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Record W2930237166 · doi:10.5539/jel.v8n3p59

A Study on the University Placement System for Gifted Children in Turkey

2019· article· en· W2930237166 on OpenAlexvenueno aff
Kamil Arif Kırkıç

Bibliographic record

VenueJournal of Education and Learning · 2019
Typearticle
Languageen
FieldPsychology
TopicEducation, Achievement, and Giftedness
Canadian institutionsnot available
Fundersnot available
KeywordsEntrance examGifted educationMathematics educationHonorPsychologyAdvanced PlacementChinaPedagogyMedical educationComputer sciencePolitical scienceCurriculum

Abstract

fetched live from OpenAlex

There is no special university entrance exam for gifted students in Turkey. Their only option is to complete the standard university entrance exam at the end of their final year in high school. This system of entrance exams does not benefit gifted students. Other universities around the world support such students in the following two ways: through honor programs and early college entrance systems. This paper examines these two types of programs that support gifted students, and it employs a cross-cultural comparison between Turkey and the United States, China, and Finland. Furthermore, the paper proposes a multi-step model for educating gifted students and for improving the university entrance exam process. The new type of entrance exam that we propose could be employed in Turkey to support gifted students entering university. By implementing the proposed university entrance system, gifted students will become more effective in life for themselves as well as society.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.019
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.023
GPT teacher head0.321
Teacher spread0.299 · 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 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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