Tailoring information literacy instruction and library services for continuing education
Bibliographic record
Abstract
As higher education diversifies worldwide, academic librarians must adapt their information literacy initiatives to meet the needs of new populations. This paper explores the implementation of information literacy instruction and library services for diverse adult learners, in response to Cooke’s (2010) call for case studies on the relationship between andragogy and information literacy. Based on librarians’ success in reaching a previously underserved continuing education department, a variety of practical techniques for working with diverse students and instructors are discussed, with a focus on how learners’ characteristics inform the approaches. Effective techniques from adult education theory and information literacy practice are discussed in the context of outreach to continuing education learners. Librarians adapt instruction and communication strategies for students with varying levels of language, library, and technology skills; teach outside usual “business hours”; teach online; integrate information literacy outcomes in course curricula; tailor communication to students and instructors; and continually develop entirely new workshops based upon the content specific to continuing education programmes. Through these efforts, this unique group of students and instructors has been provided with previously unrealised access to information literacy training and library services. Challenges in outreach and teaching remain; however, the groundwork has been laid for a sustained liaison relationship. Future work will include systematic evaluation of successes and changing needs so that structured information literacy efforts, tailored for continuing education students, can evolve over time.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".