Influence of achievement goals and self‐efficacy on students' self‐regulation and performance
Bibliographic record
Abstract
It is widely admitted that low self‐efficacy has a detrimental impact on the functioning and performance of a person mainly concerned with performance goals but has no impact when a person is mainly concerned with learning goals (Dweck, 1986 ). However, results from both correlational and experimental studies are divergent. Since these studies examined very few indicators of participants' cognitive functioning, they may have failed to detect those aspects that could be more vulnerable to a negative impact of the combination of performance goals and low self‐efficacy. Another concern is the lack of most studies to clearly distinguish the type of performance goal examined, particularly the performance‐avoidance versus the performance‐approach goal. In the current study, we decided to focus on performance‐approach and learning goals in order to examine how self‐efficacy intervenes in their effects on participants' self‐regulation and performance on a cognitive task. One hundred and forty participants (85 females and 55 males) were examined. They were randomly assigned either to the learning or the performance‐approach goals condition. In each condition, half of the participants received feedback aimed at inducing either high or low self‐efficacy beliefs with regard to the task prior to executing it aloud. Examination of participants' verbal reports, direct observation of some of their behaviours while solving the task, and responses to a retrospective questionnaire allowed the assessment of several indicators of their self‐regulation and performance. As already reported by many studies, self‐efficacy influenced various aspects of participants' self‐regulation and performance. However, contrary to Dweck's hypothesis ( 1986 ), when interaction effects between self‐efficacy and goals were observed, they always involved learning instead of performance‐approach goals. Findings of this study suggest that the nature of the goal might not matter as much as its personal significance or value.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".