Bibliographic record
Abstract
Abstract Engineering Perspectives of Grade 7 Students in CanadaMany high school students are unable to consider engineering as an undergraduate program ofstudy because they do not have the prerequisite courses required for university entrance. In orderto provide the opportunity for capable students to pursue an engineering degree and subsequentlyenter the engineering profession, they must understand what engineering is prior to entering highschool to enable them to select appropriate courses.The focus of this study is to understand how students in 7th grade perceive the profession ofengineering in three regions across Canada. The literature suggests that modest action isunderway in some areas of the United States in order to create awareness and encourage studentsto pursue an engineering program. These initiatives range from integrating engineering conceptsinto the K-12 curriculum to providing outreach and design challenge opportunities outside ofschool. Such initiatives are present in very isolated cases within Canada, however, their reachand impact is limited. In order to better understand the perspective of pre-high school students in Canada, they will beprovided with a survey incorporating a variety of questions pertaining to what they understandabout engineering as a profession. All questions have been structured as open ended in order topromote individualized answers from the students. Survey questions will be analyzed withNVIVO software to determine if there are common themes in the understanding and perceptionof engineering from the students’ perspective. Observations and emerging trends of this work inprogress will be presented in the final paper.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".