The U.S. Nation’s Report Card reveals that lower performing students exhibited greater achievement decline than their average/high performing peers based on 2022 long-term trend mathematics assessments for age 9 students. Technology, including computer-assisted instruction, plays an important role in today’s dynamic learning environments. Currently, there is a lack of computer-assisted intervention programs that systematically teach generalized word problem-solving skills that are driven by mathematical models. Model-based problem solving (MBPS) is one of the essential emphases in the Common Core mathematical practice standards. This study investigated the effects of a web-based computer tutor, MBPS, on enhancing word problem-solving performance of elementary students who are struggling in mathematics. The MBPS tutor incorporates best practices that are identified by the Institute of Educational Sciences’ (IES) latest practice guide, including providing systematic instruction, visual and verbal supports, and teaching of precise mathematical language. Findings indicate that the MBPS tutor boosted participants’ performance above and beyond the business-as-usual comparison group.

This study investigated the impact of visual cueing on attention guidance, deep-thinking promotion, and performance optimization in arithmetic word problem solving for students with mathematical learning difficulties (MLD). The participants included eight students with MLD and twenty students without MLD who attempted to solve mathematical word problems with and without visual cueing. Eye movements were recorded during the tasks. A repeated-measure design and nonparametric tests were applied to enhance the statistical power of the study. The data analysis results indicated that visual cueing effectively guided and sustained the attention of students with MLD, reducing their off-task duration. However, it showed limited influence in facilitating deep thinking and performance improvement for these students. There were no significant attention-guidance or performance-improvement effects observed in the problem-solving processes of students without MLD, who initially demonstrated better concentration levels and performance. The potential explanations for these findings are further discussed in this paper.

Measurement concepts are an essential foundation for more advanced mathematical concepts. To address the challenges of students with autism spectrum disorder (ASD) in learning measurement concepts, this study investigated the effects of using a combination of explicit instruction and virtual manipulatives (VMs) to teach measurement concepts to students with ASD in China. Using a single-case multiple-probe across skills design, researchers examined whether the intervention could support the acquisition and maintenance of measurement concepts in students with ASD. Based on visual analysis, a functional relation was found between the independent variable (i.e., explicit instruction with VMs) and student performance on solving measurement concepts problems. Implications for practice and research are discussed.

This study examined how mathematics anxiety, trait emotional intelligence, and mathematics self‐concept predict calculation fluency, numerical operations, and mathematical reasoning in students with and without mathematics learning difficulties (MLD). Participants ( N = 326) were third‐ to fifth‐grade students from China who completed standardized mathematics performance assessments and self‐report measures of mathematics anxiety and trait emotional intelligence. Structural equation modelling showed that mathematics anxiety negatively influenced all mathematics outcomes, whereas trait emotional intelligence had a positive impact. Mathematics self‐concept mediated the effects of mathematics anxiety in the full sample, with partial mediation for calculation fluency and full mediation for mathematical reasoning and numerical operations. No mediation effects were found for students with MLD. These results emphasize the need to address affective and non‐cognitive factors in interventions and highlight the critical roles of self‐concept and trait emotional intelligence in improving mathematics performance across diverse student populations.