Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Background: Engagement with school is a key predictor of students' academic outcomes, yet little is known about its association with personality. No research has considered this association using Cloninger's biopsychosocial model of personality. This model may be particularly informative because it posits the structure of human personality corresponds to three systems of human learning and memory that regulate associative conditioning, intentionality, and self-awareness, all of which are relevant for understanding engagement.
Aims: To test for defined personality phenotypes and describe how they relate to student engagement.
Sample: 469 adolescents (54.2% female) attending the eighth (M = 13.2, SD = .57) or 11 (M = 16.5, SD = .84) grades.
Methods: Students completed self-report measures of personality and engagement. We used mixture models to identify latent classes defined by common (1) temperament profiles, (2) character profiles, and (3) joint temperament-character networks, and then tested how these classes differed in engagement.
Results: Latent class analysis revealed three distinct joint temperament-character networks: Emotional-Unreliable (emotionally reactive, low self-control, and low creativity), Organized-Reliable (self-control but not creative), and Creative-Reliable (highly creative and prosocial). These networks differed significantly in engagement, with the emotional-unreliable network linked to lower engagement. However, the magnitudes of these differences across engagement dimensions did not appear to be uniform.
Conclusions: Different integrated configurations of the biopsychosocial systems for associative conditioning, intentionality, and self-awareness (differences in personality) underlie student engagement. Our results offer a fine-grained understanding of engagement dimensions in terms of their underlying personality networks, with implications for educational policies and practices.
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http://dx.doi.org/10.1111/bjep.12388 | DOI Listing |
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