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Record W1978878364 · doi:10.1108/01435120410510247

Information skills of undergraduate business students – a comparison of UK and international students

2004· article· en· W1978878364 on OpenAlexaboutno aff
Tünde Varga‐Atkins, Linda Ashcroft

Bibliographic record

VenueLibrary Management · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsDisadvantagedCurriculumPsychologyQuarter (Canadian coin)Test (biology)International businessSkills managementMedical educationMathematics educationStudy skillsInformation literacyPedagogyPolitical scienceMedicine

Abstract

fetched live from OpenAlex

Summarises the results of a study aimed at measuring the information skills of UK and international students pursuing an undergraduate course in business studies. Investigates the hypothesis that international students studying in the UK might be disadvantaged as a consequence of their different educational backgrounds. The recent higher education curriculum shift towards a more learning‐centred approach and an emphasis on independent learning means that information skills are now far more fundamental to a student’s survival and success. No significant difference between the information skills of UK and international students was found. Only about one‐quarter of students performed well on the test, while three‐quarters had inadequate information skills. The majority of students feel negative or neutral towards library and information skills – with international students having a more positive attitude than home students. One of the main sources of negative attitudes cited was the inability to find information without help.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.011
GPT teacher head0.314
Teacher spread0.303 · 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

Citations54
Published2004
Admission routes1
Has abstractyes

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