Female Engineering Students’ Motivations, Career Decisions, and Decision-Making Processes: A Social Cognitive Career and Motivation Theory
Bibliographic record
Abstract
Although women’s rights and career developments have changed over the past decade, only a few updated studies have been conducted to understand the current backgrounds of women in engineering. This study aims to understand and investigate the motivations, career decisions, and decision-making processes of a group of women in the engineering industry, specifically, a group of electrical and electronic engineering students in Taiwan. Based on social cognitive career and motivation theory, the study was guided by two research questions: 1) Why do Taiwanese female electrical and electronic engineering students decide to study this major at university level? 2) Do the participants intend to join the electrical and electronic engineering industry after graduation? Why or why not? The general inductive approach research design with interview, focus group, and member checking interview were used. The results indicated that academic interests, interests in career development, and job security concerns played significant roles in the motivations, career decisions, and decision-making processes of a group of female engineering students in Taiwan. The results of this study filled the gaps in gender discrimination, social stigma, and stereotype toward women in engineering, particularly in Taiwan.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".