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Three Stages in the Social Construction of Virtual Learning Environments

2010· book-chapter· en· W4249524527 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

VenueAdvances in social networking and online communities book series · 2010
Typebook-chapter
Languageen
FieldSocial Sciences
TopicEducation in Rural Contexts
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsVirtual learning environmentSocial learningThe InternetComputer scienceSynchronous learningInstructional simulationEducational technologyExperiential learningMathematics educationOpen learningKnowledge managementCooperative learningPsychologyMultimediaTeaching methodWorld Wide Web

Abstract

fetched live from OpenAlex

Schools located in rural communities are often physically small in terms of the number of students who attend them in person on a daily basis, but through the introduction of e-learning partnerships, they can become large educational institutions based on the enhanced range of teaching and learning they can provide. Small school capacities can be enhanced by e-learning and the creation of virtual learning environments. Structurally, the capacity of schools can be enhanced by internet-based inter-institutional collaboration. Pedagogically, e-learning can enable schools to share teaching and learning within virtual learning environments spanning participating sites to facilitate student engagement with ideas, people and places in new, interactive ways. Three stages are identified in the development of teaching and learning in the virtual structures that complement traditional schools.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.800
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.004
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.033
GPT teacher head0.324
Teacher spread0.291 · 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