MétaCan
Menu
Back to cohort
Record W4392721183 · doi:10.22318/icls2023.101745

A Community of Practice to Bridge Research and Practice in Science Education

2023· article· en· W4392721183 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

VenueProceedings. · 2023
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsDawson CollegeCégep André LaurendeauVanier CollegeJohn Abbott College
Fundersnot available
KeywordsBridging (networking)Bridge (graph theory)Community of practiceLinkage (software)Knowledge managementCurriculumEngineering ethicsComputer scienceKnowledge sharingPublic relationsSociologyPolitical sciencePedagogyEngineering

Abstract

fetched live from OpenAlex

Communities of practice (CoPs) have been used to support practitioners' efforts to adopt new teaching methods.In this paper, we summarize how our team facilitated knowledge transfer by forming and leveraging several CoPs that shared the common objective of implementing Inquiry-Based Labs (IBL) in science curricula.Over two years, our team members played the role of linkage agents in the CoPs to bridge the gap between education research, by sharing our own research findings, and practice, by collecting feedback directly from IBL practitioners about their challenges with implementation.As various needs of the members were well metto be informed, to share thoughts, to belongthe CoPs have since evolved into stable, sustainable entities.Through these powerful social interactions, CoP members themselves have become linkage agents, connecting us to the larger community that would otherwise not engage with our research and thus further bridging the gap between research and practice.

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)0.046
metaresearch head score (Gemma)0.069
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.762
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0460.069
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.308
GPT teacher head0.602
Teacher spread0.293 · 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