Dominican Female Undergraduate Engineering Students: Experiences and Self-Efficacy Enhancement
Bibliographic record
Abstract
Rudroff 2007) has become has become an important subject of study over the last decade or so.Diverse lenses, such as self-efficacy beliefs, have been used to explore the persistence of women in STEM fields (Grunert, 2013;Newman, 2017).The beliefs women have about their capabilities are important (Bandura, 1997;Zeldin & Pajares, 2000), since self-efficacy has been found to be an influential factor in their success in these programs (Aryee, 2017; Hutchinson, Follman, & Bodner, 2008;Edzie, 2014).Women who left STEM programs were less confident in their ability in these areas of knowledge compared to those that persisted (Hutchinson, Follman, Sumpter, & Bodner, 2006).Nevertheless, in-depth descriptions of self-efficacy development of women in STEM fields are scarce in the literature.In the context of Dominican students, there is an absence of research that explores women in these programs.For this reason, the purpose of this qualitative study was to better understand the contributions made by self-efficacy sources to the development of self-efficacy beliefs and the persistence of female undergraduate engineering students. Theoretical FrameworkSelf-efficacy is "the belief in one's capabilities to organize and execute the courses of action required to produce given attainments" (Bandura, 1997, p. 3) and can be weakened or enhanced through enactive mastery experiences, vicarious experiences, verbal persuasions, and physiological states. MethodInterviews with ten female undergraduate students took place at a four-year college in the Dominican Republic that specializes in engineering programs.The women were in the last year of their programs of study.Undergraduate student enrollment at this institution was approximately 5,000; of this 1,816 were registered in engineering programs.Of those students, 416 (23%) were women.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 source (direct Gemma or distilled Codex), 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".