MétaCan
Menu
Back to cohort
Record W4286771277 · doi:10.51657/ric.v6i1.51520

La participation d'étudiantes et d'étudiants en classe d'apprentissage actif vue à travers leurs artefacts épistémiques physiques.

2022· article· fr· W4286771277 on OpenAlexafffundvenue
Elizabeth S. Charles, Kevin Lenton, Michael Dugdale, Nathaniel Lasry, Chris Whittaker, Rhys Adams, Chao Zhang

Bibliographic record

VenueRevue internationale du CRIRES innover dans la tradition de Vygotsky · 2022
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsMcGill UniversityCegep de Trois-RivieresJohn Abbott CollegeCegep de ThetfordCégep de ChicoutimiVanier CollegeDawson College
FundersMinistère de l'Éducation et de l'Enseignement supérieur
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Epistemic artefacts of a physical nature are the material evidence of the work done and produced by students in the course of their learning. According to socio-cultural theory, they can mediate student participation and learning. The role they play, and what this tells us about new forms of teaching such as active learning (AL) in new environments such as active learning classrooms (ALC), had not been explored previously. We used a case study research design and ethnographic methods with 19 instructors from three colleges to explore three research questions based on this gap in the literature. Qualitative coding technique as well as latent class analysis were used to analyse the data, i.e., classroom observations (N=157). Our results confirmed that AL teaching generates physical artefacts. Furthermore, these artefacts play an epistemic role in learning and teaching. Our analyses distinguished four features of these artefacts, expressed as bi-polar modalities: (1) individual and/or collective; (2) private and/or public; (3) analogue and/or digital; and (4) new and/or reused. Other analyses led to more results. It is important to note that the public modality appears to be the most critical for understanding the mediating role of artefacts. We discuss the implications of these public artefacts on how learning and teaching takes place in ALCs and provide suggestions for practitioners using AA pedagogies in ALCs.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.764
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.152
GPT teacher head0.402
Teacher spread0.250 · 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 designTheoretical or conceptual
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

Citations1
Published2022
Admission routes3
Has abstractyes

Explore more

Same venueRevue internationale du CRIRES innover dans la tradition de VygotskySame topicEducation, sociology, and vocational trainingFrench-language works237,207