AI Insight
This study examined how different types of mathematics homework assignments affect academic performance among 18,202 Chinese eighth-grade students under China's "Double Reduction" policy. The research found that homework combinations including test-preparation exercises directly improved performance, while combinations involving applied or project-based homework enhanced performance indirectly by first increasing students' interest in homework, which then increased their general learning interest. The relationship between homework types and academic achievement was primarily mediated through a sequential chain where homework-specific interest led to broader learning interest, which subsequently predicted better mathematics performance.
Why it matters
The findings provide evidence-based guidance for educators on designing homework that balances direct skill-building with interest-generating activities to maximize both student motivation and academic outcomes. This is particularly relevant in contexts implementing homework reduction policies, showing that homework quality and variety may matter more than quantity alone.
Understand the Science
The aim of this study is to investigate the relationship between eighth-grade students’ mathematics homework types and their combinations and their Mathematics Academic Performance (MAP) in the context of China’s “Double Reduction” policy, emphasizing the chain mediating role of mathematics homework interest and learning interest. A total of 18,202 eighth-grade students completed a cross-sectional survey administered in a mixed online–offline mode. We adopted a mediation analysis method with multicategorical independent variables, using Practice Homework (PH) as the reference category. The results showed that homework combinations containing Test-Preparation Homework (TPH) tend to improve MAP through direct effects, while homework combinations including Applied/Project-Based Homework (APH)—in particular PH + APH—are more likely to enhance students’ interest and improve MAP indirectly. In addition, homework interest and learning interest mediated the link between specific homework types (and their combinations) and MAP, primarily through a sequential chain mediation pathway in which homework interest predicted learning interest, which in turn predicted MAP. These findings clarify the mechanisms through which homework design—considering both types and combinations—relates to students’ MAP in a “Double Reduction” policy context, offering practical guidance for educators on assigning homework that enhances learning motivation and academic performance.