Artículo 1

Doctora en Educación, Máster en Educación Especial y Licenciada en Educación Infantil por la Universidad

de Almería.

DOI: https://doi.org/10.61604/dl.v17i31.478

Strategies to Improve the Acquisition

of Logical Thinking in Students with ASD

and ADHD

Estrategias para mejorar la adquisición

del pensamiento lógico en estudiantes

con TEA y TDAH

ISSN: 1996-1642

e-ISSN: 2958-9754

Año 17, N° 31, junio-diciembre 2025 pp. 11-23

Revista de Educación

Universidad Don Bosco - El Salvador

Celia Gallardo Herrerías

Universidad de Almería, España

Correo: cgh188@inlumine.ual.es,

ORCID: https://orcid.org/0000-0001-5515-1269

Recibido: 10 de julio del 2025

Aceptado: 15 de octubre del 2025

Para citar este artículo: Celia, G. (2025). Strategies to improve the acquisition of logical thinking in students

with ASD and ADHD, Diá-logos, (31), 11-23. https://doi.org/10.61604/dl.v17i31.478

Nuestra revista publica bajo la Licencia

Creative Commons: Atribución-No

Comercial-Sin Derivar 4.0 Internacional

Resumen

Este estudio describe cómo las estrategias de

enseñanza basadas en la neuroplasticidad pueden

mejorar el razonamiento lógico-matemático en

estudiantes con Trastorno del Espectro Autista (TEA)

y Trastorno por Déficit de Atención e Hiperactividad

(TDAH). Basado en un diseño de métodos mixtos que

combina una revisión sistemática, una intervención

controlada y una evaluación multimodal, el estudio

reveló una mejora drástica en el rendimiento

académico, el funcionamiento cognitivo y las

conexiones neuronales. Intervenciones como

la gamificación adaptativa, los materiales

manipulativos multisensoriales y las rutinas

metacognitivas indicaron un aumento del 32%

en la capacidad de resolución de problemas en

el grupo experimental (en comparación con el 8%

del grupo control). Los niños con TEA mostraron un

mayor reconocimiento de patrones, mientras que

los niños con TDAH mostraron una mayor atención

y control inhibitorio. Las neuroimágenes indicaron

una mayor actividad de la corteza prefrontal

dorsolateral (CPDL) y una mayor conectividad

con el lóbulo parietal, lo que indica el papel de la

neuroplasticidad en el aprendizaje. Los hallazgos,

que trascienden la educación y la neurociencia,

ofrecen sugerencias prácticas para aulas inclusivas

y exigen la formación docente y la reforma de

políticas para educar a estudiantes neurodiversos.

Palabras clave

Neuroplasticidad, educación matemática, TEA,

TDAH, aprendizaje inclusivo

Abstract

This study outlines how neuroplasticity-based

instructional strategies can enhance logical-

mathematical reasoning in Autism Spectrum

Disorder (ASD) and Attention Deficit Hyperactivity

Disorder (ADHD) students. Based on a mixed-methods

design combining systematic review, controlled

intervention, and multimodal assessment, the

study revealed drastic improvement in academic

performance, cognitive functioning, and neural

connections. Interventions such as adaptive

gamification, multisensory manipulatives, and

metacognitive routines indicated a 32% increase

in problem-solving ability in the experimental group

(compared to 8% in control). Children with ASD

indicated enhanced pattern recognition, and

children with ADHD indicated enhanced attention

and inhibitory control. Neuroimaging indicated

enhanced dorsolateral prefrontal cortex (DLPFC)

activity and enhanced connectivity with the

parietal lobe, indicating the role of neuroplasticity

in learning. The findings cut across education and

neuroscience, offering actionable suggestions for

inclusive classrooms and necessitating teacher

training and policy reform to teach neurodiverse

students.

Keywords

Neuroplasticity, mathematics education, ASD,

ADHD, inclusive learning

Introduction

Neuroplasticity, as the brain's ability to change and reorganize in response to

experience, learning, and neurological damage, is now a fundamental area of study in

contemporary education in general and mathematics education in particular (Núñez,

2024). Due to its very abstract nature and demand for logic, this topic is especially difficult

for individuals with Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity

Disorder (ADHD) (Peñalba et al., 2021). These students have difficulties with elementary

cognitive processes of math learning, such as working memory, sustained attention,

and mind flexibility. However, recent research shows that educational interventions

founded on neuroplasticity can significantly enhance logical thinking development in

these groups (Alonso et al., 2024). Neuroplasticity of the brain—the adaptive power

of the nervous system to rebuild in response to stimuli—is a science foundation to

reorganize instruction in mathematics for students with ASD and ADHD (Conforme &

Morocho, 2022).

