Geometry is a very important field of mathematics which is crucial for the understanding of space. From an early age, children observe objects that cor-respond to geometric shapes and learn the position they occupy in space (above, below, etc.). It is a demanding lesson that requires imagination and combinational thought. With the introduction of technology in education, ge-ometry became more accessible to students, because through it pupils can now visualize figures, study and process them.

This study explored innovative methods for teaching mathematics to seventh-grade students with persistently low performance by using an AI-driven neural network approach, specifically focusing on solving first-degree inequalities. Guided by the Response to Intervention (RTI) framework, the intervention aimed to reduce math anxiety and build academic resilience through the development of cognitive and metacognitive strategies. A rigorous pre- and post-test design was employed to evaluate changes in performance, anxiety levels, and resilience. Fifty-six students participated in the 12-week program, receiving personalized instruction tailored to their individual needs. The AI tool provided real-time feedback and adaptive problem-solving tasks, ensuring students worked at an appropriate level of challenge. Results indicated a marked decrease in math anxiety alongside significant gains in cognitive skills such as problem-solving and numerical reasoning. Students also demonstrated enhanced metacognitive abilities, including self-monitoring and goal setting. These improvements translated into higher academic performance, particularly in the area of inequalities, and greater resilience, highlighting the effectiveness of AI-based strategies in supporting learners who struggle persistently in mathematics. Overall, the findings underscore how AI-driven teaching approaches can address both the cognitive and emotional dimensions of mathematics learning. By offering targeted, adaptive support, educators can foster a learning environment that reduces stress, promotes engagement, and facilitates long-term academic success for students with persistently low performance in mathematics.

The difficulty faced by students in Geometry (ageometria) is a relatively new learning difficulty that has not been extensively explored. Early detection, as well as intervention, is very important. Students with dyslexia, like all students with special learning difficulties, face difficulties in working memory. In addition, solving a geometric problem requires comprehension of pronunciation (in which students with dyslexia lag) and numerical processing (in which students with dyscalculia lag). For this reason, this article presents interventions aimed at improving working memory or improving reading or numerical skills, with the help of new technologies.

The purpose of this paper is to present researches on how to teach students Geometry through ICTs methods from 2014 to 2019. The articles were searched through Google Scholar. At first, the focus of the article is on the teaching of geometry with software available on the Internet for PCs. Sec-ondly, educational games for geometry are presented that a student can in-stall on any device, such as a smartphone or tablet and are available to the user at any time. Almost all of the described researches have tested the ef-fectiveness of ICTs teaching methods for geometry in relation to classical teaching methods such as paper-and-pencil. Based on findings, the teaching of geometry with ICTs had better educational results than the paper-and-pencil method of teaching.

Students with learning disabilities often experience a complex range of internal and external challenges that can significantly impact their overall well-being and development. Internally, these students may grapple with intense feelings of anxiety, depression, and physical complaints, which can lead to social withdrawal and diminished self-esteem. They may also face higher rates of bullying and social rejection, further exacerbating their psychosocial difficulties and negatively affecting their sense of belonging and acceptance. These learners are more likely to exhibit attention problems, poor concentration, and a wide range of emotional difficulties, which can further hinder their ability to engage effectively in academic and social settings. Behaviorally, students with learning disabilities may exhibit issues like attention deficits and socialisation challenges, stemming from underlying processing difficulties and challenges in understanding social cues and norms. They may also experience feelings of anger, frustration, and even aggressive behaviours, often as a result of their negative experiences and struggles with academic demands. Emerging research suggests that executive function deficits can contribute to these students' complex relationship between temperament and psychological difficulties. Problems with executive functions, such as attention, planning, memory, and flexibility, can significantly impact their cognitive and social-emotional development. Early interventions, such as video games, mobile apps, or STEM-oriented approaches, are crucial for addressing these multifaceted challenges and supporting the holistic growth and well-being of students with learning disabilities

Brain–Computer Interfaces (BCIs) have increasingly been explored as tools for monitoring and modulating cognitive processes relevant to learning. However, their application to learning disorders, and especially to mathematical learning difficulties such as dyscalculia and ageometria, remains conceptually promising but empirically underdeveloped. The present study offers a scoping review with structured narrative synthesis of recent empirical research on BCI-based interventions in learning disorder populations, with particular attention paid to their possible translational relevance for mathematical learning. Following PRISMA-ScR principles and a Population–Concept–Context framework, studies published between 2020 and 2025 were identified through database searches in Scopus, IEEE Xplore, and PubMed. A total of 30 studies met the inclusion criteria. All eligible studies focused on Attention-Deficit/Hyperactivity Disorder (ADHD), while no eligible BCI intervention studies were found for dyscalculia or ageometria. The reviewed literature was dominated by EEG-based neurofeedback interventions. To move beyond descriptive summary, the included studies were organized using a structured analytical framework based on intervention modality, primary cognitive target, methodological robustness, and translational proximity to mathematical learning disorders. Across the evidence base, the most consistent findings concerned attention regulation and executive function outcomes, whereas academic and mathematics-related outcomes were sparse and methodologically less developed. Although several studies suggested improvements in domain-general cognitive mechanisms relevant to mathematical learning, the absence of direct evidence in dyscalculia and ageometria prevents confirmatory conclusions. The review therefore identifies both the promise and the limits of current BCI applications in learning disorder contexts and argues that future research should prioritize theory-driven, disorder-specific trials targeting numeracy, visuospatial reasoning, and executive processes in mathematical learning disabilities. Although current findings suggest promising cognitive and educational potential, these technologies are not yet ready for routine implementation in standard classroom environments without further validation, teacher training, ethical safeguards, and cost-effective deployment models.