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Enregistrement W7161937797 · doi:10.82308/46387

Individual instructor's perceptions of teaching context : identifying facilitators and barriers to completion of teaching projects

2001· dissertation· en· W7161937797 sur OpenAlexaboutno aff
Katherine. Moxness

Notice bibliographique

Revuenon disponible
Typedissertation
Langueen
DomaineSocial Sciences
ThématiqueEvaluation of Teaching Practices
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésLikert scaleContext (archaeology)PerceptionProfessional developmentHigher educationWork (physics)Scale (ratio)Faculty development

Résumé

récupéré en direct d'OpenAlex

Frameworks seeking to explain teaching competency and development in higher education indicate that context and personal perspectives, as well as knowledge and action are crucial components in the understanding of how and why faculty teach as they do and how development may be encouraged and may be supported. This study sought to contribute to a deeper understanding of individual instructors' perceptions of context of higher education as it related to their teaching projects. This study investigated the daily pursuits and pre-occupations (teaching goals/projects) of an individual instructor, specifically, the instructional demands, departmental demands, the personal and professional pursuits of knowledge and the pursuits of pedagogical knowledge. More specifically, this study investigated perceived facilitators and barriers to the realization of individual teaching and other work projects. Nineteen full-time faculty members in the Departments of Physiotherapy, Occupational therapy, Nursing, Social Work, Educational Psychology and Education at a large research and teaching university in Montreal, Quebec participated in this study. The instructors were asked to complete an adapted version of Little's (1983) Personal Project Analysis (P.P.A.) instrument, which is designed to elicit an instructor's current pre-occupations or projects in his or her current context. The instructors were asked to rate these projects (seven teaching projects and seven other work projects) using a Likert scale (0 to 10) on twenty-one empirically supported dimensions. These dimensions included the following: enjoyment, difficulty, control, initiative, stress, time pressure, outcome, self-identity, others' view, value congruency, challenge, commitment, competence, support, self-worth, fun, others' benefit, self-benefit, supportiveness of culture (departmental level), hindrance of culture (departmental level), and overall current satisfaction. Instructors were asked to assess their perceived conflicts between two of their teaching projects and two of their other work projects in addition to completing a demographic questionnaire. The findings indicate that instructors identified five different types of daily pursuits that formed and defined their teaching context, as they perceived it. These five types of daily pursuits (projects) included: course planning and preparation projects; student investment, support and delegation of tasks to student projects; knowledge building and knowledge sharing projects; committees, faculty support and faculty teaching projects; and finally, teaching strategy projects. The instructors also identified five different types of daily pursuits that formed and defined their other work context. These included: publishing, conference presentation and research projects; grant proposals and funding projects; office organization projects; correspondence, university committees, outside mandates, departmental expectations and management of student and faculty projects; and finally, personal objectives and technical skill building projects. P.P.A. enabled the researcher to identify on an individual instructor level the instructor's perceived facilitators and barriers to the successful completion of teaching and other work projects. Furthermore, P.P.A. as a faculty development instrument or as an alternative to semi-structured interview methods is supported by the findings.

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,006
score de la tête « metaresearch » (Gemma)0,011
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict), Études des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,098
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0060,011
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,107
Tête enseignante GPT0,441
Écart entre enseignants0,334 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2001
Routes d'admission1
Résumé présentoui

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