Academic Performance and Behavioral Patterns

Identifying the factors that influence academic performance is an essential part of educational research. Previous studies have documented the importance of personality traits, class attendance, and social network structure. Because most of these analyses were based on a single behavioral aspect and/or small sample sizes, there is currently no quantification of the interplay of these factors. Here, we study the academic performance among a cohort of 538 undergraduate students forming a single, densely connected social network. Our work is based on data collected using smartphones, which the students used as their primary phones for two years. The availability of multi-channel data from a single population allows us to directly compare the explanatory power of individual and social characteristics. We find that the most informative indicators of performance are based on social ties and that network indicators result in better model performance than individual characteristics (including both personality and class attendance). We confirm earlier findings that class attendance is the most important predictor among individual characteristics. Finally, our results suggest the presence of strong homophily and/or peer effects among university students

Within-trait heterogeneity in age group differences in personality domains and facets:implications for the development and coherence of personality traits

The study investigated differences in the Five-Factor Model (FFM) domains and facets across adulthood. The main questions were whether personality scales reflected coherent units of trait development and thereby coherent personality traits more generally. These questions were addressed by testing if the components of the trait scales (items for facet scales and facets for domain scales) showed consistent age group differences. For this, measurement invariance (MI) framework was used. In a sample of 2,711 Estonians who had completed the NEO Personality Inventory 3 (NEO PI-3), more than half of the facet scales and one domain scale did not meet the criterion for weak MI (factor loading equality) across 12 age groups spanning ages from 18 to 91 years. Furthermore, none of the facet and domain scales met the criterion for strong MI (intercept equality), suggesting that items of the same facets and facets of the same domains varied in age group differences. When items were residualized for their respective facets, 46% of them had significant (p < 0.0002) residual age-correlations. When facets were residualized for their domain scores, a majority had significant (p < 0.002) residual age-correlations. For each domain, a series of latent factors were specified using random quarters of their items: scores of such latent factors varied notably (within domains) in correlations with age. We argue that manifestations of aetiologically coherent traits should show similar age group differences. Given this, the FFM domains and facets as embodied in the NEO PI-3 do not reflect aetiologically coherent traits

Personality traits and health-risk behaviours in university students

10.1002/per.736European Journal of Personality238675-69