首页    期刊浏览 2024年10月05日 星期六
登录注册

文章基本信息

  • 标题:Predicting Mathematical Learning Difficulties Status: The Role of Domain-Specific and Domain-General Skills
  • 本地全文:下载
  • 作者:Riikka Mononen ; Markku Niemivirta ; Johan Korhonen
  • 期刊名称:International Electronic Journal of Elementary Education
  • 印刷版ISSN:1307-9298
  • 出版年度:2022
  • 卷号:14
  • 期号:3
  • 页码:335-352
  • DOI:10.26822/iejee.2022.248
  • 语种:English
  • 出版社:International Electronic Journal of Elementary Education
  • 摘要:This study investigated which domain-specific and domain-general skills measured at grade 1 predict mathematical learning difficulties (MLD) status at grade 3. We used different cut-off criteria and measures of mathematics performance for defining the MLD status. Norwegian children’s (N= 206) numeracy, cognitive, and language skills were measured at grade 1 and arithmetic fluency and curriculum-based mathematics (CBM) at grade 3. Logistic regression analyses showed that symbolic numerical magnitude processing, verbal counting, and rapid automatized naming predicted MLD25 status (performance ≤ 25th percentile) based on arithmetic fluency, whereas verbal counting skills and nonverbal reasoning predicted the status based on CBM.The same predictors were found for MLD10 status (performance ≤ 10th percentile), and in addition, rapid automatized naming predicted the status based on CBM. Only symbolic numerical magnitude processing and verbal counting predicted LOW status (performance between 11–25th percentile) based on arithmetic fluency, whereas nonverbal reasoning and working memory when the status was based on CBM. Different cut-off scores and mathematics measures used for the definition of MLD status are important to acknowledge, as those seem to lead to different early domain-specific and domain-general predictors of MLD.
  • 关键词:arithmetic;counting;mathematical learning difficulties;nonverbal reasoning;rapid automatized naming
国家哲学社会科学文献中心版权所有