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Record W4306752152 · doi:10.15173/ijsap.v6i2.5024

Engaging with students as partners in education-space design

2022· article· en· W4306752152 on OpenAlexvenueno aff
Mike Streule, Luke McCrone, Y. Andrew, Craig Walker

Bibliographic record

VenueInternational Journal for Students as Partners · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsnot available
FundersImperial College London
KeywordsGeneral partnershipCurriculumSpace (punctuation)InstitutionMedical educationEngineering managementMathematics educationPedagogyEngineeringSociologyPsychologyPolitical scienceMedicineComputer science

Abstract

fetched live from OpenAlex

Engaging with Students as Partners (SaP) in areas of curriculum design and pedagogic consultancy is relatively well established. Here we present a case study of two recent projects at Imperial College London, a research-intensive science, technology, engineering, mathematics, and medicine (STEMM) university, that have extended the SaP model to the design and delivery of modifications to education spaces. Using a research-informed approach and tested method ensured that the students remained active throughout the “twists and turns” of the project, rather than the more traditional snapshot student-consultation approach often taken early in the design process. Students experienced authentic partnership with staff, the space, and their department/institution more broadly whilst staff acknowledged that the quality of outputs significantly exceeded expectations at a fraction of the cost of engaging external design consultants. More broadly, projects such as these establish precedents for a more ambitious institutional approach to working with students as partners.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.732
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.091
GPT teacher head0.582
Teacher spread0.491 · 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 designNot applicable
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

Citations5
Published2022
Admission routes1
Has abstractyes

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