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Record W1496658165 · doi:10.7238/rusc.v12i3.2176

21st-Century Instructional Designers: Bridging the Perceptual Gaps between Identity, Practice, Impact and Professional Development

2015· article· en· W1496658165 on OpenAlexaff
Afsaneh Sharif, Sunah Cho

Bibliographic record

VenueRUSC Universities and Knowledge Society Journal · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Teacher Training
Canadian institutionsUniversity of British ColumbiaUniversity of British Columbia Hospital
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

El propòsit d'aquest article és debatre sobre l'estatus dels dissenyadors instruccionals a través d'un breu comentari sobre la història del disseny instruccional, la comparació dels models de disseny instruccional i una presentació sobre la perspectiva de com els dissenyadors instruccionals afronten la seva identitat actual i la seva professió, mentre busquen el seu desenvolupament professional. En aquest article hem identificat diverses raons per determinar per què l'esforç de desenvolupament professional no és ideal per als dissenyadors instruccionals. Aquestes raons inclouen una falta de prioritat que es dóna al desenvolupament professional des d’un punt de vista de l’organització, el pressupost i el finançament, la càrrega de treball individual i visions i prioritats departamentals. Per tal d’afrontar i superar aquests factors, recomanem una comunitat de pràctica de dissenyadors instruccionals dins de les institucions. Com que el panorama d'educació està canviant constantment, l'àrea de dissenyadors no es pot quedar estàtica. Per a poder respondre a tots els canvis, els dissenyadors instruccionals no solament necessiten esforçar-se en el seu aprenentatge continu, també necessiten adoptar una pràctica de més col·laboració, mitjançant la qual poden compartir i intercanviar idees i millorar pràctiques.

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)0.018
metaresearch head score (Gemma)0.021
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: none
Teacher disagreement score0.025
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.021
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0130.027
Scholarly communication0.0250.016
Open science0.0010.020
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0090.001

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 head0.067
GPT teacher head0.379
Teacher spread0.313 · 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

Citations70
Published2015
Admission routes1
Has abstractyes

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