Examining Self-Monitoring Interventions for Academic Support of Students with Emotional and Behavioral Disorders
Bibliographic record
Abstract
Abstract Researchers have found that English teachers in the United States of America (USA) perceive providing writing instruction to students with emotional behavioral disorders (EBD) as a difficult task. This could be associated with the fact that students with EBD often work below skill level in the content area of writing compared to same age peers. Researchers continue to investigate interventions to increase academic outcomes for students with EBD. Utilizing a single case design, three middle school students with EBD were observed in a self-contained classroom to determine the effects of a traditional and technology based self-monitoring intervention focused on decreasing student off-task behaviors while increasing scores on writing assignments. The study took place in an urban school district within the Southeastern region of the USA. Results indicated that the first two intervention phases were equally as effective at reducing off-task behaviors. Additionally, the third intervention phase led to decreased off-task behaviors and increased writing scores for all students compared to the previous two phases. Social validity assessments indicated that the self-monitoring interventions were useful and relevant for teachers and students with EBD in the self-contained setting. Implications for teachers and educational researchers are discussed within this article.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".