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Record W4414685789 · doi:10.47408/jldhe.vi37.1699

Learning outside campus: academic Support OFF-SITE, Camberwell College of Arts, University of the Arts London

2025· article· en· W4414685789 on OpenAlexaboutno aff
Ryongsok Chang

Bibliographic record

VenueJournal of Learning Development in Higher Education · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsnot available
FundersBirkbeck, University of London
KeywordsThe artsArchitectureLearning developmentAcademic yearValue (mathematics)Student engagementVisual arts education

Abstract

fetched live from OpenAlex

Underpinned by the principles of ‘discovery learning’ (Bruner, 1961) and inspired by study trips/tours/visits in architectural education (Ewing, 2011), I included off-campus visits as part of my academic support provision from 2022. In September 2024, the Academic Support team at Camberwell College of Arts launched the OFF-SITE programme, offering visits to public spaces, museums, collections, archives, and architectural sites throughout the year, with the aims to allow cross-course student networking to happen, to orient students to London where they were studying and living, and to develop students’ awareness of art and design contexts and academic skills by using London as a resource. In this presentation, I shared the experience of planning, promoting, and implementing the programme with a focus on my visits to places such as Barbican Centre, Victoria and Albert Museum, King’s Cross redevelopment, and Canada Water Masterplan. I also reported on students’ participation in and feedback from these trips. The value of OFF-SITE was multifaceted. These visits were aligned with art and design education, allowing students to reflect in meaningful contexts and develop their critical thinking and research skills in places showcasing creative practice. It has thus provided ‘“curriculum-adjacent” spaces for exploring, planning and reflecting’ (Maxwell and McVitty, 2024), enhancing students’ learning development and engagement with creative scenes in London. These events have also contributed to ‘community-building’, one benefit of teaching outside classroom (Clarke, 2022), through cross-course student communication and networking observed in the trips. Through the implementation of OFF-SITE, valuable insights and learning have been gained into the logistical and pedagogical considerations of off-campus learning initiatives. The success of the programme further demonstrated its potential to be replicated or tailored locally to enhance student experience.

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)0.002
metaresearch head score (Gemma)0.004
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.150
Threshold uncertainty score0.503

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0100.004
Scholarly communication0.0100.004
Open science0.0020.009
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.1500.037

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 head0.025
GPT teacher head0.345
Teacher spread0.320 · 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
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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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