3 Let’s START Talking Science: Evaluation of a STEM focused educational program for elementary school students
Bibliographic record
Abstract
As the fields of Science Technology Engineering and Math (STEM) continues to grow, there is a proportional need for well-trained, keen students to take on these roles. In North America, educational curricula are quickly changing to help students develop these skill sets and knowledge early on in their schooling. However, not all schools have the means to support engaging, interactive, hands-on curricula. Enter START Science (START), a not-for-profit organization that brings college volunteers to teach hands-on STEM modules in low-income schools. It was created with the goal of encouraging students from underprivileged backgrounds to gain confidence and interest in pursuing STEM related career fields. Its qualitative impact has been felt, but has not been quantified. The aim of this study was to investigate the effectiveness of START’s STEM-based educational modules in improving positive attitudes towards science in elementary school children in low-income communities. A cohort study of 95 elementary school children in a low-income Toronto District School was performed over the course of a school year. Children were matched to either the experimental group (n=67; 5 classrooms) or the control group (n=28; 2 classrooms). The control group received standard schooling, whereas the experimental group received this plus bi-monthly hour long extra-curricular START teaching modules in one of the STEM-related fields or health awareness over the course of the school year. Attitudes towards science were evaluated using a pre- and post-intervention dichotomous attitudes survey. A Chi-square test was performed to detect statistical differences from pre to post testing. The experimental group demonstrated a 12% growth in positive attitudes toward science over the school year (n=1180 to n=1298), whereas the control group showed a 10% decrease over the school year (n=525 to n=467). Chi-square analysis indicated a significant difference between the two groups (p=0.004). Individual questions, such as “Science should be a part of everyone’s education” showed a similar trend (+18.8% experimental vs. -28.6% control) but were not statistically significant. Positive attitudes towards science increased with administration of the START modules in the experimental group, while those receiving the standard curriculum demonstrated decreasing interest. Elementary students especially in low socioeconomic status neighborhoods, may benefit from organizations such as START.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".