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Record W2916337026 · doi:10.5539/jel.v8n2p25

Irregular Teacher Turnover and Student Academic Achievement in High Schools: A Study in the Subjects Mathematics, German, French and History

2019· article· en· W2916337026 on OpenAlexvenueno aff
Belinda Aeschlimann, Walter Herzog, Fabian Sander

Bibliographic record

VenueJournal of Education and Learning · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsGermanAcademic achievementMathematics educationAffect (linguistics)PsychologyClass (philosophy)Geography

Abstract

fetched live from OpenAlex

Teacher turnover that is not related to regular school transitions is a neglected topic of educational-psychological research. This study examines irregular teacher turnover and its effect on students’ academic achievement in the subjects Mathematics, German, French and History at four high schools of the canton of Berne, Switzerland. The study is based on an administrative dataset used to track the academic achievement of N = 1789 students from more than 100 classes. The results show that irregular teacher turnovers affect every 12th class on average, whereby definitive turnovers occur more frequently than temporary ones. In all examined subjects, panel data models show that irregular teacher turnovers have a more or less pronounced negative effect on students’ academic achievements. With respect to the students’ gender no significant differences have been observed.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.156
Threshold uncertainty score0.248

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.018
GPT teacher head0.329
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 designObservational
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
Published2019
Admission routes1
Has abstractyes

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