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解构塔:伦敦塔任务中问题难度的参数和预测因素。

Deconstructing the tower: parameters and predictors of problem difficulty on the Tower of London task.

机构信息

Department of Psychology, University of Florida, United States.

出版信息

Brain Cogn. 2010 Apr;72(3):472-82. doi: 10.1016/j.bandc.2010.01.002. Epub 2010 Feb 18.

DOI:10.1016/j.bandc.2010.01.002
PMID:20167413
Abstract

The Tower of London (TOL) task has been widely used in both clinical and research realms. In the current study, 104 healthy participants attempted all possible moderate- to high-difficulty TOL problems in order to determine: (1) optimal measures of problem solving performance, (2) problem characteristics, other than the minimum moves necessary to solve the problem, that determine participants' difficulty in solving problems successfully, quickly, and efficiently, and (3) effects of increased task experience on which problem characteristics determine problem difficulty. A factor analysis of six performance measures found that, regardless of task experience, problem difficulty could be captured well either by a single factor corresponding to general quality of solution or possibly by three subordinate factors corresponding to solution efficiency, solution speed, and initial planning speed. Regression analyses predicting these performance factors revealed that in addition to a problem's minimum moves three problem parameters were critical in determining the problem difficulty: goal position hierarchy, start position hierarchy, and number of solution paths available. The relative contributions of each of the characteristics strongly depended on which performance factor defined performance. We conclude that TOL problem performance is multifaceted, and that classifying problem difficulty using only the minimum moves necessary to solve the problem is inadequate.

摘要

伦敦塔任务(TOL)已广泛应用于临床和研究领域。在本研究中,104 名健康参与者尝试了所有可能的中等到高难度 TOL 问题,以确定:(1)解决问题表现的最佳衡量标准,(2)除了解决问题所需的最少移动次数之外,还有哪些问题特征决定了参与者成功、快速和有效地解决问题的难度,以及(3)增加任务经验对哪些问题特征决定问题难度的影响。对六种表现衡量标准的因子分析发现,无论任务经验如何,都可以通过与解决方案整体质量对应的单一因子,或者通过与解决方案效率、解决方案速度和初始规划速度对应的三个从属因子,很好地捕捉问题难度。预测这些表现因素的回归分析表明,除了问题的最少移动次数之外,三个问题参数对于确定问题难度至关重要:目标位置层次结构、起始位置层次结构和可用的解决方案路径数量。每个特征的相对贡献强烈依赖于定义表现的特定表现因素。我们的结论是,TOL 问题的表现是多方面的,仅使用解决问题所需的最少移动次数来分类问题难度是不够的。

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