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Enregistrement W2729717268 · doi:10.18438/b85370

Implementation of Proactive Chat Increases Number and Complexity of Reference Questions

2017· article· en· W2729717268 sur OpenAlexvenueno aff
Sue F. Phelps

Notice bibliographique

RevueEvidence Based Library and Information Practice · 2017
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueLibrary Science and Information Literacy
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésStaffingReference deskComputer scienceService (business)Service deskPoint (geometry)World Wide WebCategorizationEmpirical researchPsychologyMedicineService delivery frameworkService designStatisticsArtificial intelligenceNursingMathematics

Résumé

récupéré en direct d'OpenAlex

A Review of: Maloney, K., & Kemp, J. H. (2015). Changes in reference question complexity following the implementation of a proactive chat system: Implications for practice. College & Research Libraries, 76(7), 959-974. http://dx.doi.org/10.5860/crl.76.7.959 Abstract Objective – To determine whether the complexity of reference questions has changed over time; whether chat reference questions are more complex than those at the reference desk; and whether proactive chat increases the number and complexity of questions. Design – Literature review and library data analysis. Setting – Library of a doctoral degree granting university in the United States of America. Methods – The study was carried out in two parts. The first was a meta-analysis of published data with empirical findings about the complexity of questions received at library service points in relationship to staffing levels. The authors used seven studies published between 1977 and 2012 from their literature review to create a matrix to compare reference questions based on the staffing level required to answer the questions (e.g., by a nonprofessional, a generalist, or a librarian). They present these articles in chronological order to illustrate how questions have changed over time. They sorted questions by the service point at which they were asked, either through chat service or at a reference desk. In the second part of the study authors used the READ scale to categorize the complexity of questions asked at the reference desk and via proactive chat reference. They collected data for chat reference for six one-week periods over the course of eight months to provide a representative sample. They recorded reference desk questions for three of those same weeks. Both evaluators scored the data for a single week to norm their results, while the remaining data was coded independently. Main Results – The complexity of questions in the seven articles studied indicated change over time, shown in tables for desk and chat reference. One outlier, a study published in 1977 before reference tools and resources moved online, reported that 62% of questions asked could be answered by nonprofessionals, 38% by a trained generalist, and only 6% required a librarian. The six other studies were published after 2001 when most resources had moved online. Of the questions from these six, authors found a range of 74-90% could be answered by a non-professional, 12-16% by a generalist, and 0-11% required a librarian. Once chat reference was added there was more variation reported between studies, with generalist questions at 30-47% of those reported and 10-23% requiring a librarian. Though the underlying differences in the study designs do not allow for formal analysis, the seven studies indicate that more complex questions are asked via chat service than at the reference desk. Each staffing level was grouped and averaged for comparison. The 1977 study shows nonprofessional questions at 62%, generalist questions at 32%, and librarian questions at 6%. Reference desk questions in the post-2001 articles indicated 81% nonprofessional, 13% generalist, and 5% librarian questions. Post-2001 chat questions were at 49% nonprofessional, 36% generalist, and 15% at librarian level. In the second part of the study, the data coded using the READ scale and collected from the proactive chat system showed an increased number and complexity of questions. The authors identified 4% of questions were rated at a level 1 (e.g., directional, library hours), 30% at level 2 (e.g., known item searching), 39% at level 3 (e.g., reference questions), and 27% at level 4 requiring advanced expertise (e.g., using specialized databases or data sets). Authors combined questions at levels 5 and 6 due to low numbers, and did not describe these when reporting their study. In comparison, 15% of reference desk questions were at a level 3 on the READ scale, and 1% were at level 4. Conclusion – Proactive chat reference service increased the number and the complexity of questions over those received via the reference desk. The frequency of complex questions was too high for nonprofessional staff to refer questions to librarians, causing reevaluation of the tiered service model. Further, this study demonstrates that users still have questions about research, but for users to access services for these questions “reference service must be proactive, convenient, and expert to meet user expectations and research needs” (p. 972).

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)0,065
score de la tête « metaresearch » (Gemma)0,281
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,065
Score d'incertitude au seuil0,342

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0650,281
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,004
Bibliométrie0,0060,005
Études des sciences et des technologies0,0010,001
Communication savante0,0050,007
Science ouverte0,0020,003
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0060,001

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 Opus0,062
Tête enseignante GPT0,376
Écart entre enseignants0,314 · 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'étudeObservationnel
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
Publié2017
Routes d'admission1
Résumé présentoui

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