Search Results (83)

This study aimed to investigate the use of a structured learning outcomes approach for fifth-grade mathematics instruction, with a focus on students with difficulties in learning mathematics, across two mainstream schools in Kuwait. Three special education teachers, across three classes, who worked with 30 focus students, participated in the study. Teachers implemented a structured approach to curriculum and pedagogy based on a focus on learning outcomes, simultaneously supported by a dedicated technology platform, with the aim of encouraging a focus on differentiation to meet individual learning needs. This study employed a mainly qualitative approach involving interviews to gauge teacher perceptions of the extent to which this approach supported them in thinking more effectively about individual learning needs. Links are made to the extant literature in this area, and recommendations are made for future research using this learning outcomes approach based on a wider sample of mainstream schools and classrooms. Full article

In this research brief, we synthesize research on integrated STEAM teaching and learning from our multi-state team, comprised of scholars from elementary mathematics and science education. This work focuses on student perceptions of STEAM experiences to inform practitioners, researchers, and stakeholders in best practices. This synthesis brings forth the following contributions to STEAM education learned from elementary students’ perspectives of their STEAM learning experiences to offer new ideas about best practices in STEAM: (1) students have various access points to STEAM and connect with the personal expression and meaning-making related to the “arts” embedded in the experience; (2) empathy can be an important driver of deep engagement with their learning experiences towards a transformative outcome; and (3) STEAM learning experiences can be a space for implementing student-centered instructional practices guided by reform efforts in science and mathematics education. Next steps will be discussed to complement the burgeoning STEAM education literature base with a continued focus on all students’ perspectives about their learning experiences. We recommend longitudinal studies on the impact of STEAM; these are now possible as STEAM initiatives become more systematically rooted in schools and communities. 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

Mathematical activities, which have the potential to engage students cognitively, are an essential component of modern educational approaches. The design of learning environments that facilitate the full realization of the potential of mathematical activities is as crucial as the activities themselves. Well-designed physical, social, and emotional learning environments significantly contribute to students’ holistic development. Pre-service teachers’ perceptions regarding the ideal learning environment for mathematical activities can shape the quality of learning environments they will create professionally. This study explores the perceptions of pre-service primary school teachers and pre-service elementary mathematics teachers regarding the ideal learning environment for mathematical activities through their drawings and related reflections. This study employs a qualitative case study design, and data were collected through freehand drawings depicting ideal learning environments and semi-structured interviews with pre-service teachers. The analysis reveals five prominent components of the ideal learning environment for mathematical activities: purpose, instructional methods and techniques, teacher–student roles, seating arrangements, and interrelations among these components. The findings indicate differences in perceptions between pre-service primary school teachers and pre-service elementary mathematics teachers. Additionally, the results highlight that these components are interrelated within the learning environment, with the purpose component serving as a guiding factor for the others. Full article

With the increasing emphasis on personalized learning, there is a growing demand for automated systems that analyze individual students’ learning states and provide effective feedback. This study proposes a system that analyzes elementary school mathematics diagnostic assessment data to generate personalized feedback. The proposed system integrates Term Frequency-Inverse Document Frequency (TF-IDF) and eXtreme Gradient Boosting (XGBoost) to vectorize textual data and automatically classify learning error patterns. The study utilizes 15,000 diagnostic assessment records collected from 2020 to 2024. After preprocessing, TF-IDF was employed to extract relevant features, and XGBoost was used to train a classification model. To validate the model’s performance, comparative experiments were conducted with Logistic Regression, Support Vector Machine (SVM), LightGBM, BERT, and DistilBERT. The TF-IDF + XGBoost model achieved an accuracy of 98.85% and an F1 Score of 0.9860, outperforming other models. Furthermore, the system demonstrated an average real-time processing speed of 1.3 s, ensuring instant feedback in educational settings. This study highlights the automation and scalability of educational data analysis, suggesting potential applications across various subjects and grade levels. Full article

In recent years, rapidly advancing technology has reshaped our world, holding the potential to transform social and economic structures. The United Nations’ Sustainable Development Goals (SDGs) provide a comprehensive roadmap that promotes not only economic growth but also social, environmental, and global sustainability. Meanwhile, artificial intelligence (AI) has emerged as a critical technology contributing to sustainable development by offering solutions to both social and economic challenges. One of the fundamental ideas is that education should always maintain a dynamic structure that supports sustainable development and fosters individuals equipped with sustainability skills. In this study, the impact of various variables related to AI applications in primary education at the elementary school level, in line with sustainable development goals, was evaluated using a mixed meta-method complemented with quantitative analyses. Within the framework of the mixed meta-method, a meta-analysis of data obtained from studies conducted between 2005 and 2025 was performed using the CMA program. The analysis determined a medium effect size of g = 0.51. To validate the meta-analysis results and enhance their content validity, a meta-thematic analysis was conducted, applying content analysis to identify themes and codes. In the final stage of this research, to further support the data obtained through the mixed meta-method, a set of evaluation form questions prepared within the Rasch measurement model framework was administered to primary school teachers. The collected data were analyzed using the FACETS program. The findings from the meta-analysis document review indicated that AI studies in primary education were most commonly applied in mathematics courses. During the meta-thematic analysis process, themes related to the impact of AI applications on learning environments, challenges encountered during implementation, and proposed solutions were identified. The Rasch measurement model process revealed that AI applications were widely used in science and mathematics curricula (FBP-4 and MP-2). Among the evaluators (raters), J2 was identified as the most lenient rater, while J11 was the strictest. When analyzing the AI-related items, the statement “I can help students prepare a presentation describing their surroundings using AI tools” (I17) was identified as the most challenging item, whereas “I understand how to effectively use AI applications in classroom activities” (I14) was found to be the easiest. The results of the analyses indicate that the obtained data are complementary and mutually supportive. The findings of this research are expected to serve as a guide for future studies and applications related to the topic, making significant contributions to the field. Full article