Both disorders of neurodevelopment share common cognitive profiles that, as

dynamic impairments rather than static, commit to employing evidence to generate

evidence-based interventions within education. The "math brain," supported by

distributed neural networks across the parietal, prefrontal, and temporal lobes, is

extremely plastic when engaged by means that complement the particular deficit of

each condition while taking advantage of their native strengths (Baquedano, 2024).

In ASD, in which structured thinking and accuracy prevail but openness of mind is the

catch, neuroplasticity may be shaped by approaches that translate cognitive inflexibility

into algorithmic precision (Bastidas et al., 2022).

Strategies to Improve the Acquisition of Logical

Thinking in Students with ASD and ADHD

Neuroimaging studies reveal that incremental repeated variation and ordered

visual arrays activate compensatory neural networks connecting parietal (processing

number) to frontal areas (executive functions), circumventing mathematical abstraction

impairment (Zambrano-Muñoz, 2023). This effect explains why students with ASD who

are taught multisensory methods not only excel in low-level math computation but also

at high-level problem-solving, dispelling the myth that rational-abstract thought is out

of range for this group (Pérez et al., 2023). In the case of ADHD, where inhibitory control

and vigilance are impaired, neuroplasticity facilitates compensation when instructional

methods introduce adaptive gamification and metacognitive control (Sánchez, 2024).

Use of immediate feedback and visual reward to mathematical tasks increases

frontostriatal dopamine release, reinforcing motivation and self-regulation (da Silva et al.,

2024). Electroencephalography measures have shown that interventions bring default

mode network activity patterns to normal, reducing distractibility with mathematical

tasks. Interestingly, ADHD students under these approaches receive a 40% reduction

in impulsivity errors, which shows that accuracy can be learned even while processing

speed challenges persist (García, 2024). The intersection of neuroscience and

education has revealed a collection of principles of instruction that possess cognitive

strength, of which the most impactful is multisensory learning. Multisensory learning

exploits the brain's ability to synthesize information from multiple channels of the

senses—vision, hearing, and touch—to create redundancies in the brain that support

learning and memory. Experiments have indicated that when students are involved

in learning activities that stimulate multiple senses, their brains create stronger links

to access knowledge in the long term. Stimulation of multiple sensory channels not

only makes it stronger for encoding but also increases the efficiency of retrieval so

that learners can retrieve ideas in various contexts. For instance, tactile math learning

through the use of manipulatives has been shown to improve numerical cognition

by developing spatial thinking, while auditory drill in language instruction improves

phonological awareness and reading acquisition. As students learn through multiple

inputs, they develop associative networks that contain knowledge as well as a single

memory trace.

Gamification is another instructional principle that's been misdefined as simply

having learning be "fun." More accurately, neuroscience instructs us that gamification

is a synaptic plasticity amplifier that creates motivation-driven change within the

brain. Through instant feedback, goal-directed challenge, and reward structures,

gamification leverages dopaminergic circuits to engage the prefrontal cortex and

create persistence. The impacts reach beyond behavior reinforcement; evidence

indicates that properly designed gamified environments cumulatively contribute

to quantifiable gains in the density of neural associations in areas associated with

executive functioning and self-regulation. As opposed to relying on extrinsic motivators,

gamification reprograms cognitive structure and converts transitory engagement into

enduring learning behaviors. The transition from extrinsic to intrinsic motivation enables

learners to develop strategic problem-solving and adaptive learning response tactics.

Gamification relies on episodic memory construction—learning from engaging

challenges creates unique mental pictures, strengthening memory through associative

retrieval processes.

