics were introduced for more dynamic processes, a method supported by research suggesting motion can effectively guide attention and illustrate transformations (Tversky et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e3.3.2 Visual Perception Skills Scale (Illustrated).\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThis researcher-developed scale was designed to assess the specific visual perception skills targeted by the intervention. Drawing on established theories of visual processing (e.g., Marr's theory of vision), the scale comprises 54 items across three primary subscales: \u003cb\u003eVisual Processing\u003c/b\u003e (e.g., identifying objects, colors, motion), \u003cb\u003eVisual Discrimination\u003c/b\u003e (e.g., matching, sorting, recognizing figure-ground), and \u003cb\u003ePart-Whole Relationships\u003c/b\u003e (e.g., identifying parts of a whole, visual closure). The instrument's content validity was established through review by a panel of ten experts in special education and educational psychology. As detailed in the dissertation, the scale demonstrated strong internal consistency (Cronbach's α = .849) and test-retest reliability.\u003c/p\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e3.3.3 Auditory Perception Skills Scale.\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThis 22-item researcher-developed scale was created to measure auditory processing abilities relevant to academic learning. The scale is divided into two core domains: \u003cb\u003eAuditory Discrimination\u003c/b\u003e (distinguishing between different environmental and phonetic sounds) and \u003cb\u003ePhonological Awareness\u003c/b\u003e (understanding the sound structure of language, such as identifying syllables and rhymes). The development was informed by research highlighting the critical link between these skills and literacy acquisition, particularly in populations with developmental disorders (Aghaz et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The instrument underwent the same rigorous expert validation process as the visual scale and demonstrated excellent psychometric properties, including high internal consistency (Cronbach's α = .890).\u003c/p\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\u003ch2\u003e3.3.4 Basic Academic Skills Test (Illustrated).\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThis criterion-referenced test was designed to measure foundational skills in reading and mathematics, serving as the primary academic outcome measure. The 60-item test is divided into three proficiency levels corresponding to grades 1, 2, and 3, allowing for the assessment of progress across a developmental continuum. The \u003cb\u003eReading\u003c/b\u003e subtest assesses skills from letter-sound correspondence to sentence comprehension. The \u003cb\u003eMathematics\u003c/b\u003e subtest evaluates skills from number recognition to simple arithmetic operations. The test items, presented in an illustrated format to reduce language load, were directly aligned with the national curriculum objectives and the intervention content, ensuring strong content and instructional validity. The test demonstrated high overall reliability (Cronbach's α = .887 across all levels).\u003c/p\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Procedure\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe study was conducted over a period of approximately five months and was structured in five distinct phases:\u003c/p\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003ePhase 1: Baseline and Pre-testing (T1).\u003c/b\u003e Following recruitment and consent, each child was assessed individually in a quiet room within the school. The researcher administered the Visual Perception Skills Scale, the Auditory Perception Skills Scale, and the Basic Academic Skills Test. This phase established the baseline performance for all dependent variables.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003ePhase 2: Intervention.\u003c/b\u003e The infographic-based training program was implemented over 16 weeks, with three individual sessions per week for each child. Each session lasted between 30 and 40 minutes and was conducted by the researcher. Sessions were highly structured, typically including a brief warm-up activity, introduction of a new concept via an infographic, several interactive practice exercises (e.g., pointing, sorting, verbal response), and positive reinforcement for effort and success.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003ePhase 3: Post-testing (T2).\u003c/b\u003e Within one week of completing the final intervention session, the full battery of assessments was re-administered to each child under the same conditions as the pre-test. This phase measured the immediate effects of the intervention.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003ePhase 4: No-Intervention Period.\u003c/b\u003e A one-month period followed the post-test during which participants received no intervention from the researcher and continued with their standard school curriculum.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003ePhase 5: Follow-up Testing (T3).\u003c/b\u003e At the end of the one-month no-intervention period, the assessments were administered for a third and final time. This phase was crucial for determining the maintenance of skills over time.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Data Analysis\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAll data were analyzed using IBM SPSS Statistics, Version 28. Given the small sample size (N = 6), which violates the assumptions of normality required for parametric tests, a non-parametric analytical approach was adopted, consistent with best practices for small-N educational research (Kratochwill et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eDescriptive statistics\u003c/b\u003e (means, standard deviations, medians, and ranges) were calculated for all variables at the three time points (T1, T2, and T3) to summarize performance and track changes.