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Record W4220980626 · doi:10.5539/jel.v11n3p1

Hybrid Teaching in Schools: Pedagogical Innovation and Professional Well-Being in a Time of Pandemic

2022· article· en· W4220980626 on OpenAlex
Sacha Stoloff, Nancy Goyette

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.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Education and Learning · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicEducation Practices and Challenges
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersUniversité du Québec à Trois-Rivières
KeywordsContext (archaeology)Professional developmentHigher educationTask (project management)PedagogyPsychologyCoronavirus disease 2019 (COVID-19)Time managementWell-beingSociologyMathematics educationPolitical scienceManagementMedicine

Abstract

fetched live from OpenAlex

At a time where education seems submerged by crisis, some teachers manage to be resilient in order to innovate to adapt and meet educational expectations. This research’s objectives are twofold: 1) to report on their pedagogical innovations and 2) to describe their professional well-being during this unprecedented time. A multi-case study with 20 teachers working in Quebec, in primary and secondary schools, made it possible to present 1) the guidelines teachers followed which directly affected their work context and modulated their professional task, 2) the practices specific to planning, teaching and evaluating, and 3) the evolution of professional well-being, shown alongside with the findings.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.264
Threshold uncertainty score0.859

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
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 head0.066
GPT teacher head0.363
Teacher spread0.298 · 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