NotesFAQContact Us
Search Tips
Peer reviewed Peer reviewed
Direct linkDirect link
ERIC Number: EJ1197004
Record Type: Journal
Publication Date: 2018-Dec
Pages: 21
Abstractor: As Provided
ISSN: ISSN-0162-3532
Intelligence, Educational and Learning Capital, and Domain Impact Level of Activities as Predictors of School Achievement
Harder, Bettina; O'Reilly, Colm; Debatin, Tobias
Journal for the Education of the Gifted, v41 n4 p327-347 Dec 2018
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.
SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail:; Web site:
Publication Type: Journal Articles; Reports - Research
Education Level: Grade 4; Intermediate Grades; Elementary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Germany
Identifiers - Assessments and Surveys: Raven Progressive Matrices
Grant or Contract Numbers: N/A