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eThe \u003cb\u003eWilcoxon signed-rank test\u003c/b\u003e was used to analyze the differences between pre-test (T1) and post-test (T2) scores for all dependent variables (visual perception, auditory perception, and academic skills). This test is the non-parametric equivalent of a paired-samples t-test and is appropriate for comparing two related measurements from a single sample.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eTo assess skill maintenance, the Wilcoxon signed-rank test was also used to compare post-test (T2) and follow-up (T3) scores.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eTo analyze the overall change in academic skills across all three time points simultaneously, a \u003cb\u003eFriedman's test\u003c/b\u003e was conducted. This test is the non-parametric alternative to a one-way repeated measures ANOVA.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eThe significance level for all inferential tests was set at \u003cb\u003eα = .05\u003c/b\u003e.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/div\u003e"},{"header":"4. Results","content":"\u003cp\u003eThis section presents the statistical analyses of the data collected at pre-test (T1), post-test (T2), and the one-month follow-up (T3). The findings are organized sequentially to address the study's primary hypotheses concerning the impact of the infographic-based intervention on participants' perceptual skills, academic skills, and the subsequent maintenance of these effects. Given the sample size (N = 6), non-parametric tests were employed for all inferential analyses as specified in the Method section. A summary of descriptive and inferential statistics is provided in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003c/p\u003e\u003ch2\u003e4.1 Impact of the Intervention on Perceptual Skills\u003c/h2\u003e\u003cp\u003eThe first hypothesis predicted that the infographic-based intervention would lead to statistically significant improvements in both visual and auditory perception skills from pre-test to post-test.\u003c/p\u003e\u003cp\u003eDescriptive statistics revealed substantial gains in visual perception. The group's mean total score on the Visual Perception Skills Scale increased dramatically from pre-test (\u003cem\u003eM\u003c/em\u003e = 34.80, \u003cem\u003eSD\u003c/em\u003e = 6.85) to post-test (\u003cem\u003eM\u003c/em\u003e = 79.83, \u003cem\u003eSD\u003c/em\u003e = 15.58). A Wilcoxon signed-rank test confirmed that this increase was statistically significant, \u003cem\u003eZ\u003c/em\u003e = 2.21, \u003cem\u003ep\u003c/em\u003e = .027. The calculated effect size for this change was large (\u003cem\u003er\u003c/em\u003e = .90), indicating that the intervention had a highly impactful and positive effect on participants' visual processing abilities.\u003c/p\u003e\u003cp\u003eA similar and equally strong pattern was observed for auditory perception. Mean scores on the Auditory Perception Skills Scale rose from \u003cem\u003eM\u003c/em\u003e = 8.17 (\u003cem\u003eSD\u003c/em\u003e = 4.07) at pre-test to \u003cem\u003eM\u003c/em\u003e = 23.17 (\u003cem\u003eSD\u003c/em\u003e = 9.62) at post-test. This improvement was also found to be statistically significant via a Wilcoxon signed-rank test, \u003cem\u003eZ\u003c/em\u003e = 2.20, \u003cem\u003ep\u003c/em\u003e = .028. The effect size was identical to that for visual perception (\u003cem\u003er\u003c/em\u003e = .90), demonstrating a large and meaningful intervention effect on auditory processing skills.\u003c/p\u003e\u003ch2\u003e4.2 Impact of the Intervention on Basic Academic Skills\u003c/h2\u003e\u003cp\u003eThe second hypothesis posited that the observed improvements in perceptual skills would translate into significant gains in basic academic skills. This hypothesis was strongly supported by the data. A Friedman's test was conducted to evaluate overall changes in academic performance across the three time points (T1, T2, T3) for each of the three curriculum levels tested. The results were statistically significant for Level 1 (χ²(2) = 7.00, \u003cem\u003ep\u003c/em\u003e = .030), Level 2 (χ²(2) = 10.37, \u003cem\u003ep\u003c/em\u003e = .006), and Level 3 (χ²(2) = 10.14, \u003cem\u003ep\u003c/em\u003e = .006), indicating a significant overall effect of the intervention across all academic proficiency levels.\u003c/p\u003e\u003cp\u003eTo specifically assess the pre-test to post-test gain, post-hoc Wilcoxon signed-rank tests were performed. A statistically significant increase was found in the Basic Academic Skills Test scores at Level 1 (\u003cem\u003eZ\u003c/em\u003e = 2.20, \u003cem\u003ep\u003c/em\u003e = .028, \u003cem\u003er\u003c/em\u003e = .90), Level 2 (\u003cem\u003eZ\u003c/em\u003e = 2.23, \u003cem\u003ep\u003c/em\u003e = .026, \u003cem\u003er\u003c/em\u003e = .91), and Level 3 (\u003cem\u003eZ\u003c/em\u003e = 2.20, \u003cem\u003ep\u003c/em\u003e = .028, \u003cem\u003er\u003c/em\u003e = .90). The large effect sizes across all levels confirm that the intervention led to substantial and practically significant improvements in participants' reading and mathematics abilities. See Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003ch2\u003e4.3 Maintenance of Intervention Effects on Follow-Up\u003c/h2\u003e\u003cp\u003eThe final hypothesis addressed the sustainability of the intervention's impact by assessing the maintenance of skills at the one-month follow-up. Wilcoxon signed-rank tests were used to compare the scores from the post-test (T2) with those from the follow-up assessment (T3). See Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eFigure 3. Academic Skills performance by levels (Level 1, Level 2, Level 3) across Pretest, Posttest, and Follow-up assessments.