Practices of Evidence-based Mathematics Interventions for Children with Autism Spectrum Disorder: A Cross-sectional Study

Abstract

Aims:

This study investigates the practices and perceptions of educators regarding evidence-based mathematics interventions for children with autism spectrum disorder (ASD).

Methods:

A quantitative survey design was employed, collecting data from 250 teachers in special and inclusive education settings.

Results:

Findings revealed strong educator awareness and positive perceptions of the effectiveness of strategies such as explicit instruction, the concrete-representational-abstract sequence, task analysis, and technology-assisted learning like video modeling. Despite high implementation rates and recognition of these practices’ benefits for conceptual understanding and skill generalization, significant barriers impeded consistent application. Primary challenges included insufficient training, time constraints, limited resources, and a lack of institutional support.

Conclusions:

The study concludes that a critical research-to-practice gap persists, underscoring the necessity for enhanced professional development, systemic resource allocation, and stronger administrative support to translate evidence-based knowledge into sustained, high-fidelity classroom practice for improved mathematics outcomes in students with ASD.

INTRODUCTION

Mathematics is a foundational subject in modern education, serving as the basis for higher-order problem-solving, critical thinking, and participation in academic and vocational opportunities. However, for children with autism spectrum disorder (ASD), mathematics learning presents unique challenges due to the interplay of cognitive, social, and behavioral characteristics associated with the condition.[1] ASD is characterized by difficulties in communication, social interaction, and restricted or repetitive behaviors, but many children with ASD also display uneven cognitive profiles. For example, while some excel in areas such as pattern recognition and rule-based reasoning, others experience significant difficulties in mathematical problem solving, conceptual understanding, and the application of skills to real-world contexts.[2]

Given these complexities, research in the past two decades has increasingly focused on the design and implementation of evidence-based interventions (EBIs) for teaching mathematics to children with ASD. Evidence-based practices (EBPs) are interventions that have been validated through rigorous research and shown to produce reliable, positive outcomes. Examples of evidence-based mathematics interventions include explicit instruction, task analysis, systematic prompting, visual support, peer-mediated instruction, and technology-assisted learning. Such approaches not only address the cognitive needs of children with ASD but also provide structure and predictability, which align well with their learning profiles.[3]

A key emphasis in evidence-based mathematics interventions is their grounding in applied behavior analysis (ABA) principles and constructivist learning strategies. ABA-based interventions rely on reinforcement, shaping, and prompting to build stepwise mastery of mathematical tasks. At the same time, constructivist approaches encourage children to explore, manipulate, and generalize mathematical concepts, promoting meaningful understanding. Interventions such as concrete–representational–abstract (CRA) instruction, schema-based instruction, and video modeling have shown promise in improving computational fluency, problem solving, and functional numeracy among children with ASD.[4,5]

Despite the growing body of research, studies consistently highlight difficulties in the practical implementation of these EBIs in schools. Teachers often struggle with limited training, lack of resources, and difficulties aligning EBIs with existing curricula. Furthermore, many interventions are tested under controlled experimental conditions but are not consistently replicated in diverse, real-world educational settings. These gaps call for research that not only examines the theoretical effectiveness of EBIs but also explores their practical use and challenges in everyday mathematics classrooms for children with ASD.[6,7]

This study focuses on the practices of evidence-based mathematics interventions in educational settings for children with ASD. By exploring how teachers select, implement, and adapt EBIs, this study seeks to bridge the gap between research and classroom practice. It contributes to the broader goal of improving educational outcomes and fostering independence among children with ASD through effective mathematics instruction. Although numerous EBIs for mathematics instruction in ASD populations have been documented (e.g., explicit instruction, CRA, peer-mediated learning), most studies have focused on intervention efficacy in controlled environments rather than their actual use in classroom contexts. There is a lack of research investigating:

1. How teachers in inclusive and special education settings implement EBIs in mathematics

2. The extent to which teachers adapt interventions to meet the diverse needs of children with ASD

3. The barriers and enablers influencing teachers’ ability to apply EBIs consistently.

This gap highlights the need for practice-oriented research that captures teachers’ perspectives and classroom realities in implementing evidence-based mathematics interventions.

Children with ASD face distinct challenges in mathematics learning that require structured, evidence-based instructional strategies. While a wide range of EBIs has demonstrated effectiveness in controlled research settings, there is insufficient understanding of their actual use, adaptation, and sustainability in real classroom contexts. Without this knowledge, there is a risk of disconnect between research recommendations and educational practice, limiting the potential of EBIs to improve mathematical outcomes for children with ASD. The problem, therefore, is a lack of systematic investigation into the practices of implementing evidence-based mathematics interventions for children with ASD in schools.

