Wee Serena
School of Psychological Science, University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia.
School of Social Sciences, Singapore Management University, 90 Stamford Road, Level 4, Singapore 178903, Singapore.
J Intell. 2018 Sep 7;6(3):40. doi: 10.3390/jintelligence6030040.
The purpose of the current study is to compare the extent to which general and specific abilities predict academic performances that are also varied in breadth (i.e., general performance and specific performance). The general and specific constructs were assumed to vary only in breadth, not order, and two data analytic approaches (i.e., structural equation modeling [SEM] and relative weights analysis) consistent with this theoretical assumption were compared. Conclusions regarding the relative importance of general and specific abilities differed based on data analytic approaches. The SEM approach identified general ability as the strongest and only significant predictor of general academic performance, with neither general nor specific abilities predicting any of the specific subject grade residuals. The relative weights analysis identified verbal reasoning as contributing more than general ability, or other specific abilities, to the explained variance in general academic performance. Verbal reasoning also contributed to most of the explained variance in each of the specific subject grades. These results do not provide support for the utility of predictor-criterion alignment, but they do provide evidence that both general and specific abilities can serve as useful predictors of performance.
本研究的目的是比较一般能力和特殊能力对学术表现(即综合表现和特定表现)的预测程度,这些学术表现的广度也各不相同。一般能力和特殊能力的结构被假定仅在广度上有所不同,而在顺序上并无差异,并且对与这一理论假设相符的两种数据分析方法(即结构方程模型[SEM]和相对权重分析)进行了比较。基于数据分析方法的不同,关于一般能力和特殊能力相对重要性的结论也有所不同。结构方程模型方法将一般能力确定为综合学术表现的最强且唯一显著的预测因素,一般能力和特殊能力均无法预测任何特定学科成绩的残差。相对权重分析表明,言语推理对综合学术表现的解释方差的贡献超过一般能力或其他特殊能力。言语推理对每个特定学科成绩的大部分解释方差也有贡献。这些结果并不支持预测指标与标准一致性的效用,但它们确实提供了证据,表明一般能力和特殊能力都可以作为表现的有用预测因素。