Wei Zhou, Cheng Huang, Rongrong Huang
Independent-samples t-tests revealed no statistically significant gender differences in MK, LK, MLK, or the overall mathematical learning knowledge structure. Multiple regression analysis showed that the model significantly predicted mathematics achievement, F(4, 85) = 33.598, p < 0.001, R 2 = 0.613. LK and MLK were significant positive predictors, whereas gender and MK were not significant unique predictors.
INTRODUCTION: This study investigated the mathematical learning knowledge structures of junior high school mathematically gifted students in Nanning, China, and examined gender differences and the relationship between these knowledge structures and mathematics achievement.
METHODS: A quantitative cross-sectional survey design was adopted. The participants were 90 Grade 9 mathematically gifted students selected through criterion-based purposive sampling from nine classes in a junior high school. Data were collected using an adapted Mathematical Learning Knowledge Questionnaire and a researcher-designed Mathematics Achievement Test. The instruments were reviewed by three experts for content validity. Reliability analysis showed acceptable to high internal consistency, with Cronbach's alpha values of 0.948 for the overall questionnaire, 0.866 for MK, 0.862 for LK, 0.886 for MLK, and 0.827 for the mathematics test.
RESULTS: Independent-samples t-tests revealed no statistically significant gender differences in MK, LK, MLK, or the overall mathematical learning knowledge structure. Multiple regression analysis showed that the model significantly predicted mathematics achievement, F(4, 85) = 33.598, p < 0.001, R 2 = 0.613. LK and MLK were significant positive predictors, whereas gender and MK were not significant unique predictors.
DISCUSSION: The findings suggest that mathematics achievement among mathematically gifted students is more closely related to learning knowledge and mathematics-specific learning knowledge than to gender or mathematical knowledge alone. Teachers and curriculum planners should give greater attention to students' learning strategies, self-regulation, and mathematics-specific learning processes.