Taking a Step to Identify How to Create Professional Learning Communities—Report of a Case Study of a Korean Public High School on How to Create and Sustain a School-based Teacher Professional Learning Community
Bibliographic record
Abstract
This study intends to identify some key factors in creating and sustaining school-based teacher professional learning communities (PLCs) through a case study of a South Korean public high school. To achieve this, the study identified some essential infrastructure, preparation, and necessary social organization for creating PLCs. The ideal unit and the encouraging/discouraging factors in the implementation process were also investigated. Data were gathered via classroom observations and by analysis of interview transcripts, questionnaire responses, and minutes from PLC meetings. Nineteen participants, including 16 teachers, a principal, an assistant principal, and a facilitator from a city department of education, who assisted the school reform process, completed the questionnaires. Three of the teachers who took the reform initiative participated in the in-depth interview. The study provides a detailed description of the school context before the PLC implementation, challenges that faced the teachers, and two main characteristics of their PLC initiative. The study indicates that participants perceived prepared teacher leaders, building trust and respect among faculty, and securing time for classroom observation and PLC meetings as the most necessary preparation in creating and implementing their PLC. Empowering grade level chairs, increasing teacher proximity, and employing additional administrative assistants were identified as effective administrative support. Participants recognized that each grade level had more advantage in implementing PLCs and thought positive changes of disruptive students and their own instructional practices were the most encouraging factors in overcoming implementation problems. Authoritative leadership of school administration and a city DOE that forcefully mandates PLCs were perceived as discouraging factors in PLC implementation.
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 | 0.019 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".