LAKBAY PISARA: ITS INFLUENCE ON THE SCHOOL PERFORMANCE OF INDIGENOUS PEOPLES EDUCATION (IPEd) LEARNERS
Bibliographic record
Abstract
This is a developmental action research that support the innovation conducted by the school during the Pandemic time where children cannot go to school since Distance Learning using the Self Learning Modules (SLMs) was used as a modality. The researchers used a Descriptive Survey using Self-made questionnaires. It also utilized the results of the Phil-IRI and the Mean Percentage Scores of the school for Third Quarter and Fourth Quarter SY 2021-2022. The study revealed that there is an extremely significant result of the academic performance of the IP Learners and their reading performance when the innovation program Lakbay Pisara was implemented. The results showed on the MPS revealed that the two-tailed P value equals 0.0005. The mean difference of third quarter minus the fourth quarter equals -3.2078 which is a 95% confidence interval of this difference from -4.7612 to – 1.6544. This implies that there was a significant difference in the schools academic performance when the Lakbay Pisara Program is implemented. With the obtained t-test 4.3776 with a degree of freedom of 16 and a standard error of difference of 0 .733, reject the null hypothesis which stated there is no. significant difference in the schools academic performance when the Lakbay Pisara Program is implemented. Moreover, the reading level of IP Learners showed that independent learners increased by up to 32.4% and frustration decreased by up to 30.99% meaning there is really significant influence of the implementation of the program to the reading level of the IP Learners. It is highly recommended to continuously continue the program and support of stakeholders should be sought.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 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".