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Record W7145284232

<実践報告>学科全員留学プログラムの評価を目指した留学後の学生アンケートの質的・量的分析

2017· article· ja· W7145284232 on OpenAlexaboutno aff
Kenichi Yamakawa

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2017
Typearticle
Languageja
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsClass (philosophy)Higher educationQualitative researchGlobalizationQualitative property
DOInot available

Abstract

fetched live from OpenAlex

The rapid spread of globalization has become an inescapable issue educational institutions must urgently address. To this end, many institutions of higher education have undertaken various measures, including offering more university courses in English and increasing the number of study-abroad, double-degree, joint-degree, and student-exchange programs. Particularly, the number of university students joining study-abroad programs offered by their universities has been increasing. Therefore, periodically checking the educational effects of such programs will be worthwhile. The purpose of the present study is to evaluate a five-month study-abroad program of a university by adopting qualitative and quantitative approaches, and to provide perspectives for its future improvement. The data were based on questionnaires administered to over 450 students who participated in the program in 2013 to 2016 upon their return to Japan after completing the study-abroad program at universities in the US and Canada. Multiple aspects of the program, such as types of classes, extracurricular activities, homestay experiences, and program contents, were analyzed. The results showed some similarities and differences in the responses of the students, who studied at different campuses and had different homestay settings. Encounters with other international students in class and the establishment of a good personal relationship with a host family in particular seem to greatly impact students' broader impression of their study-abroad experiences. The implications of the study include various ways to improve students' English proficiency, program contents, and program management, as well as areas for further research.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.005
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.050
GPT teacher head0.353
Teacher spread0.302 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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