Understanding Interest and Self-Efficacy in the Reading and Writing of Students with Persisting Specific Learning Disabilities during Middle Childhood and Early Adolescence
Bibliographic record
Abstract
Three methodological approaches were applied to understand the role of interest and self-efficacy in reading and/or writing in students without and with persisting specific learning disabilities (SLDs] in literacy. For each approach students in grades 4 to 9 completed a survey in which they rated 10 reading items and 10 writing items on a Scale 1 to 5; all items were the same but domain varied. The first approach applied Principal Component Analysis with Varimax Rotation to a sample that varied in specific kinds of literacy achievement. The second approach applied bidirectional multiple regressions in a sample of students with diagnosed SLDs-WL to (a) predict literacy achievement from ratings on interest and self-efficacy survey items; and (b) predict ratings on interest and self-efficacy survey items from literacy achievement. The third approach correlated ratings on the surveys with BOLD activation on an fMRI word reading/spelling task in a brain region associated with approach/avoidance and affect in a sample with diagnosed SLDs-WL. The first approach identified two components for the reading items (each correlated differently with reading skills) and two components for the writing items (each correlated differently with writing skills), but the components were not the same for both domains. Multiple regressions supported predicting interest and self-efficacy ratings from current reading achievement, rather than predicting reading achievement from interest and self-efficacy ratings, but also bidirectional relationships between interest or self-efficacy in writing and writing achievement. The third approach found negative correlations with amygdala connectivity for 2 reading items, but 5 positive and 2 negative correlations with amygdala connectivity for writing items; negative correlations may reflect avoidance and positive correlations approach. Collectively results show the relevance and domain-specificity of interest and self-efficacy in reading and writing for students with persisting SLDs in literacy.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".