Library Impact on Student Retention is Often Not Well Documented or Communicated
Notice bibliographique
Résumé
A Review of: Murray, A. L., & Ireland, A. P. (2017). Communicating library impact on retention: A framework for developing reciprocal value propositions. Journal of Library Administration, 57(3), 311-326. http://www.tandfonline.com/doi/full/10.1080/01930826.2016.1243425 Abstract Objective – Identification of trends in documenting and communicating library impact on student retention. Presentation of a framework of library stakeholders with examples of how libraries can communicate their value to each stakeholder group. Design – Survey and presentation of framework. Setting – Comprehensive universities in the USA. Subjects – 68 Academic library deans/directors. Methods – A survey on current methods of documenting and communicating library impact on student retention was sent to all 271 comprehensive universities with a Carnegie classification of Master’s level. The response rate was 25%. Emergent themes were identified using NVIVO for the qualitative data analysis. The six markets model was presented as a framework for identifying library stakeholder groups. Examples of reciprocal value propositions (RVP) for each stakeholder group were provided. Main Results – Analysis of the survey results identified a number of themes about documenting library impact on student retention: use of information literacy assessment, use of satisfaction or feedback instruments (eg: survey, focus group), library-use data, and lack of knowledge of methods. Several responses indicated the methods used for information literacy assessment were not a direct measure for documenting impact on retention. A few institutions piloted more direct methods by combining library use data and student success metrics. A number of institutions said they struggled with how to use library-use data to calculate library impact on retention. Methods for communicating library impact on retention included formal presentations, annual reports, annual assessment reports, informal communication, and none. Communication was often tied to documentation; if a library did not collect or document impact on retention, they were not able to communicate anything. The authors noted communication tended to be unidirectional rather than being a multidirectional discussion between the library and its stakeholders. Based on the six markets model, the authors identified six library stakeholder groups that would benefit from understanding library impact on student retention. The authors postulated that identifying these markets would allow the library to define value propositions for each market. The value propositions for each market would be reciprocal because value would be co-created when the library engages with each stakeholder group to fill a service need. The authors proposed that identifying and engaging with stakeholders, and defining reciprocal value propositions for each, would provide the library with an opportunity to advocate for itself.
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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 | 0,023 | 0,089 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,005 | 0,007 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,009 | 0,007 |
| Science ouverte | 0,002 | 0,007 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,025 | 0,005 |
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 ».