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Record W2273063612 · doi:10.1177/2158244015607584

Understanding Classroom Roles in Inquiry Education

2015· article· en· W2273063612 on OpenAlexaff
Cheryl L. Walker, Bruce M. Shore

Bibliographic record

VenueSAGE Open · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Environments and Student Outcomes
Canadian institutionsMcGill University
Fundersnot available
KeywordsSocial constructivismConstructivism (international relations)Diversification (marketing strategy)PhenomenonPedagogyMathematics educationPsychologySociologyEpistemologyPolitical science

Abstract

fetched live from OpenAlex

Inquiry-based teaching and learning are rooted in social constructivism and are central to curricular reform. Role theory and social constructivism provided insight into a commonly observed but insufficiently understood phenomenon in inquiry. Within inquiry, role shifts have been described as the switching of roles between students and teachers; however, the process may be better conceptualized as role diversification because students and teachers may undertake multiple roles simultaneously in inquiry. This article expands on existing research and proposes a framework potentially applicable to both learners and teachers, but here focused on learners. Beyond exploration, engagement, and stabilization of roles, diversification was added and described. This framework expanded on current education theory, adding new insight to a minimally explored topic, with implications for students, teachers, consultants, and researchers.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.015
Scholarly communication0.0100.011
Open science0.0010.009
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.356
GPT teacher head0.451
Teacher spread0.095 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations49
Published2015
Admission routes1
Has abstractyes

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