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Record W1563809612 · doi:10.21432/t2mk6q

A Case Study of Institutional Reform Based on Innovation Diffusion Theory Through Instructional Technology

2003· article· en· W1563809612 on OpenAlexvenueno aff
Michael Szabó, Sonia A. C. K. Sobon

Bibliographic record

VenueCanadian Journal of Learning and Technology · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsEmpowermentDiffusion of innovationsQualitative researchStakeholderKnowledge managementSociologyEducational technologyTechnology integrationInstructional designInstructional technologyMultimethodologyPedagogyPublic relationsPolitical scienceComputer scienceSocial science

Abstract

fetched live from OpenAlex

A theory-based system of educational reform through instructional technology, the Training, Infrastructure and Empowerment System (TIES), was developed and piloted in a research university during the late 1990s. In 2001, a research study was conducted on this implementation using qualitative methodology. Interviews were conducted with 12 participants who represented 4 different stakeholder groups. Some of the themes to emerge were: (a) Vision for instructional technology, (b) learning technologies and alternative delivery systems, (c) adoption of innovation, (d) general challenges and (e) lessons learned. Discussion includes implications of these themes for reform of education as they relate to a theoretical reform framework. Suggestions for further research are also identified.

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)0.010
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0120.005
Scholarly communication0.0040.006
Open science0.0020.005
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.017
GPT teacher head0.289
Teacher spread0.272 · 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 designObservational
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

Citations11
Published2003
Admission routes1
Has abstractyes

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