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Record W2178197302

A quantitative analysis of first-year engineering student persistence and interest in civic engagement at a Canadian university

2008· dissertation· en· W2178197302 on OpenAlexaffabout
Gloria Montano

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2008
Typedissertation
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsAppealCivic engagementPersistence (discontinuity)Relevance (law)Student engagementPsychologyMathematics educationPolitical scienceEngineering
DOInot available

Abstract

fetched live from OpenAlex

This study explored what variables engineering students self-identify as reasons they persist from first to second year, and what areas of civic engagement appeal to students, in order to identify areas of local relevance that could inspire academic improvements. The research found that the study group is similar to first-year students in general at the subject university and to first-year engineering students at other universities. No compelling evidence was found that the study group would perform differently than previous cohorts. Results also showed that first-year engineering students were interested in and had prior experience in civic engagement activities. Overall, female and rural students consider civic engagement more important than their counterparts, particularly with community action program participation and becoming community leaders. Findings include a descriptive profile of a dual-cohort, first-year engineering class at a Canadian university that contributes Canadian data and experience to the body of knowledge on engineering student persistence.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.422
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0060.005
Science and technology studies0.0040.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.002
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 head0.082
GPT teacher head0.306
Teacher spread0.224 · 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.

Study designQualitative
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

Citations1
Published2008
Admission routes2
Has abstractyes

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