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Record W1562624993

Professional Development: A Rural School District's Experience with Videoconferencing

2004· article· en· W1562624993 on OpenAlexafffundabout
Karen Fiege, Kim Peacock, David Geelan

Bibliographic record

VenueGriffith Research Online (Griffith University, Queensland, Australia) · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsUniversity of Alberta
FundersUniversity of AlbertaCanarie
KeywordsVideoconferencingProfessional developmentAsynchronous communicationMedical educationContinuing professional developmentDistance educationThe InternetPedagogyPsychologyMultimediaEngineeringComputer scienceTelecommunicationsMedicineWorld Wide Web
DOInot available

Abstract

fetched live from OpenAlex

The Rural Advanced Community of Learners (RACOL) project undertook an initiative to develop broadband synchronous and asynchronous technologies to a rural school district in northern Alberta, Canada. Relying on the recently installed Alberta SuperNet (a high-speed broadband network), the Virtual Presence Learning Environment (VPLE) classrooms were built using various digital and videoconferencing technologies. As of September 2003, four full-time teachers were required to teach varying subjects within these VPLE classrooms. Therefore, a professional development team was formed and nine professional development sessions were conceptualized and delivered. A history and unique qualities of the RACOL project, a review of literature pertaining to professional development for educational technologies, an in-depth analysis of the nine sessions that were delivered, as well as the results of some research conducted during the nine sessions will be described within this paper.

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)0.004
metaresearch head score (Gemma)0.007
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0250.005
Scholarly communication0.0050.002
Open science0.0030.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.134
GPT teacher head0.422
Teacher spread0.289 · 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

Citations0
Published2004
Admission routes3
Has abstractyes

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