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Record W7079703217 · doi:10.26108/byh0-6x73

A comparison of international students and Canadian students on student engagement

2014· article· en· W7079703217 on OpenAlexaboutno aff

Bibliographic record

VenueAcadiaU-DEV · 2014
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsStudent engagementData collectionPopulationUndergraduate studentQuality (philosophy)International comparisonsHigher education

Abstract

fetched live from OpenAlex

Currently there is limited research concerning the international student academic, social and personal experience at undergraduate universities, with even less conducted at Canadian universities. This gap in knowledge is an issue in universities as international students comprise an increasingly larger proportion of the student population and there is increased emphasis on attracting international students to Canada. The current study explored the undergraduate student experience to discover any differences that may exist between international and domestic students. Data collection involved the analysis of the National Survey of Student Engagement at a small Atlantic university across an nine-year span. To supplement the quantitative data obtained from the surveys, focus groups were conducted with both international and domestic students. Results from earlier surveys (NSSE 2005 – 2009) demonstrated that few differences exist between the two populations. However, more recent findings, (NSSE 2013), show significant differences between the international and domestic student experience in their quality of interactions with peers, faculty, administrative assistants and others.

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)0.007
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 score0.080
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.007
Science and technology studies0.0050.001
Scholarly communication0.0040.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.035
GPT teacher head0.343
Teacher spread0.308 · 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
Published2014
Admission routes1
Has abstractyes

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