Intelligence is a well-supported predictor of school achievement, however, it refers only to the cognitive facet of learning determinants. The aim of this article is to contrast the predictive properties of two comprehensive concepts developed within the actiotope model of giftedness (AMG) with that of intelligence. These concepts are educational and learning capital (ELC) and the domain impact level of activities (DILA), which were contrasted with a nonverbal intelligence measure (Raven’s standard progressive matrices). We investigated N = 90 fourth graders from regular classes in a German urban area. Results showed that achievement in German language was better predicted by ELC and DILA than by intelligence, whereas mathematical achievement was predicted by intelligence and educational and learning capital to similar degrees. The AMG concepts also showed incremental predictive power over intelligence. These findings suggest that ELC and, with some limitation, DILA (a) are well suited for predictions of school achievement and (b) capture valuable different aspects of the learning system than intelligence measures. Implications for education and research are discussed.

中文翻译：

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智力、教育和学习资本以及活动的领域影响水平作为学校成绩的预测指标

智力是学业成绩的一个得到充分支持的预测指标，然而，它仅指学习决定因素的认知方面。本文的目的是比较在天才行为模型 (AMG) 中开发的两个综合概念的预测特性与智力的预测特性。这些概念是教育和学习资本 (ELC) 和活动的领域影响水平 (DILA)，它们与非语言智力测量（Raven 的标准渐进矩阵）形成对比。我们调查了来自德国城市地区普通班级的 N = 90 名四年级学生。结果表明，ELC 和 DILA 比智力更能预测德语成绩，而智力和教育和学习资本对数学成绩的预测程度相似。AMG 概念还显示出对智能的增量预测能力。这些发现表明，ELC 和 DILA（有一些限制）（a）非常适合预测学校成绩，（b）捕捉学习系统的有价值的不同方面，而不是智力测量。讨论了对教育和研究的影响。