Suppr超能文献

典型的智力投入、五大性格特征、学习方法和认知能力是学业表现的预测因素。

Typical intellectual engagement, Big Five personality traits, approaches to learning and cognitive ability predictors of academic performance.

机构信息

Department of Psychology, University College London, London, UK.

出版信息

Br J Educ Psychol. 2009 Dec;79(Pt 4):769-82. doi: 10.1348/978185409X412147. Epub 2009 Feb 25.

Abstract

BACKGROUND

Both ability (measured by power tests) and non-ability (measured by preference tests) individual difference measures predict academic school outcomes. These include fluid as well as crystalized intelligence, personality traits, and learning styles. This paper examines the incremental validity of five psychometric tests and the sex and age of pupils to predict their General Certificate in Secondary Education (GCSE) test results.

AIMS

The aim was to determine how much variance ability and non-ability tests can account for in predicting specific GCSE exam scores.

SAMPLE

The sample comprised 212 British schoolchildren. Of these, 123 were females. Their mean age was 15.8 years (SD 0.98 years).

METHOD

Pupils completed three self-report tests: the Neuroticism-Extroversion-Openness-Five-Factor Inventory (NEO-FFI) which measures the 'Big Five' personality traits, (Costa & McCrae, 1992); the Typical Intellectual Engagement Scale (Goff & Ackerman, 1992) and a measure of learning style, the Study Process Questionnaire (SPQ; Biggs, 1987). They also completed two ability tests: the Wonderlic Personnel Test (Wonderlic, 1992) a short measure of general intelligence and the General Knowledge Test (Irving, Cammock, & Lynn, 2001) a measure of crystallized intelligence. Six months later they took their (10th grade) GCSE exams comprising four 'core' compulsory exams as well as a number of specific elective subjects.

RESULTS

Correlational analysis suggested that intelligence was the best predictors of school results. Preference test measures accounted for relatively little variance. Regressions indicated that over 50% of the variance in school exams for English (Literature and Language) and Maths and Science combined could be accounted for by these individual difference factors.

CONCLUSIONS

Data from less than an hour's worth of testing pupils could predict school exam results 6 months later. These tests could, therefore, be used to reliably inform important decisions about how pupils are taught.

摘要

背景

能力(通过能力测试衡量)和非能力(通过偏好测试衡量)个体差异测量都可以预测学业成绩。这些包括流体智力和晶体智力、人格特质和学习风格。本文考察了五种心理测试和学生的性别和年龄对预测他们普通中等教育证书(GCSE)考试成绩的增量有效性。

目的

目的是确定能力和非能力测试在预测特定 GCSE 考试成绩方面可以解释多少方差。

样本

样本包括 212 名英国学童。其中 123 名为女性。他们的平均年龄为 15.8 岁(SD 0.98 岁)。

方法

学生完成了三个自我报告测试:神经质-外向性-开放性-五因素人格量表(NEO-FFI),用于测量“大五”人格特质(科斯塔和麦克雷,1992 年);典型智力投入量表(高夫和阿克曼,1992 年)和学习风格量表,学习过程问卷(SPQ;比格斯,1987 年)。他们还完成了两项能力测试: Wonderlic 人事测试(Wonderlic,1992 年),用于衡量一般智力;一般知识测试(欧文、卡莫克和林恩,2001 年),用于衡量晶体智力。六个月后,他们参加了(10 年级)GCSE 考试,包括四门“核心”必修考试以及一些特定的选修科目。

结果

相关分析表明,智力是学业成绩的最佳预测因素。偏好测试衡量的标准解释了相对较小的方差。回归分析表明,英语(文学和语言)和数学与科学相结合的学校考试成绩的 50%以上可以由这些个体差异因素来解释。

结论

不到一小时的测试数据可以预测 6 个月后的学校考试成绩。因此,这些测试可以用来可靠地告知如何教授学生的重要决策。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验