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Enregistrement W1843805889 · doi:10.47678/cjhe.v44i2.185896

Book review of "Using quality benchmarks for assessing and developing undergraduate programs"

2014· article· en· W1843805889 sur OpenAlexvenueno aff
Jovan Groen

Notice bibliographique

RevueCanadian Journal of Higher Education · 2014
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueHigher Education Governance and Development
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésAccountabilityContext (archaeology)Process (computing)Quality (philosophy)Task (project management)Quality assuranceBest practiceHigher educationComputer scienceMedical educationProcess managementManagementPolitical scienceEngineeringMedicineOperations managementExternal quality assessment

Résumé

récupéré en direct d'OpenAlex

Dunn, D. S., McCarthy, M. A., Baker, S.C., & Halonen, J. S. (2011). Using quality benchmarks for assessing and developing undergraduate programs. San Francisco, CA: Jossey-Bass. Pages: 384. Price: $54.00 CDN (hardcover). ISBN 978-0-470-40556-7Although higher education has been grappling with accountability and assessment for decades, few topics produce such strong reactions among faculty and administrators as the need for a formal assessment structure and (p.46).With the recent push on quality assurance, this book explores in a very timely fashion the aims, strengths and barriers of program assessment and extends to the examination of key factors to consider in the context of such an assessment. To make the task of assessing an entire program of study more feasible, the authors divide the seemingly overwhelming task into eight components, making the assessment process more manageable, efficient and relevant. This is important if faculty members are to adopt a continuous and progressive outlook to assessment, rather than simply see the process as a sporadic exercise, undertaken solely out of necessity.The book is structured in two parts: the first part outlines a framework of eight key program domains which characterize the health of academic programs; the second part examines the practice of assessing the key program domains in different contexts and disciplines.Each of the key program domains in the first part of the book is the feature of its own chapter and speaks to the most engaging issues in the field. The first few chapters outline the role and impact of program leadership, overcoming faculty resistance to assessment and developing a sustainable assessment culture, program level learning outcomes as a blueprint for curriculum and useful criteria to evaluate effective curriculum design. The last few chapters describe the role of student development beyond intellectual training, the evaluation of faculty characteristics and contributions, how to use program assessment results to make a case for additional resources and a framework for characterizing administrative support.Each chapter contains an easy to read benchmark table with a list of attributes for which four progressive performance descriptors are outlined (underdeveloped, developing, effective, and distinguished). Descriptors for each attribute are subsequently explained and, often colourfully, illustrated by examples pulled from the considerable collective program assessment and development experience of the authors. This certainly aids in grounding the attributes and making more evident the spectrum of potential program realities. Authors are cautious to mention that benchmarks are not one size fits all. Seemingly designed with a larger research intensive university in mind, the benchmark tables are flexible and adaptable based on context. Each chapter concludes with a series of guiding questions which serve as catalyst for reflection on performance patterns in the context of each key program domain. The chapters in the second part of the book examine the use of the benchmarks in disciplines with largely differing outlooks on program assessment. Chapter 10 looks at benchmarking quality in the arts, humanities and interdisciplinary programs and chapter 11 investigates the same theme in the natural sciences. Chapters 12 and 13 conclude with an in-depth explanation of how to conduct a program self-study and practical tips.A valuable feature that makes this book a practical resource is that most chapters can easily stand alone. This is useful for a potential faculty member or reviewer who might be interested in a specific component of a review, be it program level learning outcomes or the examination of program resources, instead of having to read the book in its entirety.Other notable strengths include a description of assessment as having a formative purpose. The book emphasizes that the program assessment exercise is truly about program enhancement. …

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,005
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Synthèse · Signal consensuel: aucune
Score de désaccord entre enseignants0,045
Score d'incertitude au seuil0,150

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,005
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0030,004
Études des sciences et des technologies0,0010,001
Communication savante0,0040,003
Science ouverte0,0010,001
Intégrité de la recherche0,0010,003
Charge utile insuffisante (le modèle a refusé de juger)0,0450,029

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 Opus0,046
Tête enseignante GPT0,399
Écart entre enseignants0,352 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreSynthèse

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
Publié2014
Routes d'admission1
Résumé présentoui

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