Library and Information Literacy for Distance Education Students
Bibliographic record
Abstract
In the late 1980s, the University of Alaska committed itself to providing rural students with an opportunity to earn a baccalaureate degree via distance education. Shortly thereafter, the University of Alaska Fairbanks established a core undergraduate curriculum in which library and information literacy was included as an essential component, the intent being to help students establish a base upon which more specialized knowledge and skills could be built. Recent and ongoing technological advances have revolutionized access to information and provided distance education students with unique opportunities for conducting research, as well as affording them greater participation in the academic experience. This article reviews the literature on library services and instruction for distance education students, describes the development of the core course for distance education students, and looks at the first year of implementation. Vers la fin des annees quatre-vingts, la University of Alaska s'est engagee a offrir aux etudiants des regions rurales la possibilite d'obtenir un baccalaureat a distance. Peu apres, la University of Alaska a Fairbanks mettait sur pied un programme d'etudes de premier cycle de base comprenant des cours d'informatique et de techniques de recherche obligatoires auxquels on pouvait ajouter des connaissances et des aptitudes plus specialisees. Les progres technologiques des dernieres annees ont revolutionne l'acces a l'information et donne aux etudiants en education a distance des possibilites uniques de recherche et de participation plus active a la vie universitaire. Cet article fait le bilan des publications sur les services de bibliotheque et les cours disponibles aux etudiants a distance, decrit le processus d'elaboration des cours de base et examine le deroulement de la premiere annee du programme.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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".