The study aims to investigate the practices of using evidence-based mathematics interventions for children with ASD. Specifically, it seeks to:

1. Identify the evidence-based instructional strategies currently used by teachers to teach mathematics to children with ASD

2. Examine how teachers adapt and implement EBIs in diverse classroom contexts

3. Explore the challenges teachers face in applying EBIs consistently

4. Provide recommendations for strengthening teacher preparation and institutional support for evidence-based mathematics instruction for ASD learners.

This study holds theoretical, practical, and policy significance:

1. Theoretical significance: It extends the literature on mathematics education for ASD by shifting the focus from intervention efficacy in controlled studies to implementation practices in real classrooms

2. Practical significance: The findings will guide teachers in selecting, adapting, and applying EBIs effectively to improve mathematics outcomes for children with ASD

3. Policy significance: The study will inform policymakers and curriculum designers about the support systems, resources, and professional development needed to embed EBIs into school practices sustainably.

Ultimately, this research supports the global agenda for inclusive education by promoting the use of empirically validated practices that empower children with ASD to achieve greater independence, functional numeracy, and academic success.

LITERATURE REVIEW

Children with ASD display heterogeneous profiles of strengths and difficulties that influence their learning of mathematics. While some children with ASD exhibit strong pattern recognition or rule-based reasoning, many experience difficulties with language-mediated problem solving, generalization of skills, and applying mathematical knowledge to everyday contexts. Given the centrality of numeracy to independent living and later vocational opportunities, educators and researchers have prioritized development and validation of EBIs tailored to the cognitive, behavioral, and social characteristics of learners with ASD. This review synthesizes recent empirical and review literature (2018–2024) focused on EBIs in mathematics for children with ASD, addressing: (a) the nature of mathematics difficulties in ASD; (b) core intervention approaches and their evidence base; (c) technology-mediated practices; (d) implementation issues (fidelity, teacher training, and generalization); and (e) gaps and directions for future research.[8,9]

Mathematics learning profiles and challenges in autism spectrum disorder

Understanding the nature of mathematical difficulties in ASD is a necessary precursor to effective intervention design. Children with ASD commonly present uneven cognitive profiles: relative strengths in visual-spatial reasoning and rule learning coexist with weaknesses in language, working memory, and flexible problem solving. These characteristics create obstacles for traditional mathematics instruction, which often relies on verbal instruction, abstract symbolic reasoning, and classroom discourse. Two practical consequences are especially relevant for intervention design. First, children with ASD may learn procedures without developing conceptual understanding or the ability to generalize to new contexts. Second, co-occurring attention difficulties, anxiety, and sensory sensitivities can reduce engagement and the effectiveness of standard classroom practices. Heterogeneity requires interventions that are explicit, highly structured, visually supported, and designed to promote generalization and maintenance.[10]

Core evidence-based instructional approaches

A growing body of research supports several core instructional strategies for teaching mathematics to learners with ASD. Many of these approaches explicit instruction, task analysis with systematic prompting, CRA sequencing, schema-based instruction, and peer-mediated strategies have been studied in special education broadly and show promising applicability for ASD populations.[11]

Explicit instruction and systematic prompting

Explicit instruction defined by clear learning objectives, teacher modeling, guided practice, and immediate corrective feedback has robust empirical support in special education and is frequently recommended for students with ASD. Studies indicate that explicit teaching of discrete skills (e.g., coin identification, making change, and measurement procedures) enhances acquisition and retention. Systematic prompting hierarchies (e.g., least-to-most prompting) combined with reinforcement and systematic fading procedures support independence and reduce prompt dependence. The controlled, predictable nature of explicit instruction aligns well with many children’s preference for routine and clear structure.[12]

Task analysis and chaining

Task analysis decomposes complex functional mathematics tasks (e.g., making a purchase, following a recipe) into component steps that can be taught sequentially, assessed, and reinforced. Chaining methods forward, backward, or total task are effective for building multistep routines and have been used successfully with ASD learners to teach functional routines involving numeracy. Evidence suggests that task analysis coupled with prompting and reinforcement promotes procedural competence and increases opportunities for independent performance across contexts when generalization is explicitly practiced.[13]

