MAPEH Classes in Public High Schools during the Pandemic; the Student’s Perspectives
Bibliographic record
Abstract
The study's main focus was the viewpoint of students taking MAPEH programs at a state-owned basic education facility. To analyze the data, the study employed Collaizi's method of hermeneutic phenomenology. Additionally, the study was carried out in Cebu Province. The study's participants are ten (10) Junior High students taking MAPEH lessons. To verify the participant's answers during the interview, the researcher used triangulation of data. Four themes emerged from the study: (1) The difficulties of online learning, (2) the unfavorable learning environment, (3) communication issues with the teacher, and (4) the importance of becoming independent learners. Moreover, the study revealed the various difficulties students taking Mapeh faced, such as the lack of technology, the slow internet connection, the unfavorable learning environment, and the difficulty in communicating with their teachers about their lessons. Nevertheless, students used a variety of strategies to get past these difficulties and developed into Independent Learners who learned independently without seeking any assistance from others. They can educate themselves via books, apps, and educational websites.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".