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Enregistrement W2808079121 · doi:10.18438/eblip29414

Undergraduate Students Can Provide Satisfactory Chat Reference Service in an Academic Library

2018· article· en· W2808079121 sur OpenAlexaffvenue
H. Robson MacDonald

Notice bibliographique

RevueEvidence Based Library and Information Practice · 2018
Typearticle
Langueen
DomaineComputer Science
ThématiqueWeb and Library Services
Établissements canadiensCarleton University
Organismes subventionnairesnon disponible
Mots-clésStaffingReference deskComputer sciencePsychologyMedical educationCourtesyCLARITYLibrary scienceMedicineNursing

Résumé

récupéré en direct d'OpenAlex

A Review of: Keyes, K., & Dworak, E. (2017). Staffing chat reference with undergraduate student assistants at an academic library: A standards-based assessment. Journal of Academic Librarianship, 43(6), 469–478. https://doi.org/10.1016/j.acalib.2017.09.001 Abstract Objective – To determine whether undergraduate students can provide quality chat reference service. Design – Content analysis of undergraduate student, professional librarian, and paraprofessional staff responses in chat reference transcripts. Setting – Academic library. Subjects – 451 chat reference transcripts. Methods – Chat reference transcripts from May 2014–September 2016 were collected. Five categories of answerer were coded: librarian in the reference department (LibR), librarian from another department (LibNR), staff without a Master of Library Science (staff), staff with a Master of Library Science (+staff), and student employee (student). A random sample of 15% of each category of answerer was selected for analysis. The answerer categories were collapsed to librarians, staff, and students for the results section. Four criteria were used to code chat reference transcripts: difficulty of query, answerer behaviour, problems with transcript answer, and comments from coders. Coding for difficulty was based on the READ scale (Reference Effort Assessment Data). Answerer behaviour was based on The RUSA Guidelines (Reference and User Services Association). Behaviours assessed included: clarity, courtesy, grammar, greeting, instruction, referral, searching, sign off, sources, and whether patrons were asked if their question was answered. All coding was done independently between the two researchers, with very good interrater reliability. Data for variables with disagreement were removed from the analysis. The chi-square test was used to analyze the association between variables. Analysis also included patrons’ ratings and comments about their chat experience. Content and tone were assessed for each patron comment. Main Results – Answerer behaviours showed a significant difference between groups for 3 of the 10 behaviours assessed: courtesy (p=0.031), grammar (p=0.001), and sources (0.041). The difference between groups for courtesy was: staff (88%), librarians (76%), and students (73%). Grammar was correct in most transcripts, but there was a significant difference between the answerer groups: librarians (98%), staff (90%), and students (73%). There was a significant difference between groups that offered sources: librarians (63.8%), staff (62.5%), and students (43.8%). There was no significant difference between the answerer groups for the other seven behaviours. Overall, 31% of transcripts showed that answerers asked if a patron’s query was answered or if they needed further help. The analysis showed that 79% of transcripts were coded as clear or free of jargon. Greetings were found in 65% of transcripts. Instruction was indicated in 59% of transcripts. Referrals were offered in 27% of all transcripts. Of the transcripts where searching was deemed necessary, 82% showed evidence of searching. A sign off was present in 56% of all transcripts. Transcripts with noted problems were deemed so because of lack of effort, being incomplete or incorrect, having no reference interview, or the answerer should have asked for help. There was no significant difference between answerer groups with respect to problem questions. Of the 24% of patrons who rated their chat experience, 90% rated it as good or great, and no significant difference was found between answerer groups. Question difficulty was coded 50% at level 0-2 (easier), 39% at level 3 (medium difficulty), and 11% at level 4-5 (more difficult). Conclusion – Undergraduate students are capable of providing chat reference that is similar in quality to that of librarians and staff. However, increased training is needed for students in the areas of referrals, providing sources, and signing off. Students do better than librarians and staff with greetings and are more courteous than librarians. There is room for improvement for staff and librarians offering chat services. Tiered chat reference service using undergraduates is a viable option.

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)0,010
score de la tête « metaresearch » (Gemma)0,072
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 enseignants0,012
Score d'incertitude au seuil0,051

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0100,072
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0020,001
Communication savante0,0050,003
Science ouverte0,0010,005
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0120,006

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 Opus0,024
Tête enseignante GPT0,284
Écart entre enseignants0,259 · 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

Citations5
Publié2018
Routes d'admission2
Résumé présentoui

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