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Record W3091040696 · doi:10.1080/23752696.2020.1816845

Opinion piece: non-traditional practical work for traditional campuses

2020· article· en· W3091040696 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHigher Education Pedagogies · 2020
Typearticle
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsAthabasca University
Fundersnot available
KeywordsWork (physics)InstrumentalismHumanismAsynchronous communicationComputer scienceHumanityHigher educationPublic relationsMathematics educationSociologyKnowledge managementEngineering managementPolitical scienceEngineeringPsychologyEconomicsTelecommunicationsEconomic growthEpistemologyMechanical engineering

Abstract

fetched live from OpenAlex

Traditional practical work for higher education in STEM subjects is under pressure from rising student numbers and adesired increase in active learning. Investing in more buildings and staff is financially challenging, while stretching existing resources affects outcomes, health, and participation. A more pragmatic approach is to embrace a less instrumentalist view of practical work in physical spaces and instead adopt a critical post-humanist approach which mixes both humanity and technology to achieve a sum greater than the parts, not bound by the limits of either. We share the experiences of leading UK exponents of non-traditional laboratories in the four main categories of simulation, virtual laboratories, real-asynchronous, and real-synchronous activities, as well as experts in scaling digital education initiatives for university-wide adoption. We foreshadow opportunities, challenges and potential solutions to increasing the opportunity for active learning by students studying at traditional campuses, via the complementary addition of non-traditional practical work.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.797

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.183
GPT teacher head0.345
Teacher spread0.162 · 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