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Record W2479087626 · doi:10.7577/formakademisk.1739

Embodied Making and Design Learning - Special Issue from the Learn X Design-conference DRS/CUMULUS, Chicago 2015

2016· article· en· W2479087626 on OpenAlexaboutno aff
Marte Sørebø Gulliksen, Catharine Dishke Hondzel, Pirita Seitamaa‐Hakkarainen, Tellervo Härkki

Bibliographic record

VenueFormAkademisk - forskningstidsskrift for design og designdidaktikk · 2016
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsnot available
Fundersnot available
KeywordsEmbodied cognitionTheme (computing)Variety (cybernetics)Relation (database)Engineering ethicsLibrary sciencePsychologyComputer scienceEngineeringArtificial intelligenceWorld Wide Web

Abstract

fetched live from OpenAlex

This issue of FORMakademisk features selected articles developed from papers presented at the symposium Embodied Making and Design Learning at the DRS/CUMULUS-conference LearnXDesign in Chicago, Illinois, June 28–30, 2015. This special issue was developed as an initiative by the symposium conveners. The symposium was developed by researchers from research groups in Norway, Finland and Canada to explore various aspects of embodied making in relation to design learning. The symposium was a full-day event with four sessions, seven paper presentations, a roundtable discussion, a plenary discussion and a workshop. The symposium received positive feedback, attracting many participants and stimulating engaged discussions throughout the conference. This indicates a growing awareness of the topic of embodied making and design learning. This special issue features five articles that together highlight a variety of approaches and examples of current research endeavours in relation to the theme.

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 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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.424
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.003
Open science0.0030.001
Research integrity0.0010.002
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 head0.051
GPT teacher head0.292
Teacher spread0.241 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations1
Published2016
Admission routes1
Has abstractyes

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