\u003c/p\u003e\u003cp\u003eThe analysis revealed no statistically significant differences between post-test and follow-up scores for the total score on the Visual Perception Scale (\u003cem\u003eZ\u003c/em\u003e = 1.58, \u003cem\u003ep\u003c/em\u003e = .115) or the Auditory Perception Scale (\u003cem\u003eZ\u003c/em\u003e = 1.41, \u003cem\u003ep\u003c/em\u003e = .157). Similarly, no significant decline was observed in the Basic Academic Skills Test at Level 1 (\u003cem\u003eZ\u003c/em\u003e = 0.58, \u003cem\u003ep\u003c/em\u003e = .564), Level 2 (\u003cem\u003eZ\u003c/em\u003e = 1.41, \u003cem\u003ep\u003c/em\u003e = .157), or Level 3 (\u003cem\u003eZ\u003c/em\u003e = 1.00, \u003cem\u003ep\u003c/em\u003e = .317). The stability of the scores from post-test to follow-up demonstrates that the perceptual and academic gains achieved during the intervention were successfully maintained one month after its conclusion.\u003c/p\u003e\u003cp\u003eIn summary, the data provide robust, statistically significant support for all three study hypotheses. The infographic-based intervention was effective in enhancing perceptual and academic skills, and these gains were shown to be durable over time.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of Descriptive and Inferential Statistics for All Measures (N = 6)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeasure and Time Point\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean (M)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStd. Deviation (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWilcoxon Test (vs. Previous)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eEffect Size (\u003cem\u003er\u003c/em\u003e)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eVisual Perception Scale\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePre-Test (T1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePost-Test (T2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e79.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eZ\u003c/em\u003e = 2.21,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e = .027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.90\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFollow-Up (T3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e77.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eZ\u003c/em\u003e = 1.58,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e = .115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAuditory Perception Scale\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePre-Test (T1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePost-Test (T2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eZ\u003c/em\u003e = 2.20,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e = .028\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.90\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFollow-Up (T3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eZ\u003c/em\u003e = 1.41,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e = .157\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAcademic Skills Test (L1)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePre-Test (T1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePost-Test (T2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eZ\u003c/em\u003e = 2.20,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e = .028\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.90\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFollow-Up (T3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eZ\u003c/em\u003e = 0.58,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e = .564\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAcademic Skills Test (L2)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePre-Test (T1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePost-Test (T2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eZ\u003c/em\u003e = 2.23,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e = .026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.91\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFollow-Up (T3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eZ\u003c/em\u003e = 1.41,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e = .157\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAcademic Skills Test (L3)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePre-Test (T1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePost-Test (T2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eZ\u003c/em\u003e = 2.20,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e = .028\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.90\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFollow-Up (T3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eZ\u003c/em\u003e = 1.00,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e = .317\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eNote\u003c/b\u003e. L1, L2, L3 refer to Levels 1, 2, and 3 of the Basic Academic Skills Test. Effect size \u003cem\u003er\u003c/em\u003e is calculated as Z/√N for pre-post comparisons. A non-significant \u003cem\u003ep\u003c/em\u003e-value for follow-up tests indicates maintenance of skills.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThe findings of this study provide compelling evidence that a targeted, infographic-based intervention can significantly enhance both foundational perceptual skills and basic academic abilities in children with ASD. The statistically significant improvements observed from pre-test to post-test, coupled with the remarkable maintenance of these gains at the one-month follow-up, offer a robust validation of our primary hypotheses. This discussion will interpret these findings within the context of established neurocognitive theories of autism, situate them within the broader landscape of educational intervention research, and explore the study's profound implications for both theory and practice.