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Record W7061402578

Recruitment of international students in Canadian higher education: factors influencing students’ perceptions and experiences

2020· article· en· W7061402578 on OpenAlexaboutno aff

Bibliographic record

VenueIslandScholar (University of Prince Edward Island) · 2020
Typearticle
Languageen
FieldEngineering
TopicMagnetic Field Sensors Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPerceptionInternational educationHigher educationBridging (networking)Computer-assisted web interviewingSurvey data collectionInformal educationComparative education
DOInot available

Abstract

fetched live from OpenAlex

Working with education agents is common for many Canadian higher education institutions (HEIs) to recruit international students due to the key role education agents play in bridging the international students with foreign HEIs. The purpose of this study was to explore international students' perceptions and experiences with education agents, thus collecting feedback from international students, revealing potential issues, and suggesting improvements in HEIs’ recruitment strategy. An online survey combined with a paper format survey was distributed to current or recent international students across Canada. Two scales were used to measure participants' perceptions and experiences with education agents. A total of 385 participants completed the survey. Findings revealed that nearly half of the participants used education agent services during their application to Canadian HEIs. However, their perceptions and experiences with education agents were not positive. Participants described practices of double-dipping by agents and the more participants paid agents, the less satisfied they tended to be. The outcome of this study highlights issues in the recruitment of international students, identifies strategies to regulate agents’ practices, and strategies to better support international students. These findings can be used by Canadian HEIs to improve their recruitment strategy and create a better working relationship with education agents to support the transition of international students to Canadian HEIs.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.029
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.259
Teacher spread0.240 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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