MétaCan
Menu
Back to cohort
Record W1973517424 · doi:10.1109/fie.2012.6462310

A survey of attitudes, beliefs, and perceptions regarding the internationalization of engineering and Computer Science undergraduate programs at the University of Victoria

2012· article· en· W1973517424 on OpenAlexaffabout
Anna Braslavsky, Anissa Agah St. Pierre, Holly Tuokko, Alexandra Branzan-Albu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsUniversity of Victoria
FundersOffice of International Affairs
KeywordsInternationalizationPerceptionMedical educationGraduate studentsQuality (philosophy)Engineering educationOrder (exchange)Science and engineeringPsychologyEngineering ethicsEngineering managementEngineeringMedicineBusiness

Abstract

fetched live from OpenAlex

Canadian undergraduate and graduate programs in Engineering and Computer Science attract a large number of international students. This is a relatively recent phenomenon with social and academic implications that are not completely understood. We are aware that more can be done for the recruitment, retention, and more generally for increasing the quality of the learning experience of our international students. More efforts need to be made in order to foster and expand social and academic interactions between Canadian and international students, as well as student-faculty interactions. The research described in this paper aims to identify the first steps in creating an inclusive environment that fosters academic, social, and personal growth for both international and Canadian students. This study discusses data collected about the experience of international undergraduate students in the Faculty of Engineering our university. The purpose of the data collection was to determine their specific needs, and to solicit suggestions and recommendations about ways in which to address them.

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)0.000
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 score0.033
Threshold uncertainty score0.803

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.032
GPT teacher head0.305
Teacher spread0.273 · 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
Published2012
Admission routes2
Has abstractyes

Explore more

Same topicHigher Education and EmployabilityFrench-language works237,207