Concrete–representational–abstract and manipulatives

CRA instruction begins with hands-on manipulatives, moving to pictorial representations, then to symbolic notation supports conceptual understanding and bridges concrete experience with abstract reasoning. For students with ASD, manipulatives and visual supports scaffold meaning and reduce cognitive load associated with symbol manipulation. Several syntheses report gain procedural fluency and conceptual understanding when CRA is integrated with explicit instruction.[14]

Schema-based instruction and problem-type strategies

Schema-based instruction teaches learners to identify problem types (schemas) and apply organized solution strategies. While most schema research has focused on students with learning disabilities, emerging evidence supports adaptation for ASD populations, particularly when problems are contextualized in functional scenarios such as shopping or time management. Schema approaches can be beneficial when combined with visual organizers and stepwise prompts that reduce language processing demands.[15]

Peer-mediated and social approaches

Peer-mediated strategies (peer tutoring and cooperative learning) show promise for promoting academic skills and social interaction among learners with ASD. When peers are trained to scaffold mathematical tasks, students with ASD can benefit from repeated modeling, immediate feedback, and authentic social contexts for practicing skills. These approaches are especially relevant in inclusive classrooms where typical peers can extend opportunities for naturalistic practice and generalization.[16,17]

Technology-mediated intervention

Technological innovations have rapidly expanded the repertoire of intervention tools for mathematics instruction. Digital manipulatives, tablet apps, video modeling, virtual reality (VR), and augmented reality (AR) tools have been used to deliver individualized practice, scaffold instruction, and promote generalization.[18]

Video modeling and video-based instruction

Video modeling showing a target behavior or skill via video examples has a strong evidence base for teaching social, communication, and functional skills to children with ASD. In mathematics, video models demonstrate stepwise routines (e.g., counting money, following measurement steps) increase learners’ independence and provide a consistent, visually rich model that can be replayed multiple times. Meta-analytic and systematic reviews emphasize video modeling’s utility for procedural skill acquisition and its ease of implementation in schools.[19,20]

Interactive and adaptive software

Interactive software and adaptive learning platforms can present tasks at individualized difficulty levels, provide immediate feedback, and record performance data for teachers. Emerging studies show that such software improves on-task behavior and offers increased opportunities for repeated, distributed practice important for mastery of procedural and functional skills. Adaptive systems that modify task demands in real time can reduce frustration and support steady progress.[21]

Virtual and augmented reality

VR and AR provide immersive and contextualized environments where students can practice mathematics within simulated real-world scenarios (e.g., virtual shopping and cooking). Although research on VR/AR specifically for mathematics instruction in ASD is nascent, initial studies with broader instructional aims suggest enhanced engagement and improved transfer when tasks are highly authentic and supported by scaffolding. The potential of these technologies for safe, repeatable practice is promising but requires attention to accessibility, cost, and sensory considerations for ASD learners.[22,23]

Implementation, fidelity, and teacher preparation

Effectiveness of EBIs depends critically on implementation quality teacher knowledge, training, fidelity monitoring, and contextual support. Several reviews note that positive outcomes observed in controlled research are not always replicated in typical classrooms due to implementation barriers.[24]

Teacher knowledge and professional development

Many teachers report insufficient preservice or in-service preparation in EBIs specific to mathematics for ASD. Professional development that is job-embedded, content-focused, and includes coaching and feedback is more effective than one-off workshops. Studies advocating scalable PD models recommend combining theoretical foundations (e.g., ABA principles) with practical lesson modeling, coplanning, and fidelity monitoring.[25,26]

Fidelity, measurement, and outcome indicators

Fidelity of implementation extent to which teachers deliver interventions as designed, is often underreported in studies but is a crucial mediator of effectiveness. Reliable measures of fidelity and practical monitoring tools are needed to ensure EBIs are delivered with integrity in real classrooms. Outcome measurements should extend beyond acquisition to include generalization, maintenance, and functional outcomes such as independence in daily routines and participation in community activities.[27]

Generalization and maintenance

One enduring challenge is promoting generalization across contexts and maintenance of learned skills over time. Interventions that embed practice across settings (home, classroom, and community), involve multiple exemplars, and explicitly teach generalization strategies show better long-term outcomes. Collaboration with families and community partners enhances opportunities for naturalistic practice but requires systemic support and training for caregivers.[28]

Contextual and equity considerations

Research increasingly acknowledges the influence of cultural, socioeconomic, and systemic factors on access to EBIs. Disparities in resources, teacher expertise, and technology access shape who benefits from interventions. Inclusive education policies and frameworks such as Universal Design for Learning are advocated as means to design flexible curricula that can accommodate diverse learners, but implementation varies widely across regions and schools.[29,30]

