GROWTH, FIXED, AND MIXED MINDSETS
Bibliographic record
Abstract
Abstract Language learners’ mindsets–their beliefs about whether language is a fixed aptitude that is immutable or a malleable capacity that can be developed–are associated with achievement goals, language-use anxiety, reappraisals of challenges, and persistence. This study integrates these mindset-related constructs to identify mindset-system profiles among foreign language learners. A latent profile analysis of 234 university students in foreign language courses revealed three distinct profiles. The fixed (21.8%) and growth (20.5%) profiles showed distinct and contrasting patterns of goals, reappraisals, anxiety, and persistence. However, most learners (57.7%) endorsed a mixed profile. Although mindsets alone did not predict grades, students in the growth profile were consistently most engaged and achieved the highest grades, suggesting that mindsets function as a system, in concert with related factors. This person-centered approach enhances our understanding of the complexity and functions of the mindset system, as well as the motivation of learners with mixed mindsets.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".