Instructional Supports for Motivation Trajectories in Introductory College Engineering
Bibliographic record
Abstract
Students, instructors, and policy makers are in need of research-based recommendations for supporting students’ motivation to pursue STEM fields. The present study addressed this need by examining relations between perceived motivational supports, year-long trajectories of expectancy for success and three task values, and grades among students ( N = 1,021) in a large, gateway engineering course. Results indicated that students with higher motivation at the beginning of the year tended to perceive their class as more motivationally supportive. Controlling for relations between initial motivation and perceptions, perceived instructional supports for mastery goals, autonomy, and competence predicted more positive trajectories of all three task values. Conversely, higher perceived instructor performance goals negatively predicted grades and the slopes of self-efficacy and interest value. Results contribute key understanding about the interconnectedness of individual motivation and climate perceptions, while indicating the importance students place on certain motivationally supportive practices in promoting students’ STEM motivation trajectories.
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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 | 0.005 |
| 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 | 0.000 |
| 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".