Title

The Relationship Between Personality, Self-Regulated Learning, and Personality

Date of Award

2014

Degree Type

Thesis

Degree Name

M.A.

Department

Psychology

First Advisor

Jackson, Dennis

Keywords

academic entitlement, individual differences, personality, self-regulated learning, self-regulation, the Big-Five

Rights

CC BY-NC-ND 4.0

Abstract

The current study explored the relation between the Big-Five personality domains, self-regulated learning, and academic entitlement. Academic entitlement is defined as the tendency to possess expectations of unearned academic success, unearned/undeserved academic services, and/or the expectation of unrealistic accommodation (Chowning & Campbell, 2009; Singleton-Jackson, Jackson, & Reinhardt, 2010). Academic entitlement is a pervasive problem in today's university environment, making it important to understand risk factors for academic entitlement. Previous research on academic entitlement has reported a relation between personality factors and academic entitlement (Chowning & Campbell, 2009), and between academic entitlement and self-regulated learning (Achacoso, 2002). These relations were explored in the current study. A relation between personality and academic entitlement that is mediated by self-regulated learning was also explored. Regression analysis suggested that self-regulated learning was negatively related to academic entitlement (p<0.10). In terms of personality, agreeableness was negatively related to academic entitlement (p<0.05) and extraversion was positively related to academic entitlement (p<0.05). Agreeableness (p<0.10), conscientiousness (p<0.05), and openness (p<0.05) were positively related to self-regulated learning. Neuroticism (p<0.05) was also positively related to academic entitlement, this finding was unexpected. Mediation analysis suggested that the relation between agreeableness, conscientiousness, neuroticism, and extraversion and academic entitlement is mediated by self-regulated learning. These findings are discussed and further explored using canonical correlation analysis.

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