Self-Regulation of Middle School Students With Learning Disabilities During a Complex Project-Based Science Activity
Bibliographic record
Abstract
Self-regulation is widely considered important for the academic success of students. Yet, there is limited research about how students self-regulate during complex, long-term learning tasks, such as the project-based learning activities that commonly occur as part of science classroom instruction. There is also less known about how atypical learners, including students with learning disabilities (LD), self-regulate academic tasks. The current multiple case study explores these gaps in the research base through an investigation of how middle school students with language-based LDs self-regulated their learning during a complex, science-based project—creation of computerized serious educational games (SEG) about renewable energy sources. Findings from the current study suggest that there is a relationship between attributions that students with LD make for their performance and their self-efficacy for learning, but only under specific conditions. The role of this relationship seems to diminish when a student poorly calibrates perception of ability relative to actual performance and when a student perceives the cost of effort to outweigh the benefit.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".