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Record W2472548098 · doi:10.5539/ies.v9n7p64

Problems of the Immigrant Students’ Teachers: Are They Ready to Teach?

2016· article· en· W2472548098 on OpenAlexvenueno aff
Figen Ereş

Bibliographic record

VenueInternational Education Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and experiences of immigrants and refugees
Canadian institutionsnot available
Fundersnot available
KeywordsQualitative researchChristian ministryNonprobability samplingImmigrationEthnic groupPsychologyMathematics educationScheduleClass (philosophy)PedagogyQualitative propertyContent analysisSemi-structured interviewData collectionMedical educationSociologyPopulationMedicinePolitical scienceMathematicsSocial science

Abstract

fetched live from OpenAlex

<p class="apa">Aim of the study is to investigate the problems faced by the teachers’ of immigrant children living in Turkey. The study was conducted based on the qualitative phenomenological research design and purposive sampling method was used. Qualitative research technique was used to collect, analyze and interpret data and technically content analysis was used in this research. A semi-structured interview schedule prepared in accordance with the qualitative research approach is used as a data collection tool. As a result of the analysis, it was found that main problems face by these teachers were categorized as problems caused by the Ministry of Education, adaptation problems of the students and problems related with the migrant parents. Among them, most complained problems were those caused by the Ministry of Education. Depending on the data obtained, it can be said that, Ministry of Education has no policy or planning about the education of the migrants and the teachers were not prepared for the education and training of migrant children. Another finding was the indifference of the migrant parents regarding the school. A striking point in the study was that the teachers never mentioned about the problems concerning the differences of race, ethnicity or gender. As a result of the evaluation, it is suggested that the Ministry of Education should provide language training for immigrants and care more about the equivalence of the students, training teachers and candidate teachers about immigrant pedagogy and to develop better relations between the school and the migrant families.</p>

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.627
Threshold uncertainty score0.371

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 science0.0010.000
Research integrity0.0000.000
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 head0.053
GPT teacher head0.426
Teacher spread0.373 · 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 designNot applicable
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

Citations26
Published2016
Admission routes1
Has abstractyes

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