Recent studies have provided convincing evidence highlighting the strong relationship between spatial reasoning and mathematical performance. However, there is a limited body of research exploring the contributions of different spatial reasoning constructs to mathematical performance across various content domains, particularly within non-Western contexts. This study investigates the relationship between spatial reasoning skills—including mental rotation, spatial visualization, and spatial orientation—and mathematical performance across various domains (number, geometric shapes and measures and data display) among Chinese elementary school students in grade four (ages 9–10). The results indicate that overall spatial reasoning significantly predicts mathematical performance across various domains. All three spatial reasoning constructs significantly contribute to performance in the number and geometric shapes and measures domains, with mental rotation and spatial orientation being the strongest predictors of performance in these respective content domains. For data display performance, spatial orientation and spatial visualization significantly contribute, with spatial visualization being the strongest predictor. Although no significant gender differences were found in the overall link between spatial reasoning and mathematical performance, subgroup regression analysis showed variations. For male students, spatial orientation was the main predictor across content areas. For female students, mental rotation was the key predictor for number and geometry, while spatial visualization was most significant for data display. Full article

In the last decade, a growing number of schools have begun implementing dual language education (DLE), and studies have shown evidence of the benefits of DLE for elementary education students. However, existing research syntheses do not focus on DLE in the early years (pre-Kindergarten and Kindergarten), considering young bilingual children’s development and learning characteristics. In this paper, a novel conceptual framework is used to explore the extant literature on DLE in the early years moving beyond Bronfenbrenner’s ecological systems theory to consider additional characteristics relating to bilingual children’s development and learning. A systematic literature review was conducted following a rigorous procedure, resulting in nine studies that met the inclusion criteria. Information about each study was coded and analyzed. The results describe the studies’ sample characteristics, research design, and findings organized by students’ academic skills (i.e., language, literacy, and mathematics), dual language classroom practices, and parents’ perceptions of DLE. This paper highlights current knowledge of DLE programs in the early years, identifies gaps, and offers recommendations for future research, policy, and practice. Full article

Considering that the teaching of mathematics in elementary school is an important prerequisite for the development of mathematically literate citizens, it is essential to identify what makes it effective. The aim of this study is to determine the characteristics of effective interventions in elementary school mathematics education. To this end, a scoping review was conducted that included 44 experimental studies published between 2014 and 2023. Through a qualitative analysis of the intervention descriptions, we identified 27 characteristics, which were categorized into nine thematic units. We found that, on average, seven characteristics were used per intervention. The results of this study suggest that effective elementary school mathematics instruction should foster students’ conceptual understanding and procedural fluency through problem-solving, active learning, and mathematical games. This can be achieved through a dynamic alternation of whole-class instruction and cooperative and individual learning with the use of manipulatives and visualizations to reach the level of abstraction. Considering that the analyzed interventions rarely addressed students’ common errors and critical thinking, future research could focus on these aspects in elementary school mathematics education. Full article

The COVID-19 pandemic led to extensive school closures and an accelerated shift to remote learning, which had substantial consequences for students’ academic development. This study seeks to examine the impact of COVID-19 on learning loss among elementary students in southern Italy, with a focus on grade-level variations across key academic domains, including spelling, reading comprehension, reading speed and accuracy, and mathematical abilities. A sample of 332 students from grades II through V participated, with their performance being evaluated using standardized assessments for each academic skill. Findings revealed that students in grade III encountered greater difficulties in spelling and reading comprehension compared to both older and younger cohorts, indicating that remote learning may have disproportionately affected the initial stages of skill acquisition. These results highlight the necessity for targeted interventions, especially for younger students and those with preexisting academic challenges, to address the lasting effects of pandemic-related educational disruptions. Full article

Elementary school curricular standards in the United States emphasize mathematics and literacy, while social studies and science are often left behind. Integrating science instruction with either mathematics or literacy is a strategy some teachers use to teach skills and concepts in both disciplines. Understanding science at a young age is reliant on grasping vocabulary that is new to the learner. Integrating visual imagery into reading instruction improves students’ comprehension, enhances retrieval, and increases retention. The media-based reading enhancement of text through spatial computing has begun to show promise for the integration of science vocabulary and reading comprehension, especially for low-proficiency readers. This paper provides a literary rationale for technology-enhanced intervention, provides examples of a study conducted to test the efficacy of such an intervention, presents the implications of the study’s findings, and discusses future avenues for how spatial computing might be used in science and literacy instruction in the future. Full article

