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Record W4255858551 · doi:10.24124/2010/bpgub701

Perceptions of the 2009 impact of curriculum implementation on teaching practices of social studies 12 teachers in Northwest Alberta.

2010· dissertation· en· W4255858551 on OpenAlexaffabout
Susan E. Mills

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsUniversity of WindsorUniversity of Northern British ColumbiaLibrary and Archives Canada
Fundersnot available
KeywordsCurriculumAttendancePerceptionSocial studiesMathematics educationPedagogyProfessional developmentPsychologyMedical educationMedicinePolitical science

Abstract

fetched live from OpenAlex

Initial teacher perceptions of the impact of the new Alberta Social Studies curriculum on teaching practices were examined. Social Studies teachers in Northwest Alberta were surveyed, quantitatively and qualitatively, about the use of critical thinking skills in their teaching practices before, and after, implementation of the Grade 12 curriculum. Quantitatively, no significant differences in teaching practices were found. Neither were there any differences in teaching practices found when teachers were differentiated by the variables of sex, total teaching experience, Social Studies teaching experience and department size. However, there were increases found in workshop attendance. Qualitatively, the results aligned with the literature related to teachers' concerns of time, resources, technology, collegial support, professional development, and classroom environment only one exception related to teacher experience was found. School administrators, professional development planners, curriculum designers, and assessors of the implementation of new curricula would find this study of interest. --P. ii.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.245
Threshold uncertainty score0.493

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.082
GPT teacher head0.513
Teacher spread0.430 · 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

Citations0
Published2010
Admission routes2
Has abstractyes

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