\u003c/p\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003e5.1 Bridging the Perceptual Divide: The Mechanism of Infographic Efficacy\u003c/h2\u003e\u003cp\u003eThe primary contribution of this study is the demonstration of a successful, theory-driven intervention that directly addresses the perceptual-academic gap. The significant improvements in visual and auditory perception are not surprising when viewed through the lens of the core design principles of the infographic program. The intervention\u0026rsquo;s structure\u0026mdash;segmenting complex information into discrete, visually organized units\u0026mdash;is a direct pedagogical response to the challenges predicted by the Weak Central Coherence (WCC) theory (Happ\u0026eacute; \u0026amp; Frith, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Instead of requiring children to spontaneously derive global meaning from a cluttered field, the infographics provided a pre-organized structure, allowing them to leverage their detail-oriented processing style (an aspect of Enhanced Perceptual Functioning) in a productive manner. By presenting information in a clear, predictable, and visually salient format, the program likely reduced extraneous cognitive load, freeing up cognitive resources for processing and encoding the core content, a principle central to Cognitive Load Theory (Sweller, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Aldalalah, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCrucially, the intervention did not merely enhance perceptual skills in isolation; it facilitated their application in academic tasks. The observed transfer of gains to reading and mathematics supports the central premise of this paper: that for many children with ASD, the primary bottleneck to academic learning is perceptual, not conceptual. The infographics functioned as a \"cognitive bridge.\" In line with Dual-Coding Theory (Bi, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), the simultaneous presentation of visual icons and concise text (e.g., a numeral paired with a graphic representation of that quantity) created stronger, multi-modal memory engrams. This audio-visual binding is particularly critical for foundational literacy, where mapping graphemes to phonemes is essential (Jao Keehn et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Our findings suggest that by making this mapping explicit and visually anchored, the infographics provided the necessary scaffold for children who struggle with this integrative process, moving them beyond rote memorization to meaningful comprehension.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec25\" class=\"Section2\"\u003e\u003ch2\u003e5.2 The Durability of Learning: From Intervention to Internalization\u003c/h2\u003e\u003cp\u003ePerhaps the most significant finding of this study is the durability of the observed effects. The absence of a statistically significant decline in skills at the one-month follow-up stands in contrast to many educational interventions where skills regress once the structured support is withdrawn (Lovaas, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1987\u003c/span\u003e). This suggests that the infographic program facilitated not just performance but genuine learning and skill internalization. This sustained impact can be attributed to the intervention's alignment with the learners' intrinsic perceptual mechanisms. Rather than teaching a compensatory strategy that requires constant effort, the program presented information in a format that was more naturally processed. This likely led to a more efficient and deeper encoding of both the academic content and the perceptual strategies themselves. This finding underscores a critical point: interventions that work \u003cem\u003ewith\u003c/em\u003e the neurotype of the learner, rather than against it, have a far greater potential for producing lasting change (Pellicano \u0026amp; den Houting, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The stability of these gains provides a strong argument for the clinical and educational significance of this approach, moving it beyond a mere classroom activity to a potent tool for developmental change.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e\u003ch2\u003e5.3 Contextualizing the Findings within the Broader Literature\u003c/h2\u003e\u003cp\u003eThe results of this study both confirm and extend the existing literature. They align with a long-standing body of research advocating for the use of visual supports for individuals with ASD, which have been shown to improve understanding, reduce anxiety, and promote independence (Macoskey, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Our findings are also consistent with studies demonstrating the benefits of UDL principles in creating more accessible learning environments for neurodiverse students (Carrington et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHowever, this study makes several novel contributions. First, while the benefit of \"visual supports\" is a broad concept, our research isolates and empirically validates a specific, modern, and highly adaptable tool: the educational infographic. Second, unlike much of the previous research which has been descriptive or correlational, our quasi-experimental design provides causal evidence linking a targeted perceptual intervention directly to academic outcomes. We did not just show that children with better perception have better academic skills; we demonstrated that \u003cem\u003eimproving\u003c/em\u003e perception via a targeted intervention \u003cem\u003eleads to\u003c/em\u003e improved academic skills. This establishes a clear, evidence-based pathway for intervention that has been largely absent from the literature. Finally, the focus on both static and dynamic infographics speaks to an emerging area of research on how different presentation modalities impact learning in this population (van Rijssel, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), offering a nuanced contribution to the field of educational technology.