The third postulate is metacognition, allowing cortical reorganization by internalizing

systemic strategy to self-directed reasoning. Neuroscientific studies demonstrate that

metacognitive proclivities, such as reflection, error monitoring, and self-regulation,

enhance coupling between dorsolateral prefrontal cortex (DLPFC) and parietal cortices—

planning, attentional control, and abstract thought areas. Cognitive autonomy emerges

– Año 17, N° 31, julio - diciembre 2025

with the development of internalized structures from external support. For example,

early reliance on organizational aid like checklists and facilitated questioning ultimately

gives rise to autonomous application of problem-solving heuristics. Neuroplasticity

allows this to occur by making habitual pathways in executive networks strong enough

so that there is effective cognitive control and minimal cognitive overload. Moreover,

metacognition application extends beyond formal learning, impacting emotional

regulation and resilience. The ability to dissect the process of thinking guarantees

flexibility in unfamiliar situations, whereby the students can learn a means of coping

with complicated situations. The purpose of this paper is to report on the potentiality of

employing neuroplasticity to design more effective mathematics instructional practices

for ASD and ADHD students according to their own unique neurocognitive profiles.

While numerous studies have investigated neuroplasticity in neurological rehab

or learning situations more broadly, very few have directly addressed its application

to mathematics education in students with ASD and ADHD. Moreover, most recent

trends are focused on clinical or therapeutic uses, without regard to their usability in

conventional school settings. This misalignment between neuroscience and education

hinders the development of truly effective pedagogical interventions for these

students, who are too frequently stuck in outdated methods that fail to address their

particular cognitive requirements. This current study aims to bridge the gap between

neuroscientific research and educational practice in the following ways:

• Describe the effectiveness of neuroplasticity-informed teaching practices.

• Discuss some mechanisms of neural adaptation.

Methodology

A mixed-methods explanatory sequential design was adopted in this study, combining

both quantitative and qualitative elements to have a complete picture of the impact

of neuroplasticity-based pedagogical interventions on logical-mathematical thinking

development among students with Autism Spectrum Disorder (ASD) and Attention

Deficit Hyperactivity Disorder (ADHD). This methodological approach allowed not just

the evaluation of observable effects on school performance but also a glimpse into

the neural mechanisms and subjective processes involved in the changes. The study

was designed over the course of one complete school year, with three main phases:

baseline data collection, intervention, and outcome evaluation.

Purposive non-probability sampling was employed in the selection of the sample,

due to the specific clinical and educational characteristics of the target population.

240 participants - 120 with ASD and 120 with ADHD - from eight elementary and high

schools participated. The inclusion criteria were: between 6-16 years of age, clinical

diagnosis made according to DSM-5 criteria, IQ between 70-120, basic reading

skills, and no other severe neurological conditions. Informed consent from parents or

guardians was obtained, along with assent for children.

Participants were matched on the grounds of age, academic grade, and cognitive

profile and formed into two groups of 120 students each: an experimental and a control

group. The experimental group underwent intensive pedagogical intervention founded

on neuroplasticity, while the control group received mathematics instruction through

traditional methods of teaching. Group assignment was for best balance between

groups for individual traits, although complete randomization was not feasible due to

logistical and ethical constraints in a school setting.

Strategies to Improve the Acquisition of Logical

Thinking in Students with ASD and ADHD

The intervention was designed to be implemented over six consecutive months,

comprising five 45-minute sessions per week. The intervention was set within the context

of three pillars: (1) use of multisensory manipulatives, (2) use of adaptive gamification

platforms, and (3) systematic application of metacognitive routines scaled to students’

developmental levels. Each of the strategies was executed based on a standardized

protocol previously piloted in pilot studies.

The multisensory materials included manipulative items such as Cuisenaire rods,

logic blocks, magnetic tangrams, and operation boards. These materials were

selected and adapted to provide stimulation to the visual, tactile, and kinesthetic

channels at the same time, with opportunities for symbolic representation and abstract

thinking through manipulation. It was hoped that this type of multisensory learning

would promote synaptic consolidation and intermodal integration of mathematics

information. Teachers who were previously trained in the neuroscientific foundations of

the intervention led the implementation.

Concurrently, a bespoke digital gamification platform created in collaboration with

neuroeducation engineers was used, which automatically modulated exercise difficulty

based on student performance. The platform embedded immediate feedback loops,

virtual rewards, interactive avatars, and automatic tracking of usage data. Exercises

covered natural numbers, basic operations, patterns, geometry, and problem-solving.

The gamification approach aimed to activate dopaminergic reward mechanisms

involved in sustained attention and intrinsic motivation, with particular emphasis placed

on developing executive functions.

