Search Results (259)

Fluid intelligence and need for cognition are relevant predictors of school grades and might also interact in the prediction of grades. We examined the independent predictive values of fluid intelligence and need for cognition as well as their interaction for math and German grades and changes therein in a sample of 565 German primary school children (298 girls, 261 boys, 6 with no gender specified; M_age = 8.40, SD = 0.59). Parental education was considered a control variable. Cross-sectional analyses showed that both intelligence and need for cognition were uniquely related to grades. However, in the latent change score analyses, fluid intelligence, but not need for cognition, was related to change in math grades, but not in German grades, and only when parental education was not considered as a control variable. We found no interaction effects between fluid intelligence and need for cognition. The findings imply that the need for cognition might not play a comparably relevant role for school grades in primary school as it has been shown in previous studies focusing on secondary or tertiary education. Full article

Students with special needs often require more assistance and attention to meet their educational needs. However, schools frequently grapple with a critical shortage of special education teachers and support staff. This shortage of special education teachers can result in limited resources for general and subject teachers (e.g., math, science), making it challenging to provide individualized support to students with special needs. Specifically, subject teachers may struggle to design effective curricular content modifications and accommodations for such students without the guidance and suggestions of special education teachers. Artificial Intelligence (AI) technologies can provide some support for teachers and schools in meeting the needs of students with special needs. Also, AI may help reduce teachers’ workload. In this technology review, we assess the capabilities of Magic School AI (MSAI) in providing accommodations and modifications to assist teachers in streamlining their workload and fostering inclusivity in their classrooms. We examined five functions: text leveler, text scaffolders, assignment scaffolder, exemplar and non-examples, and sentence starters. Additionally, we discuss the limitations of MSAI and conclude by suggesting potential improvements for the system. Full article

This study compares the views of mathematics teachers in private and public schools on mathematics education during the COVID-19 pandemic from their perspectives after the pandemic, focusing on factors influencing secondary and high school mathematics education. In this study, the survey method was used to collect data. The survey method was employed to obtain information for this investigation. During the 2023–2024 school year, 644 math teachers took part in the study. Of these, 260 were from private schools, and 384 were from public schools. There are 10,323 teachers in public schools and 694 in private schools, and this sample size is more than the 371 participants that are needed for statistical purposes (based on Cochran’s formula at a 95% confidence level and a 5% margin of error). A scale consisting of thirteen 5-point Likert-type questions was developed by researchers for data collection, and mathematical modeling techniques were employed. Factor analysis using SPSS 24.00 revealed four key factors influencing teachers’ responses: teachers’ professional development and support, job satisfaction, students’ engagement, and teaching experience. The results highlight significant disparities between public and private schools in mathematics education, attributed to various factors to be elucidated further in the subsequent discussion. Full article

Math learning is a key educational goal, and one marked by substantial individual differences even in the earliest grades. Although considerable research has examined the extent to which domain-general processes, such as executive functions and fluid intelligence, contribute to this variability, there is a notable gap in understanding how they may interact to predict early math learning. In particular, prior work had not examined potential moderating effects whereby the relation between executive functions and math outcomes depends on a child’s fluid intelligence, and vice versa. The current study addressed this gap by examining the math skills in Russian first-graders (N = 160) as a function of fluid intelligence (measured with Raven’s matrices) and various components of executive functions. Consistent with prior research, the results revealed the main effects of Raven’s scores, verbal working memory, and the control component of executive function (a composite of inhibition and cognitive flexibility scores) on math growth. Importantly, extending previous research, the study found that both memory and control components of executive function interacted with fluid intelligence. Specifically, executive function had a stronger positive effect on math learning for children with lower levels of fluid intelligence. The implications for intervention research and educational practice are discussed. Full article

In response to systemic inequities in mathematics education, we developed and evaluated a five-year, multi-phase curriculum model to cultivate effective secondary mathematics teacher leaders. Supported by NSF Noyce Master Teacher Fellowships, the APLUS in MATH (APLUS in Math: Alabama Practitioner Leaders for Underserved Schools in Mathematics) program engaged 22 inservice teachers through graduate coursework, National Board Certification preparation, and leadership project development. Using a mixed-methods design, we analyzed data from classroom observations (MCOP²), National Board Certification assessments, course performance ratings, and teacher leadership project proposals. Results indicate significant improvements in instructional practices, content knowledge, and leadership readiness. Findings underscore the importance for sustained, structured professional development to prepare teachers as instructional experts and change agents in high-need educational contexts. Full article

Understanding how students’ online homework behaviors relate to their academic success is increasingly important, especially in elementary education where such research is still emerging. In this study, we examined three years of online homework data from fourth-grade students enrolled in an after-school math program. Our goal was to see whether certain behaviors—like how soon students started their homework, how many times they tried to solve problems, or whether they uploaded their written work—could help explain differences in homework completion and test performance. We used multiple regression analyses and found that some habits, such as beginning homework soon after class and regularly attending lessons, were consistently linked to better homework scores across all curriculum levels. Test performance, however, was harder to predict and showed fewer consistent patterns. These findings suggest that teaching and encouraging specific online study behaviors may help support younger students’ academic growth in digital learning environments. Full article

