UTILIZATION OF THE WHOLE CHILD APPROACH IN IMPROVING THE ACADEMIC PERFORMANCE OF HIGH SCHOOL STUDENTS IN ECONOMICS 9: BASIS FOR PROPOSED LEARNING INSTRUCTIONAL ACTIVITIES
Bibliographic record
Abstract
This study was conducted to explore the utilization of the whole child approach in improving the academic performance of high school students in Economic 9. After the process of experiment and assessment, proposed learning instructional activities utilizing the whole child tenets were produced. The proponent used purposive sampling in selecting the students who were included in the study. The researcher prepared a letter of request to the Principal of the school, to asked permission and approval to conduct the research. In the construction of the lesson plan and the teacher made test, the researcher sought the assistance of the teachers and professors coming from the different schools in the private and public, to check and validate the research instruments. The proponent also asked permission from the Association for Supervision and Curriculum Development in the U.S. to use the online standardized questionnaire. In administering the copies of the survey instrument were personally distributed and retrieved by the proponent to the grade 9 students. This study found out that the whole child approach contributed to the improvement of the academic performance of grade 9 high school students in Economics for the fourth-quarter period. This is seen through the positive results of the post-test and learning gain of students, which corroborated from the data extracted from the survey questionnaire. Through the T-test of two sample means, it was revealed that there is a significant difference in the pre-test and post-test of the students. It is also revealed that the majority of the respondents have higher post-test than pre-test and having positive learning gain. Furthermore, there is a need to intensify the efforts of the school administrators and educators to support and promote sustainable use of the whole child approach in classroom instruction. Proposed learning instructional activities were formulated based on the findings of the study.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".