Aiding Transfer in Statistics: Examining the Use of Conceptually Oriented Equations and Elaborations during Subgoal Learning.
Aiding Transfer in Statistics: Examining the Use of Conceptually Oriented Equations and Elaborations during Subgoal Learning.
复制标题
协助统计迁移：检查子目标学习期间概念导向方程和阐述的使用。
DOI：
10.1037/0022-0663.95.4.762
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发表时间：
2003
影响因子：
4.9
通讯作者：
M. M. Merrill
中科院分区：
文献类型：
--
作者：
R. Atkinson;R. Catrambone;M. M. Merrill
与子目标学习方法相一致，作者假设，与使用计算导向方程学习统计示例的学习者相比，使用概念导向方程学习统计示例的学习者将更成功地转移到新问题。面向概念的方程旨在捕捉概念与其计算之间的关系，而面向计算的方程旨在简化计算。这一假设在2个实验中得到支持。作者还研究了在学习之前或之后为学习者提供示例中说明的详细说明的含义。精心制作的位置没有明显的影响。总体而言，这些结果表明，解决方案的程序组织在适当的概念为导向的子目标更容易适应新的问题比程序建立在计算友好，但概念上不透明的步骤。（PsycINFO数据库记录（c）2016阿帕，保留所有权利）
Consistent with a subgoal-learning approach, the authors hypothesized that learners who studied statistics examples with conceptually oriented equations would transfer more successfully to novel problems compared with learners who studied examples using computationally oriented equations. The conceptually oriented equations were designed to capture the relationship between the concept and its computation, whereas the computationally oriented equations were designed to simplify calculations. This hypothesis was supported across 2 experiments. The authors also examined the implications of providing learners with elaborations of the procedures illustrated in the examples either before or after they studied them. The location of the elaborations had no apparent effect. Overall, these results demonstrate that solution procedures organized around appropriate conceptually oriented subgoals are easier to adapt for novel problems than procedures built around computationally friendly, but conceptually opaque, steps. (PsycINFO Database Record (c) 2016 APA, all rights reserved)