In 2019, the TIMSS study offered a closer look at how Moroccan eighth-grade students were doing in mathematics. The data came from a sample of 8390 students; 37% performed well, while the remaining 63% struggled. The goal was to better understand which contextual factors truly influence academic success. The dataset was dense, with over 700 variables drawn from students, teachers, and school questionnaires. To make sense of it, advanced machine learning techniques were applied, including an autoencoder to reduce dimensionality. This process helped narrow things down to 20 key variables that strongly correlated with student performance. These factors covered a range of influences, from teaching strategies and student engagement to teacher training and school-level resources. The insights from the study offer practical guidance for educators and policymakers looking to design targeted, effective interventions. At its core, the study underscores a familiar truth: success in math does not hinge on a single element but on a web of interconnected conditions. Improving outcomes requires a holistic approach, one that supports both learners and the people guiding them. Full article

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. Full article

Solving many of the pressing issues facing the world today will require a deep and integrated understanding of science, technology, engineering, and mathematics (STEM). To prepare today’s K-12 students to tackle these challenges, STEM education must create opportunities to learn disciplinary content while inventing actionable solutions to messy, interdisciplinary problems. Learning frameworks, such as Project-Based Learning (PBL), Design-Based Learning (DBL), and Entrepreneurial-Based Learning (EBL), could support this reconceptualization of STEM education. New approaches are needed that leverage and integrate what works from these frameworks to better prepare students for success post-schooling. This means leveraging frameworks that emphasize practices and ways of thinking that support students to build and justify solutions that create value for users, while also creating a need for disciplinary content knowledge. This is especially necessary for mathematics, a discipline that is often treated insufficiently in interdisciplinary STEM activities. This paper introduces the Design & Pitch (D&P) Challenges in STEM Learning Framework, a novel learning framework that leverages features of PBL, DBL, and EBL, situating math learning within entrepreneurial pitch competitions. It describes the D&P Learning Framework and explores how each contributing learning framework combines to enhance students’ work, focusing their mathematical reasoning, while also empowering them to invent relevant solutions to authentic problems. Full article

Background: Educational neuroscience has made important contributions to show how the COVID-19 pandemic impacted schooling. In countries like Brazil, with significant educational inequality, the suspension of in-person classes worsened these disparities, as low-income families faced difficulties accessing remote learning. Methods: This study evaluated executive functions (EF) and academic skills in reading, writing, and maths for 178 public school students from the first to ninth grades in São Paulo, Brazil, comparing them with pre-pandemic norms to assess possible differences. EF were assessed using the Hayling Test, Digit Span Task, and Verbal Fluency, while academic skills were measured by the School Performance Test II. To analyse differences between the sample of this study and the pre-pandemic normative samples, one-sample t-tests were performed. Due to the small sample size, segmented by school grade and age, the bootstrapping resampling method was used, and the effect size was measured with Cohen’s d. Results: A one-sample t-test showed significant differences between times, with lower post-pandemic performance in verbal fluency (9–14 years old), working memory (10–14 years old), and inhibitory control across all age groups. Writing skills were lower from the fifth to eighth grades and reading from the fourth to eight grades. Maths skills were lower in the fourth, eighth, and ninth grades. Better post-pandemic performance was seen in working memory (6 and 7 years old). Conclusions: Students in the upper grades of elementary school during the pandemic were most impacted by the suspension of in-person teaching, highlighting the importance of schooling and the need for recovery efforts at these levels. Full article

Interventions have been designed to close achievement gaps in Science, Technology, Engineering, and Math (STEM) disciplines and to remedy the “leaky STEM pipeline”. However, there has been little focus on designing complementary interventions that seek to broaden the youth population who “enter the STEM pipeline”. The current work aims to broaden STEM engagement in youth by developing a STEM intervention using unrecognized forms of cultural capital. These novel, basketball-based interventions were designed to engage a naturally occurring population of youth with pre-existing interest in sports but low levels of pre-existing STEM interest, ranging from the 2nd to the 12th grades. These interventions utilized sports as a venue for informal STEM learning across three variations: a single-hour event, a one-day clinic, and a multi-day camp. Participants’ interest in pursuing a STEM career significantly increased across all three variations of the STEM intervention. Notably, these effect sizes were descriptively larger for programs of longer duration and were significantly stronger for students who reported playing basketball prior to the program. The current work introduces a novel STEM education intervention that has been shown to be repeatedly successful in utilizing students’ pre-existing interest in sports as a bridge to STEM engagement. Full article

