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Record W2793793510 · doi:10.18438/eblip29379

Undergraduate Students Seek Librarian Assistance Only After They Have Searched Independently Without Success

2018· article· en· W2793793510 on OpenAlexvenueno aff
Elaine Sullo

Bibliographic record

VenueEvidence Based Library and Information Practice · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisMedical educationPsychologyQualitative researchCoding (social sciences)PerceptionMedicineSociology

Abstract

fetched live from OpenAlex

A Review of: Vinyard, M., Mullally, C., & Colvin, J.B. (2017). Why do students seek help in an age of DIY? Using a qualitative approach to look beyond statistics. Reference & User Services Quarterly, 56(4), 257-267. http://dx.doi.org/10.5860/rusq.56.4.257 Abstract Objective – To explore how undergraduate students look for information and the reasons these students seek assistance from a librarian. Design – Qualitative research. Setting – A university in Southern California. Subjects – 10 students were interviewed: 1 freshman, 1 sophomore, 5 juniors, and 3 seniors. Methods – Students who met with a librarian for longer than 20 minutes were invited to participate in the study, and interviews were conducted within six weeks of this interaction. Semi-structured interviews were scheduled for one hour blocks and were audio-recorded and transcribed afterward. Interview data was analyzed using applied thematic analysis. The researchers used NVivo to assist with the process of coding data. Main Results – Once all transcripts were coded, the researchers identified the following six themes related to how students look for information and the reasons they asked for assistance: how students research, personal perceptions of research skills, assumptions (students’ misperceptions about library services), motivation for asking for help, path to the librarian (how students contacted librarians and their reason for selecting a particular librarian), and experience working with a librarian. Conclusion – Overall, the research results demonstrate that students prefer to conduct research independently but will consult a librarian if they are not able to find what they need, if they find the research question especially challenging, or if they have spent an unreasonable amount of time conducting research. In-class library instruction, along with professor referrals are the most effective methods for encouraging students to seek out library assistance.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0040.002
Scholarly communication0.0060.005
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0300.016

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 head0.018
GPT teacher head0.324
Teacher spread0.306 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2018
Admission routes1
Has abstractyes

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