School Preparedness for the Mandatory Implementation of Face-To-Face Classes and Its Impact to Teaching Qualities in the New Normal
Bibliographic record
Abstract
This research used descriptive correlational research design to find significant relationship between the extent of school preparedness in the mandatory implementation of five days face-to-face classes and its possible impact to teaching qualities. The respondents of this study were 188 teachers of Candelaria West District of Quezon. It was conducted during the third quarter of SY 2022-2023. Description of the profile revealed that the respondents are mostly female, aged between 46-50, mostly taking their post graduate degree, and majority of them have been in the service for five years. The perceived level of preparedness of the school in terms of facilities, school programs, safety protocols, and students and parent’s awareness were always prepared. The perceived level of the teachers’ practices in the new normal in terms of Classroom Management, classroom instruction and collaborative activities was always practice while professional development was in the practiced spot. All the variables are correlated to each other indicating that school preparedness has significant relationship to the teaching qualities of the teachers as perceived by the respondents. Thus, the hypothesis stating that school preparedness has no significant impact to teacher’s teaching qualities in terms of classroom management, classroom instruction, professional development and collaborative activities.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".