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Record W2778629376 · doi:10.5539/ies.v11n1p81

What Makes a Change Unsuccessful through the Eyes of Teachers

2017· article· en· W2778629376 on OpenAlexvenueno aff
Sabiha Odabaşı Çimer

Bibliographic record

VenueInternational Education Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsnot available
Fundersnot available
KeywordsSkepticismAgency (philosophy)PsychologyReform movementWork (physics)Faculty developmentProfessional developmentAccountabilityTeaching methodPedagogyMathematics educationMedical educationPublic relationsPolitical scienceSociologyMedicine

Abstract

fetched live from OpenAlex

Over the past two decades, Turkey has initiated a reform movement to change her classroom assessment system to accommodate performance-based alternative assessment methods in schools. However, research investigating the impact of assessment reform on learning and teaching in schools report that performance assessment approaches have not been implemented effectively. This study investigated the teacher related factors behind the adoption decisions of teachers of these changes introduced. Data for the study were collected through interviews with 53 biology teachers in 24 schools. According to the findings, teachers’ lack of self-agency, superficial understanding of the ideas introduced, mistrust that the innovations will work in practice, skepticism about the need for a change and inadequate knowledge and abilities as a result of ineffective dissemination and professional guidance were the main factors affecting the success of the reform. Suggestions to overcome barriers to reform and implications of the findings in managing change are presented and discussed at the end of the paper.

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)0.025
metaresearch head score (Gemma)0.082
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: none
Teacher disagreement score0.025
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.082
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0140.042
Scholarly communication0.0200.016
Open science0.0020.008
Research integrity0.0120.012
Insufficient payload (model declined to judge)0.0030.001

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 head0.254
GPT teacher head0.572
Teacher spread0.317 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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