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Record W3002593792 · doi:10.24908/pceea.vi0.13704

INTERNATIONAL STUDENT PERCEPTION OF COLLABORATIVE GROUP EXAMS IN A FIRST-YEAR ENGINEERING CHEMISTRY COURSE

2019· article· en· W3002593792 on OpenAlexaffvenue
Roza Vaez Ghaemi, Ágnes Peragovics, Gabriel Potvin

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2019
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGroup workPerceptionMedical educationPsychologyWork (physics)PedagogyEngineeringMedicine

Abstract

fetched live from OpenAlex

Two-stage collaborative exams have previously been shown to improve students’ understanding and long-term retention of material, while helping to develop collaborative skills. Very little work has been done, however, on the impact of this practice on international students, who may be faced with particular challenges or contexts.. Building on previous work, the perception of first-year international students in an engineering chemistry course offered as part of the Vantage College Applied Science program at UBC regarding the practice of two-stage exams was assessed before and after participating in one for the first time. Although the experience was overall very positive, and the anticipated difficulties of the midterm seemed to be overestimated, several key challenges must be addressed before deciding whether to continue with this practice as part of this program, namely communication barriers preventing the effective participation of all group members, and a structural competitiveness that may discourage collaboration, both of which are inherent to the Vantage APSC program, as well as frustration associated with mixed technical proficiencies of group members, which is a more typical concern associated with this type of assessment.

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 score0.193
Threshold uncertainty score0.840

Codex and Gemma teacher scores by category

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

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 head0.002
GPT teacher head0.188
Teacher spread0.186 · 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
Published2019
Admission routes2
Has abstractyes

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