Geary David C, Hoard Mary K, Nugent Lara, Scofield John E
University of Missouri.
J Educ Psychol. 2021 May;113(4):754-769. doi: 10.1037/edu0000487. Epub 2020 Jul 2.
Identifying meaningful cognitive and non-cognitive predictors of mathematical competence is critical for developing targeted interventions for students struggling with mathematics. Here, 317 students' short-term verbal memory, verbal and visuospatial working memory, complex spatial abilities, intelligence, and mathematics attitudes and anxiety were assessed, and their teachers reported on their attentive-behavior in seventh-grade mathematics classrooms. Bayesian regression models revealed that complex spatial abilities and in-class attention were the most plausible predictors of seventh-grade mathematics, but not word reading, achievement, controlling for prior achievement. These results were confirmed with multilevel models that revealed interactions between these factors and prior achievement. The largest gains were among students with strong mathematical competencies in sixth-grade, and average or better in-class attention in seventh-grade as well as above average spatial abilities. High mathematics anxiety was associated with lower attention and through this indirectly influenced achievement gains. These results have implications for how to best target interventions for students at risk for long-term difficulties with mathematics.
识别有意义的数学能力认知和非认知预测因素对于为数学学习困难的学生制定有针对性的干预措施至关重要。在此,对317名学生的短期言语记忆、言语和视觉空间工作记忆、复杂空间能力、智力以及数学态度和焦虑进行了评估,他们的教师报告了他们在七年级数学课堂上的注意力行为。贝叶斯回归模型显示,复杂空间能力和课堂注意力是七年级数学最合理的预测因素,但单词阅读、成绩并非如此,同时控制了先前的成绩。多层次模型证实了这些结果,该模型揭示了这些因素与先前成绩之间的相互作用。最大的进步出现在六年级数学能力强、七年级课堂注意力平均或更好且空间能力高于平均水平的学生中。高数学焦虑与注意力降低有关,并由此间接影响成绩提升。这些结果对于如何最好地针对有长期数学困难风险的学生进行干预具有启示意义。