Evaluating STEM/Engineering Identity of Elementary and High School Students in STEM Outreach Programs
Bibliographic record
Abstract
The effectiveness of STEM outreach programs in fostering interest and sense of belonging can be assessed through participants’ STEM Identity (SI) and Engineering Identity (EI). SI/EI involve an internal feeling of belonging in STEM/Engineering and recognition of belonging from others. This paper assesses how attending a one-week STEM/Engineering camp at a Canadian university changes SI/EI and their subscales (Self-Recognition; Self-Efficacy; Interest; Recognition by Others) among elementary (grades 4-7) and high school (HS; grades 8-12) youth who completed quantitative surveys before and after the camp. SI was assessed for elementary and EI for HS students. There was no significant change in SI, but self-recognition and recognition by others increased significantly while interest and self-efficacy decreased. HS students showed a small but significant increase in EI, self-efficacy, and recognition by others. The results suggest that such programs maintain positive perceptions of the field but may not cause a large or immediate shift in SI/EI.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".