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Record W3048453868 · doi:10.3390/educsci10080207

Supporting New Teachers as Designers of Learning

2020· article· en· W3048453868 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

VenueEducation Sciences · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsProfessional learning communityProfessional developmentPsychologyIntervention (counseling)Mathematics educationInstructional designFaculty developmentPedagogyQualitative researchReflection (computer programming)Computer scienceSociology

Abstract

fetched live from OpenAlex

The aim of this study was to examine a professional learning intervention designed to support new teachers with implementing professional practice competencies. Partners from a school authority joined researcher-practitioners from a university to engage in designing a professional learning series for new teachers. A design-based research approach using quantitative (pre- and post-surveys) and qualitative data (artifacts of learning, field notes, classroom observations) were analyzed over one year. There were over 450 participants involved in the professional learning series. The findings indicated the professional learning intervention positioned new teachers as designers of learning engaging in continuous cycles of design–enactment–reflection and strengthened their pedagogical capacity to interconnect professional practice competencies with support from a community of learners. The findings from this study have implications for supporting new teachers during a period of induction and demonstrate one way to provide new teachers with the foundation for continual growth throughout their career.

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)0.001
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.596
Threshold uncertainty score0.885

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.282
GPT teacher head0.499
Teacher spread0.217 · 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