Bibliographic record
Abstract
Purpose This paper aims to investigate faculty conceptions of information literacy (IL) in a digital information landscape by examining faculty definitions of IL in the context of undergraduate education, as well as faculty perceptions of, and expectations for, undergraduate IL knowledge and abilities. Design/methodology/approach This is a qualitative research study with 24 semi-structured interviews of faculty in different disciplines at a large public research university in Toronto, Ontario. Findings Faculty view IL as fundamentally intertwined with other academic literacies and as central for the successful pursuit of much undergraduate academic research work including developing autonomous, engaged learners. Faculty place special emphasis on fostering higher-order cognitive skills, especially developing a questioning disposition and the ability to evaluate, contextualize and synthesize information sources. Faculty see considerable scope for improvement of undergraduate IL capabilities, and a large majority see a role for themselves and librarians here. Practical implications Findings of this and other studies align well with core elements in the new IL guidelines and frameworks for higher education both in North America and the United Kingdom. This includes highlighting a need for a strong faculty role in shaping IL in higher education in the future, a need for a holistic lens in developing multiple academic literacies, an emphasis on high-order cognitive abilities and a recognition of the importance of affective dimensions of learning IL. Originality/value This paper fills a gap in the literature where there is an absence of studies, especially of a qualitative nature, which explore faculty conceptions of IL. A majority of studies published focus instead on librarian conceptions and practice.
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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 | 0.031 | 0.078 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.013 | 0.034 |
| Scholarly communication | 0.023 | 0.021 |
| Open science | 0.002 | 0.023 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".