School-age children and being outdoors are intrinsically linked. Education and the outdoors offer unique opportunities to extend the learning potential of children at this age in a more engaging way. From the point of view of mathematics, this way of learning is very suitable and certainly motivating for the pupils since mathematics, especially geometry, is not very popular among pupils. Therefore, in this article, we describe how we used an out-of-school learning experience for second-level primary school pupils (sixth to ninth grade) to link mathematics to outdoor learning. Activities that we solved with pupils in the outdoor environment were solved in the teaching process using only modeling. Practical applications were illustrated through interesting topographic fieldwork, which we analyzed for their appropriate integration into the teaching process by means of a priori analysis. The inclusion of these practical problems was preceded by research on 781 pupils of primary schools who solved application problems related to the circle and the square. It was clear from the research that pupils have a significant problem with the geometric interpretation of simple geometric concepts, which can be improved with the use of mathematical modeling and the linking of similar problems that can be carried out in a non-school environment. Full article

Augmented reality (AR) technology provides context-aware experiences by overlaying digital information onto the real world to enhance learning effectiveness and reduce cognitive load. This study aimed to develop an AR Mobile Learning System (ARMLS) to address the limitations of traditional teaching materials and help elementary-school students learn geometric concepts. The ARMLS was designed based on the fifth-grade mathematics curriculum, covering topics such as definitions, geometric properties, different views of prisms and pyramids, and their relationships. A teaching experiment was conducted to compare students’ learning achievement, motivation, and cognitive load when using the ARMLS versus traditional teaching materials. This study adopted a quasi-experimental design, where four fifth-grade classes were selected from an elementary school in northern Taiwan as experimental subjects. A total of 66 students participated in the experiment, divided into two groups: 32 students from two classes as the experimental group (using the ARMLS) and 34 students from the other two classes as the control group (using traditional teaching materials). In the teaching experiment, data were collected through pre-tests, post-tests, and questionnaires. Achievement tests assessed learning effectiveness, while learning motivation and cognitive load were measured with standardized scales. System satisfaction was evaluated using a questionnaire. The Johnson–Neyman method determined the regions of significance in the analysis of covariance. Independent-sample t-tests evaluated differences in learning motivation and cognitive load between the groups, and descriptive statistics summarized system satisfaction responses. The results indicated that (1) the ARMLS enhanced the learning achievement among low- and moderate-achieving students, (2) there was no significant difference in learning motivation between the two groups, (3) the ARMLS helped reduce students’ cognitive load, and (4) most students expressed satisfaction with the ARMLS according to the questionnaire results. The ARMLS enhances engagement and deepens understanding by making abstract geometry topics more accessible. It effectively overcomes the limitations of traditional teaching materials, providing elementary students with an interactive, hands-on approach to learning geometric concepts. Full article

Scholars have claimed that artificial intelligence can be used in education to transform learning. However, there is insufficient evidence on whether intelligent tutoring systems (ITSs), a representative form of artificial intelligence in education, has transformed the teaching and learning of mathematics. To fill this gap, this systematic review was conducted to examine empirical studies from 2003 to 2023 that used ITSs in mathematics education. Technology integration was coded using the substitution, augmentation, modification, redefinition (SAMR) model, which was extended to suit ITSs in a mathematics education context. How different contexts and teacher roles are intertwined with SAMR levels were examined. The results show that while ITSs in mathematics education primarily augmented existing learning, recent ITS studies have transformed students’ learning experiences. ITSs were most commonly applied at the elementary school level, and most ITS studies focused on the areas of number and arithmetic, algebra, and geometry. The level of SAMR varied depending on the research purpose, and ITS studies in mathematics education were mainly conducted in a way that minimized teacher intervention. The results of this study suggest that the affordance of an ITS, the educational context, and the teacher’s role should be considered simultaneously to demonstrate the transformative power of ITSs in mathematics education. Full article

Visual thinking leverages spatial mechanisms in animals for navigation and reasoning. Therefore, given the challenge of abstract mathematics and logic, spatial reasoning-based teaching strategies can be highly effective. Our previous research verified that innovative box-and-ball coloring activities help teach elementary school students complex notions like quantifiers, logical connectors, and dynamic systems. However, given the richness of the activities, correction is slow, error-prone, and demands high attention and cognitive load from the teacher. Moreover, feedback to the teacher should be immediate. Thus, we propose to provide the teacher with real-time help with LLMs. We explored various prompting techniques with and without context—Zero-Shot, Few-Shot, Chain of Thought, Visualization of Thought, Self-Consistency, logicLM, and emotional —to test GPT-4o’s visual, logical, and correction capabilities. We obtained that Visualization of Thought and Self-Consistency techniques enabled GPT-4o to correctly evaluate 90% of the logical–spatial problems that we tested. Additionally, we propose a novel prompt combining some of these techniques that achieved 100% accuracy on a testing sample, excelling in spatial problems and enhancing logical reasoning. Full article