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec27\" class=\"Section2\"\u003e\u003ch2\u003e5.4 Strengths, Limitations, and Future Directions\u003c/h2\u003e\u003cp\u003eThe primary strength of this study lies in its innovative, theory-driven intervention and its rigorous single-group, pre-post-follow-up design, which provides a strong signal of the intervention's efficacy and durability. The development of bespoke, curriculum-aligned assessment tools also ensures a high degree of content validity.\u003c/p\u003e\u003cp\u003eNevertheless, the study's limitations must be acknowledged. The most significant is the small, purposive sample (N\u0026thinsp;=\u0026thinsp;6). While appropriate for an intensive, exploratory study of this nature, the small sample size limits the generalizability of the findings and necessitates a non-parametric analytical approach. Future research should seek to replicate these results with a larger, more diverse sample of children with ASD across different age groups and support levels. A randomized controlled trial (RCT) would provide the gold-standard evidence for causal inference, allowing for a direct comparison between the infographic intervention and a traditional teaching or alternative intervention group.\u003c/p\u003e\u003cp\u003eFuture research could also explore several promising avenues. It would be valuable to investigate the differential effects of static versus animated infographics on specific skills, or to integrate interactive elements to enhance engagement further. Additionally, exploring the application of this methodology to more complex academic subjects (e.g., science, social studies) and older students is a logical next step. Finally, neuroimaging studies (e.g., fMRI or EEG) could be employed to investigate the neural mechanisms underlying these behavioral changes, potentially providing objective biomarkers of improved perceptual integration and cognitive efficiency.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec28\" class=\"Section2\"\u003e\u003ch2\u003e5.5 Implications for Educational Practice\u003c/h2\u003e\u003cp\u003eThe findings of this study have profound and immediately applicable implications for inclusive education. They suggest a critical need for a paradigm shift, moving away from a purely content-driven curriculum toward one that is perceptually informed.\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eFor Educators\u003c/b\u003e: Teachers can and should integrate infographics into their daily instruction. This does not require a complete overhaul of their curriculum but rather a transformation of how key concepts are presented. Infographics can be used to introduce new topics, summarize complex information, and provide visual instructions for assignments.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eFor Curriculum Developers\u003c/b\u003e: There is a clear mandate to develop and embed perceptually-aligned materials, like infographics, directly into core curricula. Textbooks and digital learning platforms should offer visual alternatives to dense text as a standard feature, in line with UDL principles.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eFor School Psychologists and Special Educators\u003c/b\u003e: The researcher-developed scales used in this study provide a template for creating functional assessment tools that can help identify specific points of breakdown in a child's perceptual-academic pathway, allowing for more precise and targeted intervention planning.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec29\" class=\"Section2\"\u003e\u003ch2\u003e5.6 Conclusion\u003c/h2\u003e\u003cp\u003eThis study successfully demonstrated that an infographic-based intervention is a powerful tool for bridging the perceptual-academic gap in children with ASD. By aligning instructional design with the inherent neurocognitive profiles of the learners, the program not only enhanced foundational perceptual skills but also fostered significant and durable gains in essential academic abilities. The results champion a move towards neurodiversity-affirming pedagogies that leverage students' strengths and provide the necessary scaffolds to navigate their challenges. Ultimately, this research suggests that to help a child with ASD succeed academically, we may not need to change the child, but rather, change the way we present the world of knowledge to them.\u003c/p\u003e\u003c/div\u003e"},{"header":"6. Limitations and Future Directions","content":"\u003cp\u003eWhile this study provides a robust proof-of-concept for the efficacy of infographic-based interventions, its contributions must be contextualized within its methodological limitations. The primary limitation is the small, purposive sample (N\u0026thinsp;=\u0026thinsp;6). Although the one-group pretest-posttest-follow-up design allows each participant to serve as their own control, providing a strong signal of individual change (Kazdin, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), the small N restricts the statistical power and limits the generalizability of the findings to the broader, highly heterogeneous ASD population. The results, while compelling, should be interpreted as a foundational rather than a definitive statement on the intervention's universal efficacy.