Gaps and directions for future research

Despite strong evidence supporting EBIs for learners with ASD, several research gaps remain. Most studies rely on small samples and controlled settings, limiting understanding of scalability in real-world classrooms. Longitudinal research is needed to examine the sustainability of outcomes and their impact on adult life, including employment and independent living. Further investigation is also required to identify the most effective features of technology-based interventions and to understand how individual characteristics, such as language and cognitive abilities, influence intervention effectiveness. Additionally, implementation of science approaches can help identify factors that support the sustained adoption of EBIs in educational settings. Finally, future research should prioritize culturally responsive and cost-effective models to improve equity and access for diverse and underserved populations.[31,32]

The literature since 2018 converges on a set of instructional practices that are promising for teaching mathematics to children with ASD: explicit instruction, task analysis with systematic prompting, CRA sequencing, schema-based approaches, peer-mediated strategies, and technology-enhanced interventions (video modeling and adaptive software). These approaches align with the learning profiles of many children with ASD by providing structure, visual support, and opportunities for repeated practice. However, the effectiveness of these EBIs in real classrooms depends on quality of implementation, teacher training, and systemic support that promote generalization and maintenance. Future research should prioritize large-scale, longitudinal, and implementation-focused studies that attend to heterogeneity, equity, and sustainable delivery models so that evidence-based mathematics instruction can meaningfully improve functional outcomes for children with ASD.

RESEARCH METHODOLOGY

Research design

This study adopted a quantitative, descriptive survey design. The design was considered appropriate because it provides a systematic way to collect standardized data from a relatively large group of participants and to describe trends, attitudes, and practices related to the use of evidence-based mathematics interventions.[33] By employing this design, the research focuses on documenting how teachers implement evidence-based strategies in real classrooms, their perceptions of effectiveness, and the challenges they encounter, without manipulating any variables.

Population of the study

The target population comprised of teachers and special educators who teach mathematics to children with ASD at elementary and secondary school levels. This included:

• Teachers working in inclusive education settings where children with ASD learn alongside typically developing peers

• Educators in special education schools or resource centers that specifically serve children with ASD

• Educators hold specialized training or diplomas in special education, autism education, or educational psychology.

This population was selected because these professionals have direct experience with both mathematics instruction and the use (or nonuse) of EBIs in practice.

Sample and sampling of the study

A sample of n = 250 teachers was selected using stratified random sampling to ensure representation from both inclusive and special education settings. The population was stratified into two groups:

1. Teachers from inclusive schools

2. Teachers from special education schools or autism centers.

From each stratum, participants were chosen proportionally to their size in the population. This ensured that the perspectives of both inclusive and special educators were adequately captured. The sample size was determined using Cochran’s formula for survey studies to achieve adequate statistical power.

Instrument development

The main data collection tool was a structured questionnaire developed after a comprehensive review of relevant literature. The questionnaire was divided into five sections:

1. Demographics (age, gender, qualification, teaching experience, and type of school)

2. Awareness of EBPs for mathematics instruction

3. Implementation of EBPs in teaching mathematics to children with ASD (e.g., explicit instruction, CRA, task analysis, and video modeling)

4. Perceived effectiveness of interventions

5. Challenges/barriers in applying EBPs.

Items were constructed using a 5-point Likert scale ranging from strongly agree (5) to strongly disagree (1). The total number of items was 40, aligned with the study’s objectives.

Validity of the research instrument

The validity of the instrument was ensured through expert review. A panel of five experts in special education, educational psychology, and autism intervention reviewed the questionnaire for clarity, relevance, and content appropriateness. Based on their feedback, ambiguous items were revised, redundant questions were removed, and content validity was established. A Content Validity Index was calculated, with results above 0.85, which indicated strong agreement among experts that the instrument adequately represented the intended constructs.

Reliability of the research instrument

To establish reliability, a pilot study was conducted with 30 teachers who met the inclusion criteria but were not part of the final sample. The responses were analyzed using Cronbach’s alpha to measure internal consistency. The overall reliability coefficient was α =0.89, which is considered highly acceptable. Subscales showed reliability ranging from 0.82 to 0.88, confirming that the instrument was consistent and dependable.

Data collection procedure

After obtaining institutional approval and informed consent from participants, the final questionnaire was distributed through both online platforms (Google Forms and email) and printed copies in schools to maximize participation. Respondents were assured of confidentiality and anonymity. Data collection took place over a 6-week period. Follow-up reminders were sent to ensure a high response rate, resulting in 230 valid responses out of 250 distributed questionnaires (92% response rate).

