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Record W2996770528 · doi:10.52358/mm.vi2.96

Sharing contextual knowledge information via asynchronous distance learning

2019· article· en· W2996770528 on OpenAlexaffvenueabout
Lamprini Chartofylaka, Alain Stockless, Marc Fraser, Valéry Psyché, Thomas Forissier

Bibliographic record

VenueMédiations et médiatisations · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Tools and Methods
Canadian institutionsUniversité TÉLUQUniversité du Québec à Montréal
Fundersnot available
KeywordsAsynchronous communicationComputer scienceContext (archaeology)Distance educationKnowledge managementAsynchronous learningDisciplineWorld Wide WebSociologyPedagogyTeaching methodSynchronous learningCooperative learning

Abstract

fetched live from OpenAlex

This paper expands on the effective implementation of collaboration platforms for research purposes in primary education settings. In our study, Edmodo has been introduced as a medium for facilitating the asynchronous discourse between learners of Guadeloupe and Quebec. The following analysis is based on the digital traces derived from the online activity of users working on two different disciplinary research projects: one in linguistics and one in education for sustainable development (ESD). In essence, this paper covers the procedure of introducing a collaborative tool for educational purposes to an audience with diverse expertise in understanding and using it. In addition, it provides a conceptual analysis for understanding the online messages exchanged during these context-related interactions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.005
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.037
GPT teacher head0.364
Teacher spread0.328 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations2
Published2019
Admission routes3
Has abstractyes

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