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Record W2808079121 · doi:10.18438/eblip29414

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

2018· article· en· W2808079121 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueEvidence Based Library and Information Practice · 2018
Typearticle
Languageen
FieldComputer Science
TopicWeb and Library Services
Canadian institutionsCarleton University
Fundersnot available
KeywordsStaffingReference deskComputer sciencePsychologyMedical educationCourtesyCLARITYLibrary scienceMedicineNursing

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.732
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0020.584
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.284
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it