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Record W2152495376 · doi:10.21432/t22p41

An Extended Systematic Review of Canadian Policy Documents on e-Learning: What We’re Doing and Not Doing

2011· article· en· W2152495376 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Learning and Technology · 2011
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsConcordia University
Fundersnot available
KeywordsPopularityConsistency (knowledge bases)Public policyGovernment (linguistics)Public relationsPolicy learningPolitical scienceKnowledge managementComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This systematic review builds upon the work of Authors (2006) and McGreal and Anderson (2007). It seeks to provide a synthesis and discussion of publicly available government policy documents with regard to e-learning in Canada. There is general consensus, both in public opinion and in the research literature, that the educational practices associated with rapidly advancing computer information technologies are gaining popularity and are expected to be increasingly effective in enhancing learning. The purpose of this review is to uncover and describe areas of commonality and inconsistency in e-learning policy documents dated from 2000 to 2010, and to determine where discussions about e-learning are lacking. In total, 138 policy documents from Canadian provinces and territories and several federal agencies were retrieved and analyzed using prescriptive and emergent coding approaches. The review confirmed that Canadian policy makers view technology as offering potential benefits to learners, but also revealed a troubling lack of specific details, consistency and coordination in facilitating the development of e-learning to fulfill these optimistic expectations.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.085
GPT teacher head0.404
Teacher spread0.320 · 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