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A Great Wall of Difference

2007· book-chapter· en· W2494666287 on OpenAlexaffabout
Susan Crichton

Bibliographic record

VenueIGI Global eBooks · 2007
Typebook-chapter
Languageen
FieldSocial Sciences
TopicInnovative Education and Learning Practices
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInstructional designContext (archaeology)Work (physics)Process (computing)Value (mathematics)Field (mathematics)Computer scienceKnowledge managementPedagogyEngineering ethicsPsychologyMathematics educationEngineeringGeography

Abstract

fetched live from OpenAlex

Instructional design is typically viewed as a process for identifying and solving instructional problems. However, for designers who work on international development projects, the “western” assumptions of instructional design may pose particular challenges as project participants work together to find solutions to teaching and learning problems. The challenge is to find culturally sensitive ways to create resources and provide training for individuals who have different cultural backgrounds. After almost three years of work on the project shared in this article, there are still a number of questions. For example, why has there not been the development of a community of practice around instructional design with the project members? In addition, why has the Canadian project team been unable to encourage our Chinese colleagues to value the instructional design process? This paper offers a number of musings and insights about the field of instructional design within the Chinese context.

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)0.009
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: Other · Consensus signal: Other
Teacher disagreement score0.039
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0040.016
Scholarly communication0.0090.012
Open science0.0010.008
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0390.010

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 head0.103
GPT teacher head0.388
Teacher spread0.285 · 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
GenreOther

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
Published2007
Admission routes2
Has abstractyes

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