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Record W2654028783 · doi:10.5539/jel.v6n4p137

The Y-Shaped Designer—Connective Competences as Key to Collaboration across Disciplines

2017· article· en· W2654028783 on OpenAlexvenueno aff
Jan Eckert

Bibliographic record

VenueJournal of Education and Learning · 2017
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumDisciplineIdentification (biology)Curriculum developmentEngineering ethicsSet (abstract data type)Knowledge managementSociologyPedagogyComputer scienceMathematics educationEngineeringPsychologySocial science

Abstract

fetched live from OpenAlex

This paper reports on the re-development of our MA curriculum in design. Main objective of this development is a more practice- and project-based MA Curriculum that delivers connective competences for the collaboration across disciplines, rather than specializing in a specific design domain. For design education, we therefore propose a re-visited model of T-shaped skills by proposing the Y-shaped Designer, who acts in collaborations across disciplines thanks to a disciplinary root, a clearly perceived role and the ability to generate multimodal design outputs. The paper’s discussion is based on a study of the current shift in the Swiss Creative Economy, an alumni survey, a literature review focusing undisciplinarity and a series of expert-workshops, that led to the identification of the required skills our graduates need to successfully connect with a globalizing creative economy. First results are a re-definition of the competences and learning goals targeted in the new curriculum, as well as a set of didactical approaches extending the curriculum to what is meant to become a real-world lab for MA students in design.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
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 head0.039
GPT teacher head0.460
Teacher spread0.420 · 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 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

Citations3
Published2017
Admission routes1
Has abstractyes

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