Promoting Positive Behaviours using Sociodrama
Bibliographic record
Abstract
This study investigates whether the use of sociodramatic activities created by Augusto Boal can promote self-expression, a commitment to learning, and positive behaviour in grade eight students. Twenty-four ‘at-risk’ students were identified by the school principal, and participated in 10 weekly 45-minute drama sessions. Initially, participants exhibited behavioural problems such as a lack of motivation, multiple social problems, and a demonstrated lack of respect toward peers and teaching staff. Data from the sessions were collected through participant journals, field notes, questionnaires and member checks. Gender differences were observed in participation levels during activities and discussions. Student responses indicated that the use of sociodramatic techniques provided multiple opportunities for self-expression. Most girls in the study were involved in the dramatic activities and discussions on a consistent basis from the beginning, whereas most boys were inactive participants at the beginning, but increased their commitment, and even assumed leadership roles by the conclusion. While changes in self-expression and commitment to learning may have been the result of students engaging in routinely scheduled drama activities, the study found that sociodrama activities based on Boal, when implemented in the classroom, might have the potential to encourage positive behaviour in at-risk students.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".