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Record W4401868992 · doi:10.18230/tjye.2024.32.4.223

A Study of Understanding of the IB Diploma Scoring System and the Utilization of IB Scores by Foreign Universities

2024· article· en· W4401868992 on OpenAlexaboutno aff
Seulgi Song, M Jung

Bibliographic record

VenueThe Korea Association of Yeolin Education · 2024
Typearticle
Languageen
FieldComputer Science
TopicEducational Research and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationMedical educationPsychologyBusinessMedicine

Abstract

fetched live from OpenAlex

This paper aims to examine the cases of university admission utilizing the International Baccalaureate Diploma Programme (IB DP) scores as interest in the introduction of IB into the Korean public education system is growing. Furthermore, as mentioned in the introduction of the study, this research was conducted to demonstrate that, regardless of its relevance to domestic university admissions, the IB requires sufficient contextual consideration in the process leading to outcomes, unlike the immediate results it shows. It appears that there is a lack of understanding and prior research regarding its system. It is meaningful in providing an understanding of the ways in which diploma scores can be utilized for university admission. To achieve this, this paper explained the composition and calculation method of the IB scores, as well as the types of IB scores used for university admission, including school-based assessment, final IB scores, and predicted IB scores. Additionally, it attempted to provide fundamental information on the methods of utilizing IB scores. The examples used in the study introduced the methods by which universities in the UK, Hong Kong, and Canada utilize the predicted IB scores or IB exam scores. Specifically, this was suggested by aligning the two conditions of conditional offer and confirmed offer This study is expected to serve as a basic resource for university admission, as it is inseparable from IB, just like high school-university linkage. The study aims to contribute as a reference for multi-faceted reviews of IB, especially at a time when the first domestic IB graduates are being produced in South Korea.

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)0.018
metaresearch head score (Gemma)0.058
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.058
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0020.004
Scholarly communication0.0060.007
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.057
GPT teacher head0.335
Teacher spread0.278 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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