Qizhong Ou, Xinglin Chen
Investigation and analysis of maker education curriculum from the perspective of artificial intelligence
Scientific reports
identifying types mathematics content knowledge predictive students longterm learning essential improving theories mathematical development mathematics education identify types knowledge examined longterm predictors high school students knowledge algebra overall mathematics achievement analyses large nationally representative longitudinal data sets united states united kingdom revealed elementary school students knowledge fractions division uniquely predicts students knowledge algebra overall mathematics achievement high school 5 6 years later even statistically controlling types mathematical knowledge general intellectual ability working memory family income education implications findings understanding improving mathematics learning discussed