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Record W2475402150 · doi:10.5430/ijhe.v5n3p121

The Roots of the Challenge: Undergraduate Chinese Students Adjusting to American College Life

2016· article· en· W2475402150 on OpenAlexvenueno aff
Mei-Ling Tung

Bibliographic record

VenueInternational Journal of Higher Education · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsChinaCultural revolutionHigher educationEconomic growthChinese americansPolitical sciencePsychologySociologyPedagogyLawImmigrationEconomics

Abstract

fetched live from OpenAlex

Recent economic development in China not only has improved the overall living standards of Chinese people, but it has also created a new middle class. Another impact of the economic development is the increasing demand for educated workers. Subsequently, the demand for quality higher education has also increased. With more than 50% of the world’s top 100 universities located in the United States, the United States is regarded as the number one destination for international students for higher education. Due to the cultural differences between China and the United States, scholars have found that Chinese students encounter the most challenges adjusting to American college life. Lack of Western cultural exposure, different cultural values, the effect of the One-Child Policy, the emphasis on effort, endurance, and hard work in education, the continual impact of the Cultural Revolution’s aftermath on people’s relationships, the unfulfilled expectations of American college life experiences, and the influence of the Chinese education structure on students’ characters and skills-building all have an impact on Chinese students’ worldview and their interaction with their new environment. By reviewing the literature on the topic, this article seeks to understand the roots of the challenge to gain insight into the reasons why Chinese students do what they do after they come to the United States for higher education.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.404
Threshold uncertainty score0.272

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.021
GPT teacher head0.435
Teacher spread0.414 · 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 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

Citations8
Published2016
Admission routes1
Has abstractyes

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