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Record W2090858776 · doi:10.1300/j192v02n04_04

How Librarians Shape Online Courses

2006· article· en· W2090858776 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Library & Information Services in Distance Learning · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsQueen's University
Fundersnot available
KeywordsInformation literacyComputer scienceContext (archaeology)Instructional designVirtual learning environmentConstruct (python library)Resource (disambiguation)Educational technologyDistance educationKnowledge managementWorld Wide WebMultimediaMathematics educationPsychology

Abstract

fetched live from OpenAlex

Abstract Online course delivery can be a dynamic learning experience where information is used to shape and extend thinking. The challenge is creating a virtual classroom that combines evocative resources with tasks that enhance and stimulate student learning. New models are needed to reflect the changing learning environment that began with the advent of the Web. Librarians are experts in locating learning materials across the electronic landscape. They construct resource-based assignments that promote understanding of content and develop independent thinking skills. They bring a context for resource-rich learning environments and the necessary support mechanisms to ensure learners gain information literacy skills. This paper outlines how librarians can contribute to new course design models that maximize the effective use of online resources in support of student learning.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.920
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.022
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.254
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it