Exploring the possible negative effects of self-efficacy upon performance
Notice bibliographique
Résumé
The thesis contains five chapters (including three empirical chapters), which attempt \nto further our knowledge of the reciprocal relationship between self-efficacy and \nperformance. The thesis attempts to answer questions related to the possible negative effects \nthat self-efficacy can have on subsequent performance by considering the limitations of \nprevious research (e.g., Bandura & Lock, 2003; Vancouver, Thompson, Tischner, & Putka, \n2002; Vancouver, Thompson, & Williams, 2001). \nChapter 1 provides a general conceptual overview of the self-confidence and selfefficacy \nliterature, the majority of which has typically supported the positive relationship \nbetween efficacy beliefs and performance in a range of settings. The chapter then provides a \ndetailed review of how and when self-efficacy may be negatively related to subsequent \nperformance. Finally, the limitations and future directions that are offered form the basis of \nthe ensuing three empirical chapters. \nChapter 2 addresses the limitation that previous tests of the reciprocal relationship \nbetween self-efficacy and performance tend to be of short duration (i.e., approx. 8–10 trials). \nThis short duration may limit the mastery experiences that are an important source of selfefficacy \nbeliefs. This chapter explores the reciprocal relationship between self-efficacy and \nperformance in a longitudinal golf putting study where participants complete 40 trials of 20 \nputts each (800 putts in total). The results supported the positive effects of self-efficacy on \nperformance in only one of the four putting sessions, where self-efficacy had a significant \nalbeit weak positive reciprocal relationship with putting performance. \nChapter 3 explores the criticism that mundane tasks (or tasks that remain static \nthroughout testing) generally do not vary or intrude on attentional focus (Bandura & Locke, \n2003). Two studies were conducted to examine the reciprocal relationship between selfefficacy \nand performance using a complex task (car racing simulation). Participants were required to learn to race on a difficult computer racing track across trials where performance \nwas assessed in relation to improvement on the preceding lap time (Study 1) and in relation to \na baseline time (Study 2). The results supported the positive reciprocal effects of self-efficacy \non performance over time (Bandura, 1997). \nChapter 4 reports a golf putting study which examined the effects of feedback on the \nreciprocal relationship between self-efficacy and performance. Previous tests of the \nreciprocal relationship between self-efficacy and performance tend to ignore previous \nperformances in the measurement of self-efficacy. Consequently, important information \nregarding previous performances may be ignored. The current test provides a performance \ndiary where participants have access to all previous performance results, upon which they can \nbase their subsequent self-efficacy beliefs. Again, support was shown for the positive \nreciprocal effects of self-efficacy on performance (Bandura, 1997). \nChapter 5 provides a summary and integrated discussion of these findings. \nFurthermore, methodological and conceptual limitations, implications, and future research \ndirections for the study of the reciprocal relationship between self-efficacy and performance \nare discussed.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».