Utility Value Intervention Study in Postsecondary Gateway Science Courses, United States, 2017-2021
Bibliographic record
Abstract
The Utility Value Intervention (UVI) Study in Postsecondary Gateway Science Courses, funded by Institute of Education Sciences (IES) as a large-scale intervention study, aimed to assess the effectiveness of the utility value intervention in enhancing students' academic progress (reflected in course grades) and persistence (continued enrollment in science courses and sustained interest). Specifically, the study sought to determine whether the intervention had the greatest positive impact on first-generation college students (FG), underrepresented minority students (URM), first-generation underrepresented minority students (FG-URM), and students with multiple high-risk identities. This research was conducted within physics and chemistry courses and implemented as a multi-cohort double-blind randomized controlled trial, involving a total of 7,863 undergraduate participants across six different student cohorts and two science departments. Upon entry into the study, all students were randomly assigned to either the UVI treatment group or a control group. Randomization was stratified based on underrepresented ethnic minority status, first-generation college status, and gender to ensure balanced representation of these subgroups in both treatment and control conditions. Students remained in their assigned condition throughout the study, even if they enrolled in both physics and chemistry courses. The number of cohorts was determined to ensure an adequate sample size for assessing the intervention's effectiveness across various student subgroups with diverse socio-demographic characteristics. Given the study's implementation within the quarter system, Cohorts 1, 3, and 5 commenced in the fall quarter, while Cohorts 0, 2, and 4 began in the winter quarter.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".