While narcissism is typically presented as an unwelcome trait, there may be aspects of narcissism that foster positive educational outcomes. A study published in the journal Learning and Individual Differences found that university students with higher narcissism had higher mental toughness and in turn, used more adaptive learning strategies when studying.
Personality scientists continue to explore the Dark Triad traits, yet little research has considered how these traits might relate to educational outcomes. The dark traits, a cluster of subclinical anti-social personality traits, include narcissism, psychopathy, and Machiavellianism.
Study authors Andrew Denovan and his team theorized that these personality traits might influence a person’s approach to learning. For example, people who are high in grandiose narcissism tend to strive to outperform others, which may encourage goal pursuit and a deeper approach to learning. The researchers also proposed that the link between dark traits and learning styles might be influenced by a third variable — mental toughness, which describes the ability to cope and perform well when facing stress.
With these hypotheses in mind, the researchers conducted a longitudinal study to explore how dark personality traits indirectly influence learning styles through mental toughness. Undergraduate students from a university in the UK responded to questionnaires at two different time points — at the start of the academic year, and at the beginning of the second term (around three months later). A total of 100 students completed both surveys.
The questionnaires included assessments of depressive symptoms, mental toughness, and approach to studying (strategic, deep, or surface learning). The surveys also included measures of the three dark traits. This included subclinical grandiose narcissism (defined by exaggerated self-importance, dominance, and high self-confidence), Machiavellianism (defined by self-interest and manipulative behavior), and subclinical psychopathy (characterized by anti-social behavior and a lack of empathy).
As the study authors report, the only dark trait that was tied to beneficial outcomes was narcissism. At both the first and second time points, narcissism was positively related to deep learning and negatively related to depression. At Time 2, narcissism was positively related to strategic learning and negatively related to surface learning.
As hypothesized, mental toughness mediated the associations between narcissism and depression, narcissism and strategic learning, and narcissism and surface learning. Mental toughness did not, however, mediate the association between narcissism and deep learning.
Denovan and his colleagues note that these findings suggest that there are favorable aspects of grandiose narcissism, such as lower depression and positive learning styles. “It appears that the ability of grandiose narcissists to commit confidently to a target, by virtue of the association with mental toughness, offers the opportunity to focus and plan their learning accordingly,” the researchers say. Narcissists are likely driven toward strategic learning through their desire to earn the best grades and outshine others. This adaptive learning strategy is then facilitated by higher mental toughness, which bolsters commitment and persistence.
Of note, higher psychopathy was negatively associated with strategic learning at both time points and positively associated with surface learning at the start of term. This suggests that people with high levels of psychopathy tend to prefer impromptu, surface-level learning strategies that quickly enhance educational performance, as opposed to a deeper approach.
The researchers say that their study was limited in that it did not include objective achievement measures, such as school grades. Future studies might include such measures to assess whether adaptive learning styles would predict better educational performance.
The study, “Dark Triad traits, learning styles, and symptoms of depression: Assessing the contribution of mental toughness longitudinally”, was authored by Andrew Denovan, Neil Dagnall, Elena Artamonova, and Kostas A. Papageorgiou.
