Visions of Modern Middle Schools: Participatory Design With Nonstudent Stakeholder Groups
Bibliographic record
Abstract
Students are the primary users of school buildings. However, teachers, staff, administrators, parents, and caregivers of students, as well as members of the community, are crucial to the functionality schools. This research increases knowledge about how nonstudent stakeholders conceptualize new middle schools as transformative and supportive of teachers, student learning, and community vitality. Qualitative data were obtained by holding an in-person workshop in one community and distributing an online questionnaire in another. Nine categories emerged from a content analysis of participants’ responses. Despite geographic and economic differences between the two schools (e.g., “School A” served a small rural area with a lower income population and “School B” served a suburban area with a relatively high-income population), the frequency of particular categories was similar concerning nonstudent participants’ wishes for student learning, as well as what they believed would support teachers in a new building. Thematic differences were found concerning what would make their new school transformative and how it could bolster community vitality. Given that the inclusion of a broad range of users in the planning processes of new schools is becoming a best practice for architects, a growing record of nonstudent users’ visions of middle schools may afford more evidence-based decisions about postoccupancy design changes, feasibility of programs, and how the values and goals of a school might be best communicated to students, teachers, parents and caregivers, and the community at large.
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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 | 0.148 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".