Language-Related Longitudinal Predictors of Arithmetic Word Problem Solving: A Structural Equation Modeling Approach.

Area of Science:

• Cognitive Development
• Educational Psychology
• Mathematics Education

Background:

• Longitudinal studies are crucial for understanding the development of cognitive skills.
• Early identification of factors influencing mathematical problem-solving is essential for academic success.
• Language and cognitive abilities are foundational for complex academic tasks.

Purpose of the Study:

• To investigate the longitudinal relationships between various cognitive skills and word-problem solving abilities in children.
• To determine which specific cognitive skills measured in second grade predict word-problem solving performance in fourth grade.
• To examine potential gender differences in these developmental trajectories.

Main Methods:

• Structural equation modeling was employed to analyze the data.
• Data were collected from 340 children aged 6.10 to 9.02 years.
• Cognitive skills assessed included word-problem solving, computation, working memory, nonverbal reasoning, oral language, and word reading fluency.

Main Results:

• Prior word-problem solving, computation skill, nonverbal reasoning, and oral language significantly predicted fourth-grade word-problem solving performance.
• These predictive relationships were consistent across genders, with no significant differences observed between boys and girls.
• The findings highlight the interconnectedness of language and mathematical reasoning development.

Conclusions:

• Early foundational cognitive and language skills are strong predictors of later mathematical word-problem solving abilities.
• Interventions aimed at improving these foundational skills in early elementary years may enhance mathematical competence.
• Understanding these longitudinal links is vital for developing effective educational strategies for diverse learners.