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Record W2755545348 · doi:10.5430/ijhe.v6n5p76

Co-Operation Is Not Enough: Teacher Educators as Curriculum Developers in Times of Change

2017· article· en· W2755545348 on OpenAlexvenueno aff
Torhild Erika Lillemark Høydalsvik

Bibliographic record

VenueInternational Journal of Higher Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumQualitative researchFocus groupMultidisciplinary approachProcess (computing)Exploratory researchQualitative propertyPedagogyMedical educationMathematics educationSociologyPolitical sciencePsychologyMedicineComputer science

Abstract

fetched live from OpenAlex

The purpose of this exploratory two site case study is to examine how teacher educators, student teachers and programme leaders experience their ‘curriculum developer role’ in times of change, against the background of a new national guideline for preschool teacher education being implemented in Norway. The multidisciplinary team approach established by policy for this reform is examined as a strategy to create coherent programmes. Data collected for the study include fifteen semi-structured interviews and four focus groups conducted at two educational institutions. Qualitative data processing software is used to process four stages of qualitative data analysis. The evidence indicates that the actors involved experienced the ‘reproduction’ of curriculum elements from before the recent reform to a modest extent. Most frequently, they describe incorporation of earlier practices, ‘moderate translation’, in order to meet the demands of multiple disciplines. ‘Radical translation’ also takes place as part of their new collaborative role.

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)0.017
metaresearch head score (Gemma)0.027
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0280.022
Scholarly communication0.0160.012
Open science0.0020.014
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0040.001

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 head0.145
GPT teacher head0.465
Teacher spread0.320 · 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

Citations7
Published2017
Admission routes1
Has abstractyes

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