Seeing Deep Structure From the Interactions of Surface Features
Seeing Deep Structure From the Interactions of Surface Features
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DOI：
10.1080/00461520.2012.695709
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发表时间：
2012-01-01
影响因子：
8.8
通讯作者：
VanLehn, Kurt A.
中科院分区：
文献类型：
--
作者：
Chi, Michelene T. H.;VanLehn, Kurt A.
迁移通常被认为是要求个体在新的目标问题和以前遇到的源问题之间“看到”深层结构中的相同之处，即使表面特征可能不同。我们建议专家可以通过考虑显式表面特征的一阶相互作用和一阶线索之间的二阶关系来“看到”深层结构。基于这一推测性假设，我们提出了一种特定领域的自下而上的教学方法，该方法明确地教导学生专注于推导一阶互动线索，并注意一阶互动线索之间的二阶关系。要做到这一点，研究人员和教学设计师首先需要从有经验的解决者或专家那里提取他们是如何获得这种一阶线索的。迁移被认为是基于二阶关系的相似性，这是日常生活中熟悉的关系，如等于，大于，等等。
Transfer is typically thought of as requiring individuals to "see" what is the same in the deep structure between a new target problem and a previously encountered source problem, even though the surface features may be dissimilar. We propose that experts can "see" the deep structure by considering the first-order interactions of the explicit surface features and the second-order relationships between the first-order cues. Based on this speculative hypothesis, we propose a domain-specific bottom-up instructional approach that teaches students explicitly to focus on deriving the first-order interactions cues and noticing the second-order relationships among the first-order interaction cues. To do so, researchers and instructional designers need to first extract from experienced solvers or experts how they derive such first-order cues. Transfer is assumed to be based on the similarities in the second-order relationships, which are familiar everyday relationships such as equal to, greater than, and so forth.