Insights From Predictors of Faculty Success: A Mixed Methods Study
Notice bibliographique
Résumé
Abstract The purpose of this study was to explore the predictors of faculty success. The study was underpinned by the philosophy of pragmatism because the researcher sought to solve perceived real-world challenges in the post-secondary education sector related to faculty success and performance. Those real-world challenges in the post-secondary sector include increased public scrutiny of their productivity, reduced public funding, and concerns regarding professorial interface, efficacy and discourse around faculty accountability. Using both qualitative and quantitative methods of inquiry, a mixed methods approach guided this research. Scales such as the teacher collegiality scale (TCS), developed by Mediha Shah (2011), and organizational commitment and work satisfaction scales (Meyer et al., 1993; Stride, Wall, & Catley, 2007) were adapted for the study and administered to academics. For the purposes of this study the terms academic and faculty were used interchangeably. An academic refers to those members of staff who deliver various combinations of the following services: teaching, research, and service in post-secondary institutions. Interpretation panel sessions were conducted with academics at the University of Saskatchewan, the site for this study. Higher education institutions operate in a highly competitive and globalized environment, and this results in a great emphasis on faculty performance. Hemsley-Brown and Goonawardana (2007) corroborated this claim, asserting that post-secondary institutions (PSIs) operating in today’s competitive and internationalized landscape incessantly compete for international students (and faculty) to remain competitive in the face of declining government funding and government-supported recruitment campaigns (p. 3) in the case of public institutions. Therefore, faculty success and its drivers have become focal points and place faculty members in roles as key agents of performance within these institutions. Past studies have suggested that collegiality may be a driver of performance; therefore, studying faculty collegiality and other possible drivers of success were thought to be prospective means to reveal insights into the determinants of faculty success and to offer practical solutions for post-secondary institutions. This study revealed associations between the dependent variable, faculty success and the independent variables, collegiality, work engagement, resilience, work satisfaction, organizational commitment, and trust. However, the study indicated that only the variables collegiality, work engagement, and resilience predicted faculty success. Comparative analyses were also conducted on the data to explore faculty success across various demographic variables. Significant differences were identified in faculty success across tenure. There was 95% confidence reached that there were statistically significant differences in faculty success across tenure at the U of S (F(5, 183) = 2.808, p =. 018 as determined by the one-way ANOVA test. A Tukey post hoc test also revealed that faculty members in their posts between 6-10 years were more successful than those in their jobs between 11-15 years (p = .009), suggesting that early career faculty members were more successful than mid-career faculty members.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,033 | 0,031 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,004 | 0,002 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».