\u003c/p\u003e\u003cp\u003eSecond, the study was conducted by the researcher, who also developed the intervention and assessment materials. While this ensures a high degree of fidelity in implementation, it introduces the potential for experimenter bias. Although standardized procedures were strictly followed, the lack of blind assessment is a limitation. Future replications would be strengthened by employing independent assessors who are blind to the study's hypotheses and the participants' intervention status.\u003c/p\u003e\u003cp\u003eFinally, while the study successfully demonstrated a transfer of skills to academic tasks, these tasks were measured via a researcher-developed test aligned with the intervention content. To establish broader generalization, future studies should include standardized, norm-referenced academic achievement tests and observational measures of classroom performance as outcome variables.\u003c/p\u003e\u003cp\u003eThese limitations pave a clear path for future research. The immediate next step is to replicate this study with a larger, more diverse sample within a randomized controlled trial (RCT) design. An RCT would allow for a direct comparison against a control group receiving traditional instruction, providing the gold-standard evidence needed for widespread adoption. Furthermore, future investigations could employ a component analysis to dismantle the intervention and determine the relative contributions of its specific elements (e.g., static vs. dynamic infographics, color-coding, textual brevity). Lastly, leveraging neuroimaging technologies like EEG to track changes in neural processing during infographic-based tasks could provide invaluable objective evidence of the intervention\u0026rsquo;s impact on the underlying perceptual mechanisms, moving the field from behavioral observation to neurocognitive validation.\u003c/p\u003e"},{"header":"7. Conclusion and Implications","content":"\u003cp\u003eThis study was conceptualized to address a fundamental, yet often overlooked, challenge in autism education: the chasm between atypical perceptual processing and the demands of academic learning. The findings unequivocally demonstrate that a targeted, infographic-based intervention serves as a powerful bridge across this gap. By systematically enhancing visual and auditory perception, the program produced not only significant and durable improvements in these foundational domains but also facilitated a remarkable and sustained transfer of these gains to essential academic skills in reading and mathematics.\u003c/p\u003e\u003cp\u003eThe implications of this research are both profound and pragmatic. For educational theory, it provides strong empirical support for a \u003cb\u003eperceptually-driven pedagogical model\u003c/b\u003e for ASD. It affirms that to unlock the academic potential of these learners, we must first address the foundational level at which they process information. The study repositions perceptual support not as a mere accommodation, but as a core mechanism for enabling higher-order cognition. It strongly suggests that for children on the spectrum, the path to academic competence is paved with perceptual clarity.\u003c/p\u003e\u003cp\u003eFor educational practice, this study offers a readily implementable, evidence-based tool that respects the neurotype of the learner. It moves beyond abstract principles and provides a concrete methodology that educators can adopt to make curricula more accessible and effective. The success of this intervention serves as a cornerstone, a foundational piece of evidence arguing that by redesigning the delivery of information to align with the autistic mind, we can foster authentic learning and create truly inclusive educational ecosystems. This work does not merely add another intervention to the existing repertoire; it provides a new lens through which to view and approach autism education\u0026mdash;one that begins with perception.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cb\u003eAuthor Note\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis research article is derived from the doctoral dissertation titled \u003cem\u003e\u0026ldquo;Using Infographics to Develop Visual and Auditory Perception Skills and Their Effect on Improving Basic Academic Skills among Integrated Children with Autism Spectrum Disorder\u0026rdquo;\u003c/em\u003e, submitted to the Faculty of Education, University of Al-Arish, Arab Republic of Egypt, in partial fulfillment of the requirements for the Ph.D. degree in Special Education. The authors gratefully acknowledge the support and guidance provided by the Faculty of Education at the University of Al-Arish and extend sincere thanks to the participating schools, teachers, and families who made this research possible.\u003c/p\u003e\n\u003cp\u003eCorrespondence concerning this article should be addressed to Dr. Ahmed Fadlallah Shalally Hassan, Department of Special Education, Faculty of Education, University of Al-Arish, Arab Republic of Egypt. Email: [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e(Data tables and full measurement specifications are excerpted from the doctoral dissertation.