Temporal stability of need satisfaction and frustration profiles and their association with motivational functioning
Bibliographic record
Abstract
This study examined profiles of need satisfaction and frustration among secondary school students ( N = 548) in physical education, stability over two months' time, and associations with students' motivation. Using a bifactor exploratory structural equation model, we examined students' global need fulfillment alongside specific autonomy, competence, and relatedness satisfaction and frustration. We contribute to theory in two ways. First, we identified meaningful subpopulations of secondary school physical education students. Global need fulfillment explained differences for the majority of students (Profile 3; 61.6%), displaying a need-based in-tandem pattern associated with adaptive motivational outcomes. However, the inclusion of specific need satisfaction and frustration components uncovered two important subgroups (Profile 2, 33.0%; Profile 1, 5.4%) characterized by slightly (Profile 2) and more (Profile 1) unbalanced profiles. These subgroups, associated with maladaptive outcomes, would have been overlooked using only global measures. Second, profile membership proved to be highly stable within students over a relatively short period. Educational relevance and implications The most valuable implication for education is that negative motivational outcomes (i.e., controlled motivation and amotivation) can be driven by various combinations of need-based experiences. Teachers could experiment with a wide range of motivational behaviors ( Ahmadi et al., 2023 ) to counter negative motivational outcomes. However, for a subgroup of students (33.0%; Profile 2), characterized by higher levels of controlled motivation, especially those behaviors that aim to diminish relatedness frustration may be helpful. Teachers can, for instance, refrain from rejecting these students and show them unconditional regard. For another group of students (5.4%; Profile 1), characterized by higher levels of amotivation, especially those behaviors that aim to diminish autonomy frustration, may be effective. Teachers can, for instance, refrain from pressuring these students, use inviting language, allow their input or choice, or teach in students' preferred ways. Teachers could target specific students who need it the most, in pursuit of transitioning more students into more highly fulfilled profiles. Such experiments are particularly valuable, as students who feel more controlled or amotivated compared to their peers may demand a disproportionate share of the teacher's classroom management efforts.
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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 | 0.007 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".