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Record W2064254097 · doi:10.1080/0158791032000127473

Web-based video and frame theory in the professional development of teachers: some implications for distance education

2003· article· en· W2064254097 on OpenAlexaff
Cresencia Fong, Earl Woodruff

Bibliographic record

VenueDistance Education · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDistance educationFrame (networking)Professional developmentWeb applicationFaculty developmentSociologyComputer scienceMultimediaMathematics educationPedagogyWorld Wide WebPsychologyTelecommunications

Abstract

fetched live from OpenAlex

This study explores the use of video vignettes as a tool for the professional development of teachers. It is postulated that teachers' professional frames prime them to view vignettes through multiple “lenses,” and that teachers may not recognize exemplary practice when presented with it. Think-aloud and interview data are collected as 11 pre-service and 11 experienced teachers observe exemplary astronomy teaching video vignettes. Quantitative analyses suggest that teachers rarely recognized the exemplary qualities of practice presented to them. Furthermore, teaching experience significantly influences the type of lens through which a teacher will observe exemplary practice vignettes. There is also some evidence to suggest that priming teachers with instructions may be helpful. Implications for the design of video on the Web are discussed.

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)0.009
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.004
Scholarly communication0.0040.007
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.019
GPT teacher head0.364
Teacher spread0.345 · 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 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

Citations15
Published2003
Admission routes1
Has abstractyes

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