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Record W2030385121 · doi:10.11645/7.1.1785

Information literacy in the programmatic university accreditation standards of select professions in Canada, the United States, the United Kingdom, and Australia

2013· article· en· W2030385121 on OpenAlexaffabout
Cara Bradley

Bibliographic record

VenueJournal of Information Literacy · 2013
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsAccreditationInformation literacyKingdomPolitical scienceLiteracyHigher educationMedical educationLibrary sciencePedagogySociologyMedicineComputer science

Abstract

fetched live from OpenAlex

University accreditation schemes, in some form or other, are ubiquitous among English-language speaking countries around the world. Some countries employ national or regional accreditation processes, and a few authors have explored the role of information literacy (IL) in these institution-wide accreditation practices. Little, however, has been written about IL in the context of accreditation standards developed by various professions to regulate the quality of university programmes educating future professionals in the field. This paper investigates the potential of these professional accreditation standards to advance the IL cause and give it a higher profile on campus. It undertakes a qualitative content analysis of the professional accreditation standards for three professions-- nursing, social work, and engineering –in Canada, the United States (US), the United Kingdom (UK), and Australia to determine: If (and in what context) the term IL is used in the accreditation criteria; Other terms/language used in the accreditation criteria to describe IL and associated skills and competencies; Correlations between outcomes outlined in the accreditation documents and IL competencies outlined by the library profession. The study identifies trends, both within specific professions, and within the documents produced by each of the four countries under consideration. It reports significant variation in the language used in the professions to describe the concept of IL, highlighting the alternative language used in the various professions to describe this ability. The study also maps outcomes outlined in the accreditation documents to the Association of College and Research Libraries’ (ACRL’s) Information Literacy Competency Standards for Higher Education ((ACRL 2000) in order to identify areas of overlapping concern. In doing so, this study helps familiarise librarians with the accreditation standards in several subjects, and provides a model for librarians to use in analysing accreditation standards in other subject areas in order to advance IL on their campuses. This article is based on a paper presented at LILAC 2013

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)0.007
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.993
Threshold uncertainty score0.482

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0040.007
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.319
Teacher spread0.304 · 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 designQualitative
DomainEvaluation
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

Citations21
Published2013
Admission routes2
Has abstractyes

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