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Record W3216401924 · doi:10.5539/ies.v14n12p125

Geography Literacy Profile of Pre-Service Teachers: The Case of Turkey

2021· article· en· W3216401924 on OpenAlexvenueno aff
Ebru Gençtürk Güven

Bibliographic record

VenueInternational Education Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGeography Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsLiteracyMathematics educationTest (biology)Descriptive statisticsSettlement (finance)Medical educationPsychologyPedagogyMedicineMathematicsStatisticsComputer science

Abstract

fetched live from OpenAlex

The study aims to determine the “Geography Literacy” levels of senior year pre-service teachers. To do so, the correlations between geo-literacy on the one hand, and the program the student is enrolled in, the type of settlement the student lived in during secondary education, the type of high school the student graduated from, the student’s travel experience so far, and attitudes towards geography on the other, were assessed. The study was carried out with 4th year pre-service teachers (n=427) enrolled in six programs in the faculty of education, during the fall semester of academic year 2018-2019. The “Geography Literacy Test” developed by Gençtürk (2009) was used as the data collection tool. The data gathered were analyzed through descriptive, independent samples t-test, one-way ANOVA, chi-square, and Pearson correlation techniques. The study revealed that the geo-literacy levels of pre-service teachers were inadequate. Moreover, the geography literacy levels were found to exhibit significant variance with reference to gender, attitudes, the type of high school, the program the student is enrolled in, and the type of settlement the student lived in during secondary education. The findings were then used as the basis of specific proposals for increasing geo-literacy levels and paving the way for future studies.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.453
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.060
GPT teacher head0.460
Teacher spread0.400 · 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
Published2021
Admission routes1
Has abstractyes

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