摘要
平衡秤任务是儿童高级认知策略研究非常著名的一种形式,Siegler提出的规则评估技术极大地推动了解题规则的相关研究,但在应用过程中显现了规则评估技术的不稳定性等诸多局限。目前,平衡秤任务的解题规则的研究方法发展迅速,基于潜变量的分析方法已克服了这些不足,在统计方面具有明显优势。因此,我国教育与心理研究者应关注使用潜在类别分析等方法解决高级认知策略研究中的各种问题。
The balance scale task has been frequently studied in developmental psychology. Siegler＇s rule assessment methodology {RAM） has greatly promoted the research on children＇s problem-solving rules on balance scale task. However, RAM was frequently criticized for lacking statistical background and its instability. With the development of research on cognitive rules, the shortcomings of RAM can be solved by latent class analysis （ LCA } by which we can test statistically how many rules are needed to fit the data and these rules. In the present paper, principles of RAM and LCA are reviewed and compared extensively. China＇s educational and psychological researchers should utilize the latent class analysis to analyze high-level cognitive strategies for a variety of tasks.
出处
《赣南师范学院学报》
2014年第1期86-90,共5页
Journal of Gannan Teachers' College(Social Science(2))
基金
江西省教育科学规划重点课题(13ZD2L005)
江西省高校人文社会科学研究青年基金项目(XL1302)
赣南医学院人才引进课题(2008154)
关键词
平衡秤任务
解题策略
潜在类别分析
认知规则
balance scale task
solution strategy
latent class analysis
cognitive rules
