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Record W2223115272

E-Learning for Teacher Development: Global Perspectives of Policy and Planning Issues

2005· article· en· W2223115272 on OpenAlexaff
Paul Resta, Mary Lamon, Alain Breuleux, Evgueni Khvilon, Mariana Patru

Bibliographic record

VenueSociety for Information Technology & Teacher Education International Conference · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsMcGill UniversityUniversity of Toronto
Fundersnot available
KeywordsContext (archaeology)Session (web analytics)Blended learningPanel discussionPedagogyPublic relationsPolitical scienceEducational technologyKnowledge managementPsychologyComputer scienceBusinessWorld Wide WebGeography
DOInot available

Abstract

fetched live from OpenAlex

The panel session will focus on key topics and issues related to the use of e-Learning for teacher development. The international group of panelists are chapter authors of a new book commissioned by UNESCO entitled e-Learning for Teacher Development: A Policy and Planning Guide. Four basic categories of e-learning for teacher development will be presented including: accessing online resources; online courses and degree programs; blended learning environments; and communities of practice. Each category is framed within two axes of e-learning: content and communication. Panelists will share their diverse views of the global context of e-learning for teacher development, the global challenge of preparing 15-35 million teachers needed in the next 15 years to meet UNESCO's Education for All goals and the major organizational, financial, policy and planning issues related to effective use of elearning for teacher development in both developed and developing countries.

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.

How this classification was reachedexpand

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.021
GPT teacher head0.382
Teacher spread0.361 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2005
Admission routes1
Has abstractyes

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