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Record W2788880146 · doi:10.31468/cjsdwr.600

Drawing as a Way of Knowing: Visual Practices as the Route to Becoming Academic

2018· article· en· W2788880146 on OpenAlex
Sandra Abegglen, Tom Burns, Sandra Sinfield

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueDiscourse and Writing/Rédactologie · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsnot available
Fundersnot available
KeywordsSet (abstract data type)Mathematics educationPsychologyAcademic writingPedagogyGraduate studentsComputer science

Abstract

fetched live from OpenAlex

This case study illustrates what happened when we took a playful approach in a first year undergraduate academic skills module and a graduate Facilitating Student Learning module asking our students to “draw to learn.” We found that they not only enjoyed the challenges we set them, but also that they “blossomed” and approached their academic writing with more confidence and joy. Hence we argue for a more ludic approach to learning and teaching in Higher Education to enable Widening Participation students and their tutors to become the academic writers they want to be. In particular “blind drawing” seems to be a powerful tool for diminishing the fear of failure and for fostering deep understanding as well as self-confidence.

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)0.003
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.451
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.177
GPT teacher head0.555
Teacher spread0.378 · 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