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Record W1983878706 · doi:10.1177/1741143214535747

The use of technology in Prince Edward Island (Canada) high schools

2014· article· en· W1983878706 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEducational Management Administration & Leadership · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsEducational leadershipQualitative researchPerceptionSociologyPedagogyTechnology integrationEducational technologyPublic relationsPsychologyPolitical scienceSocial science

Abstract

fetched live from OpenAlex

The purpose of this paper is to document the perceptions of school leaders regarding the technological use, skills, and attitudes of high school teachers. Using a qualitative research approach, 11 educational leaders from Prince Edward Island (Canada) were individually interviewed. Participants represented the Department of Education, principals, vice-principals, and department heads. Analyzed through the concept of e-leadership, the findings indicated that participants used a growing array of technological tools and activities including Smartboards, flipped classrooms, Prezi, educational apps, YouTube, and teacher blogs. Participants identified lack of time as a possible reason why some teachers were not incorporating technology into student learning. Findings highlight the need for provincial and school district authorities to promote policies aimed at promoting e-leadership among teachers. We insert an appendix to provide descriptions of the technological terms included within the 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.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.879
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.063
GPT teacher head0.312
Teacher spread0.248 · 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