The third condition included personalized metacognitive routines, couched

in the “STOP-THINK-ACT-REVIEW” framework, to facilitate planning, monitoring, and

self-evaluating in mathematical problem-solving. The routines were implemented

through verbal scaffolding, teacher modeling, and self-regulation notebooks, with

the expectation of facilitating gradual internalization of self-reflective thinking. Think-

aloud protocols, reflective pauses, and step-by-step checklists were the other methods

employed.

Intervention effects were assessed on three complementary levels: academic,

neuropsychological, and neurophysiological. Academic assessment involved

standardized mathematics tests adapted to each educational level, administered

pre- and post-intervention and including multiple-choice items, open problems,

and contextualized application problems. Neuropsychological assessment involved

executive function batteries including the Stroop test, numerical working memory

tasks, and set-shifting tasks, supplemented by teacher observation questionnaires and

caregiver behavior scales.

On the neurophysiological level, a representative subsample of 30 students underwent

functional neuroimaging scans (fMRI) and brain activity recordings (EEG), conducted

in collaboration with an applied neuroscience research center. Mathematical content

tasks used for imaging were specifically selected to activate regions that are engaged

in numerical processing and executive functions, that is, the dorsolateral prefrontal

cortex (DLPFC) and inferior parietal lobe.

Quantitative data analysis employed tests of statistical significance (Students’ t-test,

ANOVA, ANCOVA) at 95% confidence level, using specialist software (SPSS and R).

Pearson correlation coefficients were employed to investigate correlations between

– Año 17, N° 31, julio - diciembre 2025

academic performance and brain activation measured. Qualitative data underwent

thematic content analysis of semi-structured interviews, observation notes, and

teacher reflective diaries. Triangulation of varied sources allowed checking for internal

consistency in findings via multiple sources.

Results

The findings of this study irrevocably establish the effectiveness of pedagogical

interventions based on neuroplasticity in strengthening logical-mathematical thinking

among individuals with Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity

Disorder (ADHD). Through the application of a mixed-methods design that includes

quantitative measures like standardized tests, neuropsychological rating scales, and

neuroimaging procedures, and qualitative measures like classroom observations,

teacher interviews, and reflection diaries, it was feasible to not only determine the direct

impact of the intervention but also the cognitive and neurophysiological processes

underlying these changes. The concentration of the data allowed for an integrated

perspective on the way different student profiles respond to structured intervention

according to a neuroeducational bias. At a scholastic level, significant and statistically

adequate gains were evidenced in logical-mathematical skills across diagnostic

groups, albeit with profiles differentiated by pattern.

Of the ASD students, 78% of the experimental group reached competency levels

at their grade levels after the intervention, compared to 45% of the control group,

and the difference was significant (χ² = 6.84, p <.01). This was particularly the case

in problem-solving with pattern recognition, number sequences, and algorithmic

problem-solving. The application of visual aids such as flow diagrams, touch rods

color-coded by category, and logical association cards facilitated the development

from concrete to abstract thinking. The tools were scaffolding that facilitated more

internalization of structured strategies. Classroom observations revealed extensive

development of spontaneous generalization of the strategies to non-mathematical

subjects such as time management and planning daily activities, which was a sign

of deep learning consolidation. On the part of ADHD students, the greatest effects

were found in maintaining attention over time, suppressing automatic response, and

complex problem-solving.

Gamification of content, converting standard instructions into a contest with

successively increasing levels, symbolic reinforcement, and immediate feedback, had

a large effect on cognitive engagement and self-regulation. Following the intervention,

65% of the experimental group ADHD students answered challenging math problems

correctly, as opposed to 30% of the control group, with a highly significant difference

(t(51) = 3.91, p <.001). Impulsivity-based error was also reduced by 40%, especially

on timed mental computation items, as indicated in the Numerical Agility Test results.

This type of error—premature answers before problem analysis conclusion—is a

typical clinical indicator in ADHD, and its reduction reflects true change in inhibition

of behavior. Required reflective interruptions before responding, in addition to visual

indicators noted on critical aspects of the problem statement, were mentioned by

teachers as most effective features in effecting this impact. From the basic cognitive

function view, important growth was noted in inhibitory control, working memory, and

cognitive flexibility.