Data analysis procedure

Data were coded and analyzed using Statistical Package for the Social Sciences (SPSS, version 26, IBM Corporation, Armonk, NY, USA). The following analyses were performed:

• Descriptive statistics (means, standard deviations, frequencies, and percentages) to summarize demographic characteristics and response patterns

• Independent samples t-tests to compare the practices of teachers from inclusive versus special education settings

• One-way analysis of variance (ANOVA) to examine differences in practices and perceptions across teacher qualification levels (e.g., diploma, master’s, and PhD).

Findings were presented in tabular and graphical formats with interpretation in line with the research objectives.

Table 1 shows that most respondents were female (62%), middle-aged (55.2% between 41 and 50 years), and highly qualified, with the majority holding a master’s degree (58%) followed by M.Phil.(38%). A large portion of participants were from urban areas (78%) and had 6–10 years of teaching experience (52.8%). These demographics suggest that the study largely reflects the perspectives of experienced, urban-based, and well-qualified teachers, which adds depth to the findings on EBPs.

Table 1.

Frequency distribution of respondents by demographics

Title	Description	Frequency (%)
Gender	Male	95 (38.0)
	Female	155 (62.0)
Age of respondents (years)	21–30	5 (2.0)
	31–40	81 (32.4)
	41–50	138 (55.2)
	51–60	26 (10.4)
Qualification	Master	145 (58.0)
	M.Phil.	95 (38.0)
	PHD	10 (4.0)
Area of posting	Rural	55 (22.0)
	Urban	195 (78.0)
Experience year	1–5	48 (19.2)
	6–10	132 (52.8)
	11–15	57 (22.8)
	>15	13 (5.2)
Total	-	250 (100)

Table 2 reveals that teachers demonstrated a strong awareness of EBPs (overall mean scores above 4.0). Most participants agreed that EBPs are essential for teaching mathematics to children with ASD (M = 4.46), and many had received professional training (M = 4.35). Teachers also reported updating themselves with recent research (M = 4.23). This suggests that the majority not only understand EBPs but also value them as crucial for effective instruction.

Table 2.

Awareness of evidence-based interventions

Statements of questions	5, n (%)	4, n (%)	3, n (%)	2, n (%)	1, n (%)	Mean	SD
I am familiar with the term “evidence-based practices” in mathematics instruction	123 (49)	110 (44)	12 (5)	5 (2)	0	4.40	0.68
EBPs are essential for teaching mathematics to children with ASD	120 (48)	124 (50)	6 (2)	0	0	4.46	0.55
I can differentiate between evidence-based and traditional teaching strategies	105 (42)	136 (54)	7 (3)	0	2 (1)	4.37	0.62
I have received professional training on evidence-based mathematics interventions	120 (48)	111 (44)	8 (3)	9 (4)	2 (1)	4.35	0.78
Awareness of EBPs improves teachers’ instructional confidence	80 (32)	136 (54)	23 (9)	11 (4)	0	4.14	0.76
I regularly update myself with recent research on EBPs in mathematics	102 (41)	113 (45)	26 (10)	9 (4)	0	4.23	0.78

SD=Standard deviation, EBPs=Evidence-based practices, ASD=Autism spectrum disorder

Table 3 indicates that teachers actively apply various evidence-based strategies in their classrooms, with mean scores consistently above 4.0. High levels of implementation were observed for task analysis (M = 4.26), CRA sequence (M = 4.26), adapting lessons to IEPs (M = 4.32), and real-life problem-solving activities (M = 4.26). This reflects a strong commitment to structured, individualized, and practical approaches in teaching mathematics to children with ASD.

Table 3.

