Individual difference characteristics and contextual factors affecting educational attainment
Notice bibliographique
Résumé
The studies in this dissertation examine cognitive and non-cognitive predictors of postsecondary educational attainment. While prior research has documented links between core cognitive abilities (e.g., processing speed, attention, fluid intelligence) and academic success, less is known about the mechanisms translating these abilities into outcomes. It also remains unclear how contextual disruptions, such as the COVID-19 pandemic impacted students’ psychosocial and academic functioning. The first study investigated the role of learning strategies, along with willingness to engage in effortful cognitive activity (Need for Cognition; NFC), as potential intermediaries between basic cognitive abilities and academic outcomes. Results showed that while standard cognitive measures did not directly predict academic performance, both NFC and model-based (goal-directed) learning strategies were significant positive predictors. Further analyses indicated that fluid intelligence and attention positively predicted NFC and model-based learning, suggesting that these abilities may facilitate the development of motivational and strategic traits that, in turn, promote academic success. These findings emphasize the importance of motivation and strategy use, even when direct associations with basic cognitive abilities are lacking. The second study complements the first by examining the broader socio-environmental challenges posed by the COVID-19 pandemic on Canadian university students, with a focus on understanding the impact of the pandemic on students’ mental health, social networks, SES, and educational attainment. Using longitudinal data collected before and during the pandemic, results revealed that while GPA slightly improved, psychosocial well-being deteriorated. Increases in substance use, smaller social networks, and reduced well-being were observed. Cross-sectional analyses further showed that greater substance use during the pandemic predicted poorer GPA, and students with pre-existing psychiatric conditions were particularly vulnerable to increased substance use. These findings suggest that students with mental health vulnerabilities may be disproportionately affected by crises, underscoring the need to address maladaptive coping to support academic success. Together, these studies highlight both individual (e.g., cognition, motivation, learning strategies) and contextual influences (e.g., pandemic disruptions) as important predictors of academic attainment. By considering internal and external factors, this dissertation provides a more comprehensive understanding of the multifaceted determinants of educational success, informing both theory and practice for optimizing university student outcomes.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».