Choice and voice in middle school: cultivating agency for well-being
Bibliographic record
Abstract
Self-determination theory (Ryan & Deci, 2009) suggests that teacher provided supports for autonomy, competence and relatedness facilitate motivation and, in turn, students’ engagement and overall well-being. The literature related to well-being, however, does not provide a clear and thorough description of the factors that connect well-being and agency. This phenomenological case study explores the factors that influence students’ agency for well-being and answers the question, “How does a choice and voice teaching approach in English Language Arts impact middle years students’ agency for well-being?” The study involved fifteen participants who were students taught by the researcher in Grades 7 and 8 during the 2012 - 2018 school years. Ethics approval was given to conduct individual interviews, a focus group discussion and to use students’ writing pieces as data. In exploring the literature and hearing from the students it became apparent that choice and voice opportunities are seldom incorporated in the pedagogical toolkits of upper elementary and secondary teachers in the formal education system. In order for students to have power and agency they require autonomy support with a focus on collaboration, communication, creativity and critical thinking. Findings revealed that human agency relates to these needs for well-being, and that the Choice and Voice based approach described promotes self-esteem and confidence, and increases student motivation and engagement. As such, the study reveals an approach that all teachers can implement to support and enhance learners’ overall agency for well-being.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".