Autonomous, controlled, and amotivated types of academic motivation: A person-oriented analysis.
Bibliographic record
Abstract
The authors investigated students ’ profiles regarding autonomous, controlled, and amotivated regulation and tested whether profile groups differed on some academic adjustment outcomes. Studies 1 and 2 performed on high school students revealed 3 profiles: (a) students with high levels of both controlled motivation and amotivation but low levels of autonomous motivation, (b) students with high levels of both controlled and autonomous motivation but low levels of amotivation, and (c) students with moderate levels of both autonomous and controlled motivations but low levels of amotivation. These first 2 studies revealed that students in the high autonomous/high controlled group reported the highest degree of academic adjustment. Study 3 performed on college students revealed 3 profiles: (a) students with high levels of autonomous motivations but low levels of both controlled motivation and amotivation, (b) students with high levels of both autonomous and controlled motivation but low levels of amotivation, and (c) students with low to moderate levels of the various motivational components. Study 3 indicated that students in the autonomous group were more persistent than students in the other groups. Results are discussed in light of self-determination theory (E. L. Deci & R. M. Ryan, 1985).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".