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Record W2162176319 · doi:10.18438/b8c32z

Undergraduate Students Still Experience Difficulty Interpreting Library of Congress Call Numbers

2013· article· en· W2162176319 on OpenAlexvenueno aff
Michelle Dalton

Bibliographic record

VenueEvidence Based Library and Information Practice · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsSnowball samplingTest (biology)Mathematics educationTask (project management)Sample (material)Index (typography)Computer sciencePsychologyMedical educationStatisticsWorld Wide WebMathematicsMedicineEngineering

Abstract

fetched live from OpenAlex

Objective – To explore how undergraduate students interpret Library of Congress call numbers when trying to locate books. Design – Multiple case study. Setting – A public, residential university in Illinois, United States of America. Subjects – 11 undergraduate students (10 upper division, 1 freshman; no transfer students included). Methods – A qualitative approach was adopted, with a multiple case study design used to facilitate the collection of data from several sources. Students were recruited for the study via convenience and snowball sampling. Participants who volunteered were interviewed and requested to complete a task that required them to organize eight call numbers written on index cards in the correct order. Interviewees were also asked about any instruction they had received on interpreting call numbers, and their experiences locating materials in other libraries and bookstores. Responses were then coded using colours to identify common themes. Main Results – The study reported that there was little correlation between the students’ own estimation of their ability to locate materials and their actual performance in the index card test. Five students who reported that they could find materials 75-100% of the time performed poorly in the test. Of the 11 participants, only 4 ordered the cards correctly, and in 1 such case this was by fortune rather than correct reasoning. Of these, three self-reported a high level of confidence in their ability to locate material, whilst one reported that he could only find the material he was looking for approximately half of the time. Of the seven students who incorrectly ordered the cards, no two students placed their cards in the same order, indicative that there is no clear pattern in how students misinterpret the numbers. During the interview process, five students stated that they experienced more difficulty locating books in bookstores compared with the library. Conclusion – Based on the findings of the study, the authors recommend several interventions which could help students to locate material within the library, namely through improved signage in shelving areas including the listing of subjects and colour-coding, as well as integrating training on understanding call numbers into subject-based instruction. The possibility of using online directional aids such as QR codes and electronic floor maps is also suggested as a strategy to help orient students.

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)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.994
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.003

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 head0.012
GPT teacher head0.301
Teacher spread0.289 · 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.

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

Citations0
Published2013
Admission routes1
Has abstractyes

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