The Educational Leader’s Role in Guiding Teachers to Declutter Their Classrooms
Bibliographic record
Abstract
Abstract: Classrooms are often cluttered, creating overstimulated students and overwhelmed teachers, which does not lead to optimal learning environments. A teacher’s role is to optimize the learning environment; however, not all teachers are aware of the connection between the physical learning environment and learning outcomes. Of particular concern is the link between cluttered spaces and poor learning outcomes due to distraction (Granito and Santana, 2016). Unfortunately, not all instructional leaders recognize this connection either or those who do may not always know how to provide support. The educational leader's responsibility as an instructional leader is to help teaching staff enhance their ability to establish ideal learning settings. Thus, educational leaders need to prioritize support for teachers in creating school spaces that are intentionally decluttered for optimum learning and teaching. In this paper, I provide best practices using research and personal observation to describe how to support educational leaders in this process. This paper also includes a section on how to support teachers during decluttering as suggested by practitioners writing on the internet.
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 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".