Implementation of evidence-based practices in teaching mathematics

Statements of questions	5, n (%)	4, n (%)	3, n (%)	2, n (%)	1, n (%)	Mean	SD
I use explicit instruction (step-by-step modeling, guided practice) while teaching math to ASD learners	91 (36)	128 (51)	27 (11)	2 (1)	2 (1)	4.22	0.73
I apply task analysis to break down complex math tasks into smaller steps	95 (38)	133 (53)	17 (7)	3 (1)	2 (1)	4.26	0.71
I use systematic prompting (least-to-most or most-to-least) for math tasks	84 (34)	142 (57)	18 (7)	0 (0)	6 (2)	4.19	0.77
I follow the CRA sequence in teaching math	108 (43)	116 (46)	14 (6)	8 (3)	4 (2)	4.26	0.83
I integrate schema-based instruction to help students solve word problems	85 (34)	137 (55)	21 (8)	2 (1)	5 (2)	4.18	0.78
I embed visual supports (charts, diagrams, number lines) in my teaching	84 (34)	124 (50)	32 (13)	8 (3)	2 (1)	4.12	0.81
I implement peer-assisted learning in mathematics instruction for ASD students	82 (33)	137 (55)	22 (9)	6 (2)	3 (1)	4.16	0.77
I use real-life problem-solving activities (shopping, cooking) in teaching math	93 (37)	135 (54)	16 (6)	6 (2)	0	4.26	0.68
I adapt mathematics lessons according to the IEP of each child	105 (42)	123 (49)	18 (7)	4 (2)	0	4.32	0.68
I incorporate reinforcement strategies to encourage student’s progress in math	76 (30)	152 (61)	15 (6)	7 (3)	0	4.19	0.67

SD=Standard deviation, ASD=Autism spectrum disorder, CRA=Concrete–representational–abstract, IEP=Individualized education plans

Table 4 shows that teachers widely integrate technology into mathematics instruction for ASD students, with mean values ranging from 4.16 to 4.29. Video modeling (M = 4.29) and digital manipulatives (M = 4.23) were particularly common, while institutional support for technology also scored positively (M = 4.20). This suggests that technology is not only viewed as an effective tool but is also being actively used to enhance engagement and generalization of skills.

Table 4.

Technology integration in mathematics instruction

Statements of questions	5, n (%)	4, n (%)	3, n (%)	2, n (%)	1, n (%)	Mean	SD
I use digital manipulatives (apps, software) for teaching math concepts	89 (36)	136 (54)	19 (8)	6 (2)	0	4.23	0.69
Video modeling is part of my mathematics instruction for ASD learners	99 (40)	128 (51)	19 (8)	4 (2)	0	4.29	0.67
I integrate interactive learning platforms (e.g.,, math apps) to improve engagement	85 (34)	131 (52)	23 (9)	11 (4)	0	4.16	0.76
Technology helps students with ASD generalize math skills to real-life situations	87 (35)	134 (54)	18 (7)	8 (3)	3 (1)	4.18	0.79
Use of technology increases student motivation and participation in math lessons	89 (36)	133 (53)	24 (10)	4 (2)	0	4.23	0.68
My institution provides adequate technological support for EBPs in math	90 (36)	126 (50)	27 (11)	7 (3)	0	4.20	0.74

SD=Standard deviation, ASD=Autism spectrum disorder, EBPs=Evidence-based practices

Table 5 describes the teachers strongly perceived EBPs as effective in improving learning outcomes for children with ASD. High agreement was recorded for peer-assisted strategies fostering social and academic skills (M = 4.36), technology-based EBPs being more effective than traditional methods (M = 4.38), and improvements in conceptual understanding (M = 4.31). These findings highlight that teachers recognize EBPs as impactful in both academic and functional areas of mathematics learning.

Table 5.

Perceived effectiveness of evidence-based practices

Statements of questions	5, n (%)	4, n (%)	3, n (%)	2, n (%)	1, n (%)	Mean	SD
EBPs improve mathematical accuracy among children with ASD	96 (38)	134 (54)	18 (7)	2 (1)	0	4.30	0.63
EBPs enhance student’s problem-solving ability	111 (44)	108 (43)	23 (9)	4 (2)	4 (2)	4.27	0.82
EBPs improve conceptual understanding rather than rote memorization	102 (41)	131 (52)	12 (5)	3 (1)	2 (1)	4.31	0.69
Peer-assisted strategies foster both social and academic skills	98 (39)	144 (58)	8 (3)	0	0	4.36	0.54
Technology-based EBPs are more effective than traditional teaching	106 (42)	132 (53)	12 (5)	0	0	4.38	0.58
Functional mathematics instruction (e.g.,, money, time) improves independence of ASD students	87 (35)	135 (54)	26 (10)	2 (1)	0	4.23	0.66
EBPs significantly enhance learning outcomes in mathematics for ASD learners	96 (38)	138 (55)	14 (6)	2 (1)	0	4.31	0.61

SD=Standard deviation, ASD=Autism spectrum disorder, EBPs=Evidence-based practices

Table 6 indicates the despite of strong awareness and implementation, teachers reported notable challenges. Lack of training (M = 4.34), time constraints (M = 4.32), and limited resources (M = 4.26) were the most significant barriers. Institutional and administrative support was also rated as insufficient (M = 4.14). These findings underline that while teachers value EBPs, systemic and structural barriers hinder consistent application.

