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.

This research investigates the impact of digital math serious educational games (SEGs) on enhancing math skills and motivation, specifically focusing on first-degree equations for students with learning difficulties. A comparative study was conducted among two groups of students with learning disabilities. One group engaged with the digital math serious educational game “Battleship”, while the other received traditional curriculum-based instruction. The study’s dual objectives were to assess the effectiveness of digital math SEGs in improving mathematical performance and to evaluate motivation levels. Additionally, gender differences in performance and motivation were examined to understand how SEGs impact boys and girls differently. Employing an empirical approach, a test comprising standard exercises on first-degree equations, typically encountered in seventh grade, was administered. The Motivated Strategies for Learning Questionnaire (MSLQ) was administered to measure motivation. The research sample consisted of 104 seventh-grade students with learning disabilities, aged 12–13 years, from four public schools in the northern sector of Attica, Greece. The sample was evenly divided into two groups of 52 students each. Data were analyzed using SPSS and Excel. Results indicated that students who engaged with the digital math SEG demonstrated significantly improved math performance compared to their peers who used the standard curriculum book. Interestingly, the control group, which used the standard curriculum book, reported higher levels of motivation, underscoring the complex interplay of motivational factors among students with learning disabilities. Furthermore, the analysis by gender revealed that both boys and girls benefited from SEGs in terms of performance. However, motivation levels were only slightly affected by gender, highlighting the potential of SEGs to support diverse learners.

This study examines the impact of an integrated teaching approach, combining ChatGPT and traditional methods, on geometric understanding in third-grade students (ages 9-10). Grounded in Piaget’s and Van Hiele’s theories, the research involved 436 students from Attica, Greece, divided into an experimental group and a control group, 218 students each. Performance assessments focused on symmetry and plane shapes, alongside evaluations of Anxiety Levels, Learning Styles, Cognitive Styles, and Executive Functions. Results indicate that the experimental group outperformed the control group in geometric reasoning, demonstrating improved understanding and application of geometric properties. Correlations between anxiety levels and cognitive styles suggest that tailored teaching strategies enhance engagement and comprehension. Statistical analyses confirmed the effectiveness of the integrated teaching method, highlighting its meaningful impact on students’ learning outcomes. This study contributes to the literature on effective pedagogical strategies for young learners, emphasizing the importance of aligning teaching methods with cognitive development. The findings suggest that integrating technology into education can promote deeper learning in geometry, with implications for future instructional practices in mathematics education.

This study examines the impact of digital tools on fraction comprehension among 5th-grade students with learning difficulties in mathematics. It assesses the effectiveness of three teaching methods: educational software, video tutorials, and their combination. The research involved 252 students from 8 state-funded elementary schools, employing a quantitative experimental design with pre- and post-test assessments. Grounded in Constructivist Learning Theory and Technological Pedagogical Content Knowledge (TPACK), this research explored how technology can enhance mathematical understanding. Results indicated that the combined method achieved the highest improvement (58%, p < .001, Cohen’s d = 3.03), significantly outperforming educational software alone (33%, p = .015, Cohen’s d = 2.52) and video tutorials alone (7%, p = .987, Cohen’s d = 0.14). These findings highlight the substantial benefits of integrating diverse digital tools to effectively support mathematics learning among students facing additional educational challenges.

Inclusive AI-mediated mathematics education for students with learning difficulties refers to a human-centered approach to mathematics teaching and learning that uses artificial intelligence (AI), adaptive technologies, and data-rich environments to support learners who experience persistent challenges in mathematics. These challenges may take the form of a formally identified developmental learning disorder with impairment in mathematics, broader learning difficulties, low and unstable achievement, irregular engagement, or heightened mathematics anxiety that places students at risk of disengagement and poor long-term outcomes. This approach integrates early screening, personalized instruction, and affect-aware support to address both cognitive difficulties and the emotional burden associated with mathematics anxiety. Situated within digitally augmented schools, homes, and community spaces typical of smart cities, it seeks to reduce stress and anxiety, prevent the reproduction of educational inequalities, and promote equitable participation in science, technology, engineering, and mathematics (STEM) pathways. It emphasizes Universal Design for Learning (UDL), ethical and transparent use of learner data, and sustained collaboration among teachers, families, technologists, urban planners, and policy-makers across micro (individual), meso (school and community), and macro (urban and policy) levels. Crucially, AI functions as decision support rather than replacement of pedagogical judgment, with teachers maintaining human-in-the-loop oversight and responsibility for inclusive instructional decisions. Where learner data include fine-grained logs or affect-related indicators, data minimization, clear purpose limitation, and child- and family-friendly transparency are essential. Implementation should also consider feasibility and sustainability, including staff capacity and resource constraints, so that inclusive benefits do not depend on high-cost infrastructures.

Understanding decimal place value is a key challenge for students with Learning Difficulties (LD) in mathematics. This study explores the impact of AI-powered ChatGPT, on enhancing learning during the COVID-19 pandemic. Fifty-four sixth-grade students with learning difficulties from six Greek elementary schools engaged with the interactive platforms Khan Academy and DreamBox, with personalized support from ChatGPT. Results revealed significant improvements in decimal place value comprehension post-intervention. Additionally, this research investigated how AI-powered adaptive platforms enhance the effectiveness of micro-credentials in certifying student achievements and upskilling mathematics teachers. The study highlights the potential of micro-credentials to improve pedagogy in technology-driven learning environments. By integrating AI tools and micro-credentials, this study offers insights into how educators can better support students with LD and the importance of micro-credentials in validating learning progress and advancing teachers' skills in the digital age.