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Enregistrement W4320894712 · doi:10.4300/jgme-d-22-00397.1

Program Evaluation Use in Graduate Medical Education

2023· article· en· W4320894712 sur OpenAlexafffund
Katherine Moreau, Kaylee Eady

Notice bibliographique

RevueJournal of Graduate Medical Education · 2023
Typearticle
Langueen
DomaineDecision Sciences
ThématiqueEvaluation and Performance Assessment
Établissements canadiensUniversity of Ottawa
Organismes subventionnairesUniversity of Ottawa
Mots-clésTimelineProcess (computing)PublicationCurriculumMedical educationProgram evaluationGraduate medical educationComputer sciencePsychologyAccreditationMedicinePolitical sciencePedagogy

Résumé

récupéré en direct d'OpenAlex

It is common to complete evaluations of graduate medical education (GME) programs, present them at conferences, publish them in peer-reviewed journals, add them to curricula vitae (CVs), and then move on without using them to enact changes in the programs themselves. Such actions may reflect the reality that many individuals perceive and conduct program evaluations as if they were research.1 While research and program evaluation use similar methods, they have distinct purposes, timelines, audiences, and most notably, intended uses.2 Evaluations of GME programs need to be used to, for example, inform program decisions and modifications, grow program stakeholders' knowledge, stimulate organizational culture changes, or improve the quality of training.1,3,4 They need to be more than intellectual exercises resulting in accomplishments listed on CVs.5 As such, we emphasize that evaluation use is an essential consequence of program evaluation. Those involved in program evaluation should discuss it and maintain its prominence at the onset of every evaluation. We also promote the adage “use-it-or-lose-it” to stress timely program evaluation use. Yet the literature on program evaluation in GME often neglects to discuss use, including how selected evaluation approaches can influence evaluation use.1,6,7 In this article, we explain evaluation use by describing both the use of evaluation findings and process use (ie, changes resulting from engagement in the evaluation process itself).1,8 We also suggest strategies, including evaluation approaches, that faculty can use to increase evaluation use in GME.The 3 categories of use of evaluation findings are instrumental, conceptual, and symbolic. Instrumental use refers to instances where stakeholders use evaluation findings to take direct actions (eg, improvements, changes, terminations) in a program.9 For example, evaluation findings show that residents in a GME program are struggling to complete their research projects. Using the findings, the GME team implements new research training activities to assist residents in the completion of their projects. Conceptual use describes occurrences where stakeholders use evaluation findings to evolve their understandings of a program but do not take direct actions based on these findings.4 For instance, the GME team acknowledges the findings that residents are struggling to complete their research projects. These findings inform their understanding of why residents are not attending academic conferences to present their research. Lastly, symbolic use occurs when stakeholders use the sheer existence of a completed evaluation to comply with reporting requirements or justify a previously made program action.4 For example, the funding university requires the GME program to complete an evaluation to retain funding for residents' research projects. The GME team completes an evaluation and presents the report to the university. Alternatively, before the evaluation, the GME program hired a research assistant to help residents with their research projects and the subsequent evaluation findings are used to justify the hiring of the research assistant. In GME, we emphasize instrumental use, as this form of use leads to actions that can improve programs. However, the use of evaluation findings is typically a short-term consequence of evaluation because these findings are relevant only within a specific and limited timeframe (ie, use-it-or-lose it).On the other hand, process use can have ongoing influence on individuals, programs, and organizations. It recognizes that evaluation processes themselves can affect attitudes, thought processes, and behaviors.10 Process use recognizes stakeholders' learning advancements from their involvement in an evaluation as well as the effects of evaluation processes on program functioning and organizational culture.11 Process use does not require changes to a program or direct actions because of evaluation findings. There are 6 types of process use which we illustrate with examples:When stakeholders are involved in evaluation processes, they enter an evaluation culture and learn how to think and look at things through an evaluative lens. They can also use the knowledge and skills (eg, evaluation knowledge, methodological and facilitation skills) they develop to strengthen their organization's abilities to design, implement, interpret, and use evaluations and thereby build their organization's evaluation capacity. In this sense, process use is valuable throughout and following an evaluation and in various GME settings regardless of the evaluation findings or recommendations.12The Table presents strategies that faculty involved in program evaluation can employ to increase evaluation use.In closing, it is imperative to remember that evaluation use, especially process use, can occur throughout a program evaluation rather than simply at its conclusion.10 Evaluation use can start at the planning stage and continue well beyond a presentation or publication of an evaluation. Program evaluators need a use-it-or-lose-it perspective throughout the evaluation process to maximize improvements to training. This perspective will maintain stakeholders' faith in the value of evaluation, as they witness that evaluation efforts lead to timely, actionable findings and processes. Ultimately, we must embrace evaluation use to ensure that all stakeholders and programs, not only conference attendees, readers of peer-reviewed journals, or our CVs, witness the consequences (both positive and negative) of program evaluation.

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)0,039
score de la tête « metaresearch » (Gemma)0,073
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesMétarecherche
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Autre devis · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,853
Score d'incertitude au seuil0,998

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0390,073
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0020,003
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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.

Tête enseignante Opus0,534
Tête enseignante GPT0,616
Écart entre enseignants0,082 · 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeAutre devis
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

Citations10
Publié2023
Routes d'admission2
Résumé présentoui

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