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Record W4225413396 · doi:10.1075/itl.21010.kri

Korean pop culture reshaping Korean teaching

2022· article· en· W4225413396 on OpenAlex
Olga Kriukova

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueITL Review of Applied Linguistics · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Culture and Media Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSyllabusAffect (linguistics)Korean cultureKorean languagePopular culturePsychologyAsian cultureTarget cultureMathematics educationPedagogySociologyMedia studiesLinguisticsAnthropologyCommunication

Abstract

fetched live from OpenAlex

Abstract Korean pop culture is becoming more and more popular outside of Korea and Asia. This trend draws enormous attention to Korean culture, history, and of course, the language. Surveys show that more and more people are learning the language precisely because of their love for Korean pop culture. Such a tendency could not but affect how Korean is taught. In this article, I will look into how the syllabus, teaching methods, and materials used in the KFL classrooms have changed under the influence of Korean pop culture. Moreover, in order to identify if the use of materials related to pop culture can benefit students’ motivation and performance, I conducted an experiment with two groups of students, all starting their beginner-level course (three months). The results of the study showed how the use of such materials in the classroom can affect students’ motivation and attitude toward learning.

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.

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)0.002
metaresearch head score (Gemma)0.004
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: Other · Consensus signal: none
Teacher disagreement score0.948
Threshold uncertainty score0.919

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.024
GPT teacher head0.333
Teacher spread0.309 · 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