A Study of the Information Literacy Needs of Social Work Graduate Students at a mid-sized Canadian university
Bibliographic record
Abstract
This study consists of an analysis of the information literacy (IL) needs and levels of 44 social work graduate students at a mid-sized Canadian university using the Technology Acceptance Model. Students completed a quantitative questionnaire that included supplementary open-ended questions. Results showed that students who received a library tour and/or in-class library instruction were more knowledgeable and confident about library resources and services. The study clearly demonstrates that information literacy sessions should be essential components of graduate education. A comprehensive literature review of information literacy studies focusing on social work students is also provided, along with the current graduate social work modified Beile Test of Information Literacy for Education (B-TILED) assessment tool (Beile O’Neil, 2005). The authors recommend that information literacy surveys in Canada include the relevant required elements for the Institutional Quality Assurance Process (IQAP) and program learning outcomes. Given the lack of a Canadian national document for information literacy standards, such surveys should also reflect the components of ACRL’s new Framework for Information Literacy for Higher Education. This study can serve as a model for replication at other universities, particularly those that are part of the Ontario Council of University Libraries and that have graduate social work programs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".