Behavioral Factors Affecting the Performance of Grade 2 Learners in the New Normal Setting
Bibliographic record
Abstract
This study aimed to determine the learners’ academic performance and the learners’ behavior. The respondents of the study were 49 grade 2 pupils and parