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ERIC Number: EJ1180721
Record Type: Journal
Publication Date: 2015-Dec
Pages: 9
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0119-5646
EISSN: N/A
Demographic Factors, Personality, and Ability as Predictors of Learning Approaches
Xie, Qiuzhi; Zhang, Li-fang
Asia-Pacific Education Researcher, v24 n4 p569-577 Dec 2015
This study investigated the extent to which learning approaches can be accounted for by personal factors (i.e., demographics, ability, and personality). The participants were 443 students in a university in mainland China. The Revised Two-factor Study Process Questionnaire, the NEO Five-Factor Inventory-3, and the short form of Raven's Advanced Progress Matrices were respectively applied to test students' learning approaches, personality, and ability. The results of correlations and structural equation modeling indicated that male students were more likely to be deep learners than female students; relative to Year-one students, Year-three students were more likely to use the surface learning approach and less likely to use the deep learning approach. Openness to experience and conscientiousness had strong positive effects on the deep learning approach. Neuroticism had positive effect, whereas conscientiousness had negative effect on the surface learning approach. Approximately 44 % of the variance in the deep learning approach and approximately 18 % of the variance in the surface learning approach could be explained by the three personal factors. Personality was the strongest predictor of learning approaches, whereas ability was the weakest predictor. The implications of the results were discussed.
Springer. Available from: Springer Nature. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: customerservice@springernature.com; Web site: https://bibliotheek.ehb.be:2123/
Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: China
Identifiers - Assessments and Surveys: Raven Advanced Progressive Matrices; NEO Five Factor Inventory
Grant or Contract Numbers: N/A