This study aimed to validate the usefulness of the Simplified Computerized Comprehensive Learning Ability Screening Test (SCLST) in schools and homes, to facilitate early detection and intervention for children with reading disorder (RD), math disorder (MD), or attention-deficit hyperactivity disorder (ADHD). Participants included 207 children and adolescents diagnosed with ADHD, RD, or MD and the healthy control group that was matched 1:1 by gender, age, and educational years. Higher rates of omission errors, commission errors, and standard deviation of response times were observed in the ADHD group (p < 0.001) in the SCLST-ADHD. The accuracy rates of the SCLST-RD and SCLST-MD were lower in the RD (p < 0.001) and MD group (p < 0.01), respectively. The mean response times were higher in the MD group (p < 0.001). In addition, the optimal sensitivity and specificity values were 84.6% and 88.5%, and the positive and negative predictive values were 88.0% and 85.2%, respectively, in the SCLST-ADHD. In the SCLTS-RD, the sensitivity and specificity values were 81.1% and 85.6%, and the positive and negative predictive values were 84.9% and 81.9%, respectively. In the SCLST-MD, the sensitivity and specificity values were 97.4% and 76.9%, and the positive and negative predictive values were 80.9% and 96.8%, respectively. Thus, by supporting timely assessment and intervention, this tool can support clinicians and educators in early-stage learning disabilities screening and reduce long-term psychosocial impairments. Full article

The transition stage to pre-primary school represents a key event, in which the support received from family and teachers is essential in facilitating the transition and in ensuring an effective adjustment to the school environment. Our study aimed to investigate the impact of mathematical prerequisites on cognitive development, compared to the impact of reading and writing prerequisites, from the perspective of parents and early childhood educators. Thus, we quantified the impact of reading–writing and math prerequisites on children’s transition from kindergarten to school, analyzing the challenges, opportunities, and possibilities that arise. The sample consisted of 685 parents and 188 teachers, using the preschool prerequisites screening standardized questionnaire developed by the company Cognitrom, a questionnaire-survey, and the focus group method. Initially, the fidelity of the research instrument was assessed by calculating Cronbach’s alpha coefficient. The data distribution was tested using the skewness and kurtosis coefficients. Subsequently, descriptive analyses were carried out in order to provide an overview of the data collected by performing a multiple linear regression analysis. In addition, the Phi coefficient and V Cramer’s V coefficient were used to analyze the association between the research variables. By corroborating the obtained results, we can state that, from the parents’ and early childhood teachers’ perspective, math prerequisites have a greater influence on children’s cognitive development in the transition process from kindergarten to school compared to reading–writing prerequisites, confirming the general hypothesis. Full article

Enhancing mathematical achievement has been identified as a pivotal issue in school education, extending beyond mathematics education alone. However, research comprehensively examining the relationship between multiple affective variables and learning and mathematics achievement is limited. The present study examines the relationship between self-efficacy, mathematics anxiety, behavioural engagement, and mathematics achievement among students in Japan. Moreover, this study examines whether there are any differences in this relationship according to gender and socio-economic status (SES). A path analysis using the data from students in Japan (n = 5760) in the PISA 2022 dataset revealed that (1) self-efficacy for formal and applied mathematics was significantly negatively related to mathematics anxiety and significantly positively related to behavioural engagement and mathematics achievement, (2) self-efficacy for mathematical reasoning and 21st-century mathematics was found to be significantly negatively associated with mathematics anxiety and positively associated with behavioural engagement, and (3) while a negative correlation was observed between mathematics anxiety and behavioural engagement, a significant relationship was not identified between the two and mathematics achievement. Furthermore, the multiple-group structural equation modelling, with gender and SES as the grouping variable, demonstrated no differences in gender and SES in the relationship between self-efficacy, mathematics anxiety, behavioural engagement, and math achievement. Full article

This study examines the effects of implementing a movement-integrated instruction (MII) program in third-grade mathematics classes with a focus on students’ mathematical learning outcomes and physical literacy development. The program was designed using the Analysis, Design, Development, Implementation and Evaluation (ADDIE) instructional model and was implemented in a public elementary school in South Korea. While the primary instructional emphasis was placed on improving mathematical concept comprehension and problem solving, the study also evaluated outcomes in three core areas of physical literacy: physical competence, motivation and confidence, and knowledge and understanding of physical activity. A descriptive qualitative approach was adopted and supplemented with quantitative data. The data sources included classroom observations, learning artifacts, teacher reflections, semi-structured interviews, and structured student surveys. The results showed that 82.6% of students reported improved bodily control and coordination, while 75.4% indicated that they used skills acquired through physical education (PE) to solve math problems. Student work demonstrated an increasing use of multi-step reasoning, diagrammatic representations, and contextual explanations, suggesting that embodied learning reinforces both cognitive engagement and physical development. Although challenges related to time, space, and varying motor abilities were encountered, they were addressed through interdisciplinary integration and differentiated instructional strategies. This study provides empirical support for MII as a pedagogical model that effectively bridges academic learning and physical development, and offers practical recommendations for broader applications in elementary education. Full article