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Record W1507770617 · doi:10.19173/irrodl.v10i5.664

Open Educational Resources: New Possibilities for Change and Sustainability

2009· article· en· W1507770617 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2009
Typearticle
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsOpen educational resourcesSustainabilityKnowledge managementWork (physics)Object (grammar)BusinessPublic relationsPolitical scienceComputer scienceWorld Wide WebEngineering

Abstract

fetched live from OpenAlex

In an attempt to understand the potential of OER for change and sustainability, this paper presents the results of an informal survey of active and inactive collections of online educational resources, emphasizing data related to collection longevity and the project attributes associated with it. Through an analysis of the results of this survey, in combination with other surveys of OER stakeholders and projects, the paper comes to an initial conclusion: Despite differences in priorities and emphasis, OER initiatives are in danger of running aground of the same sustainability challenges that have claimed numerous learning object collection or repository projects in the past. OER projects suffer from the same incompatibilities with existing institutional cultures and priorities that have dogged learning object initiatives, and they face the concomitant challenge of gaining access to the operational funding support that experience shows is necessary for their survival. However, through a review of one of the most successful of OER projects to date, the MIT Open Courseware Initiative, the paper ends by augmenting this significant caveat with a second, more hopeful conclusion: OER projects, unlike learning object initiatives, can accrue tangible benefits to educational institutions, such as student recruitment and marketing. Highlighting these benefits, it is argued, provides an opportunity to link OER initiatives to core institutional priorities. In addition to providing a possible route to financial sustainability, this characteristic of OER may help to foster the significant changes in practice and culture long sought by promoters of both learning objects and OERs.

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)0.006
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.926
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0000.000
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 head0.143
GPT teacher head0.477
Teacher spread0.334 · 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