Same Classroom, Different Affordances? Demographic Differences in Perceptions of Motivational Climate in Five STEM Courses
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Students vary in their perceptions of teachers’ motivational supports, even within the same classroom, but it is unclear why this is the case. To enable the design of equitable environments and understand the theoretical nature of motivational climate, this study explored demographic differences in university students’ perceptions of instruction across five large, introductory STEM (science, technology, engineering, and mathematics) courses (N = 2,486), along with end-of-semester outcomes. Results indicated that women and students from traditionally underrepresented racial or ethnic groups (Black, Hispanic/Latino/a, or Indigenous students) tended to perceive slightly higher motivational support in their courses compared to men and traditionally overrepresented (White or Asian) students, respectively. However, patterns were not uniform across all courses or variables. Men and women did not significantly differ on end-of-semester interest in any course, but women tended to have lower self-efficacy in some courses and significantly higher grades in programming compared to men. Implications include a caution for researchers against interpreting sample-specific or aggregated evidence of demographic differences as generalizing to broader populations or specific settings.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it