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

机译:典型的智力投入,五种人格特质,学习方法和学习成绩的认知预测指标

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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 dWonderlic 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.
机译:背景。能力(通过能力测验衡量)和非能力(通过偏好测验衡量)个人差异衡量都可以预测学院的学习成绩。这些包括流动性和结晶性智力,人格特质和学习风格。本文研究了五项心理测验的递增有效性以及学生的性别和年龄,以预测其中学普通教育证书(GCSE)的考试结果。目的目的是确定在预测特定的GCSE考试成绩时,差异能力和非能力测试可占多少。样品。样本包括212名英国学童。其中,123名是女性。他们的平均年龄为15.8岁(标准差为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-五因素量表(NEO-FFI),用于测量“大五人”的人格特质(Costa&McCrae,1992);典型的智力投入量表(Goff&Ackerman,1992)和学习方式的量度,研究过程问卷(SPQ; Biggs,1987)。他们还完成了两项能力测试:dWonderlic人员测试(Wonderlic,1992)是对通用智力的简短度量,而通用知识测试(Irving,Cammock和Lynn,2001)是对结晶智能的度量。六个月后,他们参加了(10年级)GCSE考试,其中包括四门“核心”强制性考试以及一些特定的选修科目。结果。相关分析表明,智力是学校成绩的最佳预测指标。偏好测试方法所占的差异相对较小。回归表明,英语(文学和语言)以及数学和科学相结合的学校考试中超过50%的差异可以由这些个体差异因素来解释。结论来自不到一个小时的测试学生的数据可以预测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有关如何教学生的重要决定。

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