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Record W2925780990

Family Determinants of Undergraduate Students’ Decisions to Pursue Engineering as a Degree Choice

2018· article· en· W2925780990 on OpenAlexaffabout
Amit Sundly, Gerald Galway

Bibliographic record

Venue2019 Conference of the Canadian Society for the Study of Education · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsEngineering educationDegree programWork (physics)Science and engineeringValue (mathematics)Degree (music)Medical educationPsychologyEngineeringEngineering ethicsMedicineEngineering managementComputer science
DOInot available

Abstract

fetched live from OpenAlex

The global demand for science and engineering professionals is at its peak, yet relatively few Canadian students choose post-secondary programs in certain STEM-related fields leading to an under capacity in the labour market. In this study we used a quantitative research methodology to investigate the influence of family determinants on the decisions of students who decide to pursue an undergraduate Engineering degree. A survey of 151 undergraduate engineering students at Memorial University identified high parental income and education, financial support by parents, parental advice/encouragement, parental pressure to be academically competitive, and value for a degree in science or engineering among family members as key enabling influences for students who opt for university-level engineering studies. Following on the findings from this research and other recent work in this area, we suggest several tangible school-family based strategies and other policy options that could be useful in motivating more high school students to pursue a career in engineering.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score0.482

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.116
GPT teacher head0.389
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
Published2018
Admission routes2
Has abstractyes

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