Assessment in the Era of Neoliberalism: Examining the Value and Institutionalization of Student Learning Outcomes Assessment at the University of Redlands, School of Business and Society
Notice bibliographique
Résumé
In this qualitative case study, I explore, from a scholar’s point of view, the student learning outcome (SLO) assessment processes at the University of Redlands, School of Business & Society (School). I examine the degree to which the SLO assessment processes at the School have been institutionalized at the School, the value of SLO assessment to the various stakeholders, and the limitations of SLO assessment as they relate to improving learning outcomes. This study is evaluated through the theoretical lens of Neoliberalism. I utilized the case study research methodology because it is “an empirical inquiry that investigates a contemporary phenomenon (the ‘case’) in depth and within its real-world context” (Yin, 2015, p.16). I conducted semi-structured interviews with over 20 participants, including faculty, nontenured faculty, students, alumni, and administrators. My study reveals that while the institutionalized SLO assessment regime is firmly in place at the School, it is undervalued and not being used to continuously improve student learning outcomes. This is due, in part, to the influence of Neoliberal policies and practices that enable the School to meet its institutional need of satisfying accreditors but which do not meet the needs of other stakeholders, such as the nontenured faculty and the students. By adhering to accreditation guidelines, the faculty and administration have employed an overly structured assessment regime that is not transparent to nontenured faculty, students, or the greater community. Leadership at the School ought to seize the opportunity to review and reset the SLO processes as soon as possible to break the grip of Neoliberalism and institute a more wholistic view of student education that is focused on continuous quality improvement. Dedication To my fiancée Karen, her mother “Dottie,” and her brother Craig, for their unconditional love and unwavering support throughout this project. To my family in Nova Scotia, Canada, my parents and grandparents, my brother, Stephen, his wife MaryEllen, Peter, Casey, and their families. To my aunt Shirley, my uncle Earl, and to my cousins, Dixie, David and his wife Kim, and Rodney. I am so proud to be able to dedicate this work to all of you.
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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 | 0,005 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».