A new curriculum for information literacy: expert consultation report
Bibliographic record
Abstract
Information literacy can be defined as a set of skills, attributes and behaviour that underpins student learning in the digital age. It has been linked to graduate employability and increasingly UK universities are developing information literacy strategies to inform how they ensure students acquire these competencies during their undergraduate studies. Information literacy programmes or sessions are often run by academic libraries; however, in order to be most effective, experts recognise that information literacy should be embedded within a subject curriculum and ideally taught in partnership with academic and academic support colleagues, rather than in one-off sessions run by librarians. SCONUL's Seven Pillars of Information Literacy model, widely accepted in higher education, sets out the skills and attributes that an information literate person should have. In practical terms, however, how information literacy is taught varies widely across higher education. In addition, recent research suggests that the information-seeking behaviour and needs of students are changing (CIBER, 2008), largely driven by the changing experiences and expectations of 'the Google Generation' who have grown up with access to the internet being the norm. While the Google Generation and 'Digital Native' terms have been debated and widely criticised (Jones, et al, 2010), it is clear that information literacy programmes over the next five years will need to adapt and respond to the needs of current students. This short project developed a practical curriculum for information literacy that meets the needs of the undergraduate student entering higher education over the next five years. It consulted widely with experts in the information literacy field, and also those working in curriculum design and educational technologies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.005 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".