Table 6.

Barriers and challenges

Statements of questions	5, n (%)	4, n (%)	3, n (%)	2, n (%)	1, n (%)	Mean	SD
Lack of training hinders my ability to use EBPs in teaching mathematics	107 (43)	125 (50)	16 (6)	0	2 (1)	4.34	0.67
Limited resources prevent the application of EBPs effectively	103 (41)	122 (49)	13 (5)	10 (4)	2 (1)	4.26	0.80
Time constraints reduce opportunities to implement EBPs in math instruction	109 (44)	116 (46)	21 (8)	4 (2)	0	4.32	0.70
Large class sizes make it difficult to use individualized EBPs	92 (37)	134 (54)	18 (7)	4 (2)	2 (1)	4.24	0.72
Curriculum guidelines do not emphasize the importance of EBPs	79 (32)	153 (61)	7 (3)	11 (4)	0	4.20	0.69
Lack of institutional and administrative support limits my use of EBPs	88 (35)	123 (49)	26 (10)	11 (4)	2 (1)	4.14	0.83

SD=Standard deviation, EBPs=Evidence-based practices

Table 7 shows the t-test results in which no significant difference between male and female teachers in their use of EBPs (P = 0.241). This shows that gender does not play a determining role in teachers’ awareness, implementation, or perceptions of EBPs.

Table 7.

Comparison of gender

Gender	n	Mean	SD	df	t	Significant (two-tailed)
Male	95	149.97	10.54	248	1.18	0.241
Female	155	148.46	9.35

SD=Standard deviation

Table 8 shows a significant difference was found between rural and urban teachers (P < 0.05), with rural teachers reporting higher mean scores (M = 154.67) compared to urban teachers (M = 147.45). This suggests that rural educators may be more consistent in implementing EBPs, possibly due to smaller class sizes or greater reliance on structured methods.

Table 8.

Comparison of area

Area	n	Mean	SD	df	t	Significant (two-tailed)
Rural	55	154.67	11.19	248	5.05	0
Urban	195	147.45	8.80

SD=Standard deviation

Table 9 reveals the ANOVA results which are significant differences across age groups (P < 0.05). This indicates that teachers’ practices and perceptions of EBPs vary with age, with mid-career teachers (31–50 years) likely demonstrating stronger implementation compared to younger or older counterparts.

Table 9.

Comparison of age

Age	Sum of squares	df	Mean square	F	Significant
Between groups	2951.92	3	983.97	11.48	0.00
Within groups	21,078.76	246	85.69
Total	24,030.68	249

Table 10 shows the significant differences that were also observed across qualification levels (P < 0.05). Teachers with higher qualifications (M.Phil. and PhD) showed stronger awareness and use of EBPs than those with a master’s degree. This suggests that advanced academic training enhances familiarity with research-based instructional practices.

Table 10.

Comparison of qualification

Qualification	Sum of squares	df	Mean square	F	Significant
Between groups	2920.40	2	1460.20	17.09	0.00
Within groups	21,110.28	247	85.47
Total	24,030.68	249

Table 11 shows the results in which significant variation by teaching experience (P < 0.05). Teachers with 6–15 years of experience showed higher engagement with EBPs compared to those with very little (1–5 years) or extensive experience (>15 years). This suggests that mid-level experience is associated with more consistent application of evidence-based mathematics interventions.

Table 11.

Comparison of experience

Area of posting	Sum of squares	df	Mean square	F	Significant
Between groups	3431.02	3	1143.67	13.66	0.00
Within groups	20,599.66	246	83.74
Total	24,030.68	249

FINDINGS

The quantitative analysis of survey data from 250 teachers provided clear insights into the practices, perceptions, and challenges associated with implementing evidence-based mathematics interventions for children with ASD.

First, the data revealed a strong foundational awareness of EBPs among educators. A significant majority of teachers were familiar with the term “EBPs” (M = 4.40) and affirmed their essential role in teaching mathematics to children with ASD (M = 4.46). Furthermore, nearly all respondents had received some form of professional training on these interventions (M = 4.35).

Regarding implementation, teachers reported actively using a range of EBPs in their classrooms. High levels of implementation were recorded for task analysis (M = 4.26), the CRA sequence (M = 4.26), and adapting lessons to Individualized Education Plans (IEPs) (M = 4.32). The integration of technology was also prominent, with video modeling (M = 4.29) and digital manipulatives (M = 4.23) being frequently employed to enhance engagement and skill generalization.

