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Record W2805384480 · doi:10.5210/fm.v24i6.9180

Open enough? Eight factors to consider when transitioning from closed to open resources and courses: A conceptual framework

2019· article· en· W2805384480 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

VenueFirst Monday · 2019
Typearticle
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsMount Royal UniversityUniversity of Alberta
Fundersnot available
KeywordsOpen educational resourcesOpenness to experienceUsabilityOpen educationComputer scienceOpen standardMassive open online courseOpen dataKnowledge managementOpen sourceOpen platformWorld Wide WebPsychologyHuman–computer interactionInteroperability

Abstract

fetched live from OpenAlex

Transitioning from closed courses and educational resources to open educational resources (OER) and open courseware (OCW) requires considerations of many factors beyond simply the use of an open licence. This paper examines the pedagogical choices and trade-offs involved in creating OER and OCW. Eight factors are identified that influence openness (open licensing, accessibility and usability standards, language, cultural considerations, support costs, digital distribution, and file formats). These factors are examined under closed, mixed and most open scenarios to relatively compare the amount of effort, willingness, skill and knowledge required. The paper concludes by suggesting that maximizing openness is not practical and argues that open educators should strive for ‘open enough’ rather than maximal openness.

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, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.927
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0030.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.031
GPT teacher head0.296
Teacher spread0.264 · 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