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Record W2908018371 · doi:10.5539/jel.v8n1p1

A Collaborative Journey Toward Understanding the Role of Social Class in Teaching and Learning

2018· article· en· W2908018371 on OpenAlexvenueno aff
Lynda R. Wiest, Cynthia H. Brock, Constance M. Morton, Monica N. Colbert, Ryan J. Linton, Brittany Herrera

Bibliographic record

VenueJournal of Education and Learning · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsnot available
Fundersnot available
KeywordsClass (philosophy)PsychologySalientMathematics educationTeaching methodPedagogyGraduate studentsStudent engagementComputer science

Abstract

fetched live from OpenAlex

One important area of development for educators at all levels is teaching students from diverse backgrounds, which includes attention to the important role of social class. In this reflective essay, two teacher educators and four students (two graduate, two undergraduate) examine the aspects of a course on social class and schooling that they perceive to have influenced favorable change in their learning and practice. Individual writings by the six participants at three checkpoints during and after the course generated four themes that the authors discuss in relation to the course content and pedagogy: salient content; effective instructional approaches; application of course material; and suggested improvements. Factors that contributed to course effectiveness included a focus on deep growth involving knowledge and dispositions; instructional methods that encouraged meaningful participant engagement and reflection in a “safe” classroom environment; and practical applications for course material. Suggested improvements centered on including direct engagement experiences and exploring individual course topics in greater depth.

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)0.003
metaresearch head score (Gemma)0.002
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 score0.076
Threshold uncertainty score0.889

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.097
GPT teacher head0.408
Teacher spread0.311 · 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.

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

Citations3
Published2018
Admission routes1
Has abstractyes

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