In terms of perceived effectiveness, teachers held strongly positive views. They reported that EBPs significantly enhance learning outcomes (M = 4.31), improve conceptual understanding (M = 4.31), and that technology-based EBPs are more effective than traditional methods (M = 4.38). Peer-assisted strategies were also highly rated for fostering both academic and social skills (M = 4.36).

Despite this strong awareness and commitment, significant barriers impeded consistent application. The most formidable obstacles identified were a lack of training (M = 4.34), time constraints (M = 4.32), and limited resources (M = 4.26). Insufficient institutional and administrative support was also noted as a limiting factor (M = 4.14).

Finally, inferential analyses revealed notable demographic variations. There was no significant difference in EBP implementation based on gender (P = 0.241). However, significant differences were found based on location, age, qualification, and experience. Rural teachers reported higher implementation levels than their urban counterparts (P < 0.05). Teachers with advanced qualifications (M.Phil., PhD) and those with 6–15 years of experience demonstrated significantly stronger engagement with EBPs compared to their less-qualified or less-experienced colleagues (P < 0.05).

DISCUSSION

The findings of this study paint a picture of a teaching workforce that is both knowledgeable and motivated to use EBPs yet operating within a system that presents substantial structural challenges. The high levels of awareness and positive perceptions of effectiveness align with the growing body of literature advocating for structured, visually supported, and individualized instruction for students with ASD. The widespread implementation of strategies like explicit instruction, CRA, and task analysis indicates a successful translation of research recommendations into classroom practice, addressing the core cognitive profiles of many children with ASD who benefit from predictability and clear structure.[34,35]

The enthusiastic adoption of technology, particularly video modeling, underscores a shift towards dynamic, multisensory tools that can provide consistent, repeatable models for learning a key advantage for students with ASD. This suggests that teachers are not only aware of technological tools but are also leveraging them to bridge the gap between abstract mathematical concepts and real-world application.[36]

However, the persistence of significant barriers highlights a critical research-to-practice gap. The identified challenges lack training, time, and resources are consistent with implementation science literature, which identifies these as common drivers of the “know-do” gap in education. The fact that teachers feel underprepared and under-supported, despite recognizing the value of EBPs, points to a systemic failure in providing the necessary implementation of drivers, such as coaching, allocating time for planning, and access to materials.[37,38]

The demographic findings offer nuanced insights into targeted support. The higher engagement among rural teachers, despite typically having fewer resources, may be attributed to smaller class sizes allowing for more individualized instruction or a greater reliance on proven, structured methods in resource-limited settings. The correlation between higher qualifications and EBP use emphasizes the critical role of advanced academic training in deepening pedagogical content knowledge and fostering a research-oriented practice. Similarly, the peak engagement among mid-career teachers suggests a “sweet spot” where educators have moved beyond initial survival stages and possess both the experience and the openness to innovate.[,40,41]

CONCLUSION

This study concludes that while there is a strong and commendable commitment among teachers to implement evidence-based mathematics interventions for children with ASD, this commitment is not yet fully actualized due to systemic barriers. Educators are broadly aware of effective practices, perceive them as highly beneficial, and are actively integrating a variety of strategies from explicit instruction to advanced technology into their teaching. This demonstrates a significant positive stride toward inclusive and effective mathematics education.

However, the potential of these EBPs to transform learning outcomes is being curtailed by a lack of institutional support structures. Without addressing the foundational issues of inadequate training, time constraints, and resource limitations, the consistent and high-fidelity implementation of EBPs will remain elusive. The findings underscore that the challenge is no longer one of teacher willingness or awareness, but one of system-wide support. Therefore, the path to improving mathematics education for children with ASD lies not in discovering new interventions, but in creating the conditions that allow educators to effectively implement the EBPs that already exist.

Recommendations

Based on the findings of this study, the following recommendations are proposed:

1. Allocate resources for sustained, job-embedded professional development focused specifically on EBPs for mathematics instruction for ASD, moving beyond one-time workshops to include coaching and mentoring

2. Integrate EBP guidelines into official curriculum documents and provide teachers with dedicated planning time to adapt lessons and develop individualized materials

3. Ensure schools, particularly those in underserved areas, have adequate funding for instructional materials, assistive technology, and digital tools proven to support students with ASD

4. School administration should actively encourage and recognize teachers’ efforts to implement EBPs, creating a collaborative environment for sharing best practices.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

This research work was funded by Umm Al-Qura University, Saudi Arabia under grant number: 26UQU4340202GSSR04.