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author wishes to express sincere gratitude to the children and educators who participated in this study, whose insights enriched the validation process of the pictorial visual perception scale. Special thanks are due to the administration of inclusive primary schools for their cooperation during data collection. The author also acknowledges the valuable linguistic support provided. Appreciation is extended to peer reviewers whose constructive feedback will help enhance the clarity and impact of this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the principles of the Declaration of Helsinki. Ethical approval was obtained from the Research Ethics Committee of the Faculty of Education, Arish University (Approval No. EDU/REC/2024/07; dated September 22, 2024). Written informed consent was obtained from the parents or legal guardians of all children participating in the study. Verbal assent was also obtained from the children where possible.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Not applicable. (This study does not contain any individual person\u0026rsquo;s data in any form, such as individual details, images, or videos).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The datasets generated and/or analyzed during the current study are not publicly available due to privacy and ethical restrictions concerning child participants but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA.F.S.H. conceived the study, designed the instrument and the intervention, collected and analyzed the data, and wrote the manuscript. M.A.A.E. supervised the research, contributed to the study design and data interpretation, and critically revised the manuscript. N.M.A.A. co-supervised the research, assisted in the methodological design, and reviewed the final manuscript. All authors read and approved of the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAghaz A, Salehi F, Taaki F, Jadidi H, Bahrami A, Hemmati E (2018) Pattern of phonological awareness skills in children with autism spectrum disorders. Koomesh 20(4):659\u0026ndash;666\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAldalalah OM (2021) The Effectiveness of Infographic via Interactive Smart Board on enhancing Creative Thinking: A Cognitive Load Perspective. 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J Autism Dev Disord 53(1):307\u0026ndash;319. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10803-021-05381-z\u003c/span\u003e\u003cspan address=\"10.1007/s10803-021-05381-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Department of Special Education, Faculty of Education, Arish University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Visual Perception, Auditory Perception, Infographics, Basic Academic Skills, Autism Spectrum Disorder (ASD)","lastPublishedDoi":"10.21203/rs.3.rs-8096304/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8096304/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eChildren with Autism Spectrum Disorder (ASD) often face significant academic challenges linked to underlying perceptual processing deficits. However, interventions that specifically leverage their unique perceptual profiles to foster academic growth remain underexplored. This study investigated the effectiveness of a novel, infographic-based training program designed to enhance visual and auditory perception skills and, consequently, improve basic academic skills (reading and mathematics) in children with ASD.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e\u003cp\u003eA quasi-experimental one-group pretest-posttest-follow-up design was employed. The sample consisted of six children (4 males, 2 females) diagnosed with ASD, aged 6\u0026ndash;8 years, enrolled in inclusive school settings. The intervention comprised a 16-week, researcher-developed program utilizing educational infographics. Participants were assessed using researcher-developed scales for visual perception, auditory perception, and a test of basic academic skills at three time points: before the intervention (pre-test), immediately after its completion (post-test), and one month later (follow-up). Data were analyzed using non-parametric Wilcoxon signed-rank and Friedman's tests.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe analysis revealed statistically significant improvements from pre-test to post-test across all primary outcome measures: visual perception, auditory perception, and basic academic skills (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05). The gains were substantial, indicating a strong and positive intervention effect. Furthermore, no statistically significant decline in performance was observed between the post-test and the one-month follow-up assessments, demonstrating the successful maintenance and sustained impact of the skills acquired.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThe findings provide robust evidence that a targeted, infographic-based intervention is an effective tool for enhancing both foundational perceptual abilities and essential academic skills in children with ASD. By presenting information in a visually structured and perceptually aligned format, infographics can successfully bridge the critical gap between perceptual processing and academic learning. This study offers a practical, theoretically grounded approach for educators and clinicians to support the academic development of this population within inclusive environments.\u003c/p\u003e","manuscriptTitle":"Bridging the Perceptual-Academic Gap: How Infographics Enhance Basic Academic Skills by Improving Auditory and Visual Perception in Children with ASD","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-13 14:53:52","doi":"10.21203/rs.3.rs-8096304/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6469cea3-938a-4e31-8d4e-872d8b41492e","owner":[],"postedDate":"November 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57870428,"name":"Special Education"}],"tags":[],"updatedAt":"2025-11-13T14:53:52+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-13 14:53:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8096304","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8096304","identity":"rs-8096304","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}