Neuropsychological assessment by the WISC-V subtests indicated an average 1.5

standard point growth on the working memory items, i.e., reverse numerical span,

quantified in more ability to follow complex directions and hold applicable information

Strategies to Improve the Acquisition of Logical

Thinking in Students with ASD and ADHD

in working memory when completing tasks. These benefits were more profound when

supports incorporated visual aids with personalized narrative features, e.g., illustrated

cards with well-known video game figures representing mathematical algorithms. This

motivational-engaging intrinsic design was core to skill transfer. In terms of cognitive

flexibility—historically impaired in both disorders—the results showed a differential

pattern: ASD students reduced by 25% response time for alternation between arithmetic

operations, while ADHD students reduced perseverative errors by 30%. Metacognitive

strategies, such as the employment of self-instructions (“first I identify, then I solve”), were

the most important factor in improving this ability. Notably, some of the ASD students

began to use these self-verbalizations in social contexts in an attempt to manage

conflict or transition, thus providing intriguing opportunities for the study of cross-domain

transfer.

Functional magnetic resonance imaging (fMRI) and electroencephalographic

(EEG) measures provided strong evidence that the intervention supported improvement

in the efficacy and integration of the involved neural networks for mathematical

reasoning. fMRI scans indicated a substantial enhancement of activation in the

left dorsolateral prefrontal cortex, particularly for logical reasoning, and enhanced

functional connectivity with the inferior parietal lobe. These shifts were most evident in the

highest-achieving students, with 15-18% mean increases in BOLD signal in these brain

regions. EEG metrics also reflected increased theta coherence between frontoparietal

regions, a sign of effective cognitive integration. The increase was most pronounced in

gamification sessions, which suggests that motivational processes not only facilitated

commitment to behavior but directly energized functional reorganization in the brain.

Students with the greatest increase in theta coherence were also those for whom the

most significant attitude change toward mathematics, from frustration or avoidance to

persistent engagement, was documented by teachers.

Examination of the moderating variables showed that individual variables made

the most significant contribution toward intervention effectiveness. For ASD individuals,

receptive language level was the most predictive factor: those who were scoring in

the 60th percentile range and above on the CELF-5 test were better placed to benefit

from conceptual metaphor and narrative structured assistance. For less advanced

language difficulties among learners, more visual and manipulative strategies of support

proved to be more effective. In the case of ADHD learners, symptom profile—either

inattentive or hyperactive—governed the effectiveness of intervention. Participants

with prevalent inattentiveness responded more to visual organizers, schematics, and

timers, and participants with extreme hyperactivity responded more to controlled

movement interventions and kinesthetic feedback. A second important moderator was

age: 6- to 10-year-olds made rapid progress with intensive multisensory materials, but

these needed to be constantly reinforced if they were to remain effective. In contrast,

younger learners aged 11 to 16 years exhibited more incremental but longer-term

progress, especially where approaches capitalized on their developing ability for self-

awareness and abstract thinking. These findings not only attest to the effectiveness of

approaches based on neuroplasticity but also to highlight the significance of careful

individualization to each learner’s neurocognitive and developmental blueprint.

Qualitative insights into learning transformation

Qualitative information derived from teacher interviews, classroom observations, and

student focus groups further enriched our understanding of deeper processes that led

to change in performance and attitude towards mathematics learning. These sources

opened up access to analysis levels that would have been impossible with quantitative

– Año 17, N° 31, julio - diciembre 2025

measurement and gave a more accurate representation of the subjective, relational,

and affective changes following the intervention process.

Experienced teachers, who were accustomed to the typical resistance of students

with ASD and ADHD to structured and abstract activities, began noticing differences

in behavior patterns. Avoidance behaviors—most often voiced as distraction, passive

resistance, complaining, or escape behaviors—were increasingly offset by distracting

and persistence in the face of obstacles. As one third-grade teacher put it: “Before,

when I’d give them an activity with numbers, some wouldn’t even look at it.” They now

approach and ask if they may do it ‘their way,’ as if they think they have a way to try. This

sense of agency—having their own way based on their abilities—was remarked on by

numerous educators as one of the most striking changes. Ethnographic observations

of class sessions revealed that affective interaction with content influenced cognitive

engagement directly.

When problems in mathematics were embedded in compelling stories or associated

with students’ unique interests—video games, sports, pets, or fantasy quests—

engagement persisted for longer periods of time, autonomous initiative in working

on problems with less overt outside help was greater, and random metacognitive

verbalizations were heightened. These remarks, which had been inscribed with a coding

scheme based on Zimmerman’s (2000) self-regulation phases, also demonstrated a

sea change—from utterances like “this is hard” or “I don’t understand” to utterances

like “I’ll do it like this,” “I have done something like that before,” or “if I do it first, then I

think that will work.” This shift in students’ self-talk is humongously informative, expressing

not just greater comprehension but even a change towards more positive self-view as

learners. These opinions were repeated by student focus groups in candid and open

voices.

Certain students gave brief descriptions of their experiences of pedagogical

methods leading to episodes of immediate understanding, which could be described

as colloquially “it clicked in my head” or “the light bulb went on.” A student with ADHD

remarked: “When they did steps as a recipe for cooking, it assisted me in following

everything without omitting important points. I did it as a game, as if I had to complete

a mission step by step.” An additional ASD student commented: “When we utilized

textured cards, like rubber or with images, they assisted me in remembering how each

number functioned, as if each one had a personality.” These descriptions proved

invaluable in the process of identification of affective, sensory, and symbolic variables

not initially included in the intervention design but crucial in learning internalization.

The category was not restricted to the innate capacity to solve problems but

encompassed the inner perception of personal effectiveness in managing hard tasks.

Observations indicated that as students saw that their efforts translated into achievement,

even small steps, their willingness to take on harder tasks was considerably enhanced.

This impact was strongest in students who had an academic history of failure or low

math self-efficacy. The sense of “being able to do what before seemed impossible”

was a watershed in their school career, according to several teacher accounts.

Perception of autonomy was the second prevailing category. Students reported—

both in interviews and in written or oral reflection—that, for the first time, they were able

to “choose how to learn,” “solve in their own way,” or “decide where to start.” Perception

of control over the learning process—even if delineated by the teacher in terms of

pre-determined options—was central to creating a less dependent and more active

state of mind. Teachers reported that, after some weeks of intervention, some children

Strategies to Improve the Acquisition of Logical

Thinking in Students with ASD and ADHD

began to invent their own problems, to modify proposed rules of mathematical games

presented to them, or to integrate strategies in the absence of external instruction.

This suggests, not merely content knowledge, but take-over—a kind of mental

empowerment not always induced through more traditional, hierarchical methods.

Moreover, attitude changes of a kind larger than mathematics education were

typically observed. In most cases, teachers reported that students who previously had

avoided participation in group work started taking central roles in mathematics tasks.

In a few cases, they even taught strategies to other students through metaphors or

diagrams. Not only did this reinforce the students’ own learning, but also helped to

create more positive and inclusive classroom environments. The socioconstructivist

explanation for such phenomena is that the interventions changed not only individual

competence but also relational and cultural classroom practices—a crucial factor in

environments where neurodiversity has been historically marginalized or medicalized.

Another theme to arise from teacher interviews was the impact of emotional support

within mathematical activity. Instructors who had once envisioned their task as merely

“teaching content” began to see the benefit of creating emotionally safe classrooms

where mistakes were not criticized but reframed as an inevitable aspect of the learning

process. Here, “normalization of error” (putting normal errors on the table in problem-

solving discussions or making teachers’ own errors explicit) and “emotionally contingent

feedback” (providing sincere praise for effort, not for correct answers) were observed to

be important drivers of change. A high school teacher recounted: “When I explained to

them that I had also gotten a problem wrong, it was as if a wall came down. They took

more risks. And afterward, they did it better.” Far from trivializing the process of teaching,

this kind of interaction enriches it by building trust on both sides.

It is worth mentioning that these qualitative findings are not mere subjective

impressions but are corroborated through systematic triangulation with quantitative

findings. For instance, students who reported more competence and autonomy were

also the ones who reported the highest gains on standardized measures of working

memory, problem-solving capacity, and math accuracy. This synthesis of qualitative

and quantitative information highlights the internal validity of findings and supports a

more ecological and holistic contextual understanding of learning.

The second critical factor was the role teacher-student relationships played in the

success of the intervention. Those instructors who established a relationship of trust—

founded upon respect for the students’ individuality, recognition of their thought style,

and active listening—were the instructors whose students showed the greatest growth.

Several interviews identified the instructor as a “cognitive translator,” one who could read

the idiosyncratic thinking of a student and reformulate material in a structure that would

intersect with their internal logic. This labor-intensive, gentle, and professionally skilled

work was greatly appreciated by the families, who saw not only academic growth but

also emotional development in their children.

Lastly, this qualitative approach also permitted the possible determination of

challenges and tensions that need to be taken into account in future implementations.

Some instructors described difficulty in sustaining the intervention in environments with

overwhelming institutional pressures, few resources, or demand for compliance with

standardized curriculum demands. Others described a need for additional training

in neuroeducational interventions, particularly in developing visual support, sensory

modifications, and emotion regulation strategies. These testimonies emphasize that,

though the intervention has been extremely successful, its scalability and sustainability

– Año 17, N° 31, julio - diciembre 2025

most critically depend on acknowledgment of teaching as intellectual and complex

practice, coupled with professional support and institutional environment.

Discussion

The findings of this present study are overall consistent with the prior work on

neuroplasticity and mathematics education but further provide notable subtleties and

new insights deserving of much discussion.

Prior work, as that of Meltzoff & Kuhl (2016), had previously demonstrated that

repeated systematic practice and imitation were capable of enhancing neural

networks in ASD children, specifically in sequencing and recognizing patterns. Our results

align with this premise, insofar as activities with physical manipulatives and gamification

that featured some incremental repetition produced breathtaking improvements on

structured problem-solving. The current study diverged from previous research, however,

in demonstrating that such improvements are not simply procedure skill specific but

that they generalize to the higher-order abstract thinking skills, which operate like Baron-

Cohen (2017) had suggested were more difficult for this group.

One of the results most directly relevant to the current study was increased functional

connectivity between inferior parietal lobe and dorsolateral prefrontal cortex in ASD

students that signaled higher integration of logical reasoning and numerical calculation.

This contrasts with studies such as Butterworth (2018), where persistent numerical

cognition impairments were reported in ASD patients. One possible explanation is

that multisensory intervention employed in this study engaged compensatory neural

networks to substitute typically associated impairments.

As is in line with Barkley (2019), our findings are in agreement with the fact that ADHD

students show immense improvement in math tasks if pedagogical interventions have

components modulating attention and lowering impulsivity. Adaptive gamification,

through its real-time feedback and dependent reward structures, reproduced

effects identical to those identified by Diamond (2013) in executive function training

interventions. But this study provides additional validation in the sense that it shows these

benefits are not only maintained in real-world learning settings but also are associated

with quantifiable changes in neurophysiology, such as normalization of DMN function.

One of the points of departure from previous studies, e.g., Dehaene (2020), is that

while previous studies emphasized processing speed as an important factor in math

learning among ADHD, the current findings emphasize that accuracy and inhibitory

control can also be equally important. For example, the 40% reduction in errors caused

by impulsivity on timed tests illustrates that metacognitive strategies (e.g., reflective

pauses, self-verbalization) can overcome speed problems, an area not well covered

in the literature.

These findings support Merzenich et al. (2014) forecast for the brain’s plasticity following

multisensory stimulation, but they have a more generalizability application in that they

demonstrate that these results occur outside clinical/rehabilitation environments. Unlike

research that tested these approaches in labs with small samples (e.g., clinical trials

employing neurofeedback), our intervention was utilized within normal classroom

environments, thereby establishing its validity in normal classroom settings.

Strategies to Improve the Acquisition of Logical

Thinking in Students with ASD and ADHD

Second, while earlier studies like Dehaene (2020) pointed out the part of spaced

repetition in the consolidation of learning, our study shows that if this strategy is coupled

with ludic factors (gamification) it maximizes even more the long-term memory. This

implies that intrinsic motivation is a driving force for neuroplasticity, something that has

been less investigated in ASD and ADHD populations.

Conclusions

The research represents an important milestone in uncovering how the principles

of neuroplasticity can be rigorously used to improve mathematics learning in children

with Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD).

The findings ratify earlier results on the adaptive ability of the brain in neurodivergent

disorders and providing strong empirical evidence on the specific processes in which

scientifically engineered pedagogical procedures can optimize the development of

logical-mathematical thinking. During the course of this research, it was established

that a blend of multisensory modalities, adaptive gamification, and metacognitive

procedures, along with optimizing learning and performance, is accountable for

changes of networks that take on function and structure-related roles involved in

calculating and abstracting.

This observation is in agreement with some of the previous basic studies’ conclusions

regarding this field of neuroscience. But this study does one better than that in

demonstrating that such advantage is not restricted to lower-order abilities but translated

to higher-order ones such as dynamic problem-solving and generalization of principles.

This would mean that ASD neuroplasticity can be accessed in a more integrated way

than has been achieved to date, given pedagogic interventions are made suitably

adaptive in a way that is appropriate to cater to differential needs.

The evidence for the intervention efficacy of approaches such as gamification

and metacognitive breaks to reduce impulsivity and improve sustained attention to

demonstrate that these interventions not only fix behavioral deficits but enable stable

neurofunctional adaptations. One of the most applied discoveries was the normalization

of activity in the default mode network (DMN) which indicates increased ability to control

attention even under states of distraction. This contradicts earlier studies that primarily

stated the importance of speed of processing and speculated that accuracy and

inhibitory control might also be equally important to academic performance in this

sample.

Most importantly, perhaps, is the evidence that neuroplasticity-informed methods

can be applied in everyday classrooms without the necessity of separate clinical or

technological environments. This is crucial to bridging the gap between teaching and

neuroscience research because it provides teachers with easy and scalable fixes.

The research also provides direct evidence of the neural foundations of such

gains—a topic seldom broached in earlier research. Neuroimaging research indicated

not just that pedagogical intervention caused brain regions accountable for working

with numbers (e.g., inferior parietal lobe) but also engaged functional integration of

these brain regions with the dorsolateral prefrontal cortex (DLPFC) executive processes

accountable for. Results demonstrate a process of neural compensation wherein

external strategies (e.g., visual support, prompt feedback) become increasingly more

internalized such that the learner can eventually become more independent with

metacognitive abilities.

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Yet another innovative aspect is the determination of moderating variables that

influence the effectiveness of the intervention. For instance, ASD children with increased

prior verbal skills were helped by activities involving mathematical language, whereas

ADHD children with high levels of hyperactivity were more favorably influenced by

kinesthetic approaches. This suggests the need for adapting teaching strategies based

on characteristics rather than applying the same strategy to all students bearing the

same diagnosis.

The implications of this research for inclusive education are extensive. To begin,

they offer an evidence-based framework for curriculum development and instructional

materials responsive to the neurocognitive needs of ASD and ADHD students. For

example, adaptive gamification might be systematically incorporated into math

curricula—not an aside but as a fundamental strategy for keeping learners on course

and frustration-free. Similarly, usage of multisensory manipulatives should never be

limited to early years because they were shown to be beneficial even for teens in

bridging the gap towards higher-order thought.

Secondly, the study brings to the forefront the requirement for teachers to undergo

neuroeducation training. Teachers not just need to know these methods, but also their

neuroscientific foundation so that they can innovate and apply them across a range of

situations. This requires more cross-disciplinary engagements between neuroscientists,

teachers, and educators, and embedding these matters within initial training sessions

and continuing professional development.

Policy-wise, the study suggests that neuroplasticity-informed interventions can be

incorporated into school systems. Allocation for budget provision to special teaching

devices is provided, manufacturing of standard protocols for neurocognitive assessment

within school classrooms, and design of online platforms to facilitate roll-out of gamified

procedures. The study is also in support of policies for actual inclusion, as opposed to

segregating neurodivergent students into specialist rooms since the interventions were

conducted within regular classrooms.

While this study is contributing notably, it also has limitations which can be resolved in

future work. First, even with rigid methodological design, the inability to fully randomize

groups potentially introduced selection biases. Future studies have the advantage of

using pure experimental designs for maximum internal validity.

Second, follow-up was limited to a relatively short period (6–12 months). It would

be informative to see whether improvements noted are maintained in the long term

and whether the changes noted in the brain are paralleled by long-term academic

function. This would require longitudinal studies with more than one time point.

Finally, this study dealt with ASD and ADHD, but whether one uses the same

techniques with other disorders—such as dyscalculia or nonverbal learning disorder—

would be relevant. Since these disorders share some of the same cognitive deficits as

ASD and ADHD (e.g., working memory or visuospatial processing), it could be the case

that neuroplasticity-based interventions would benefit these students as well.

Strategies to Improve the Acquisition of Logical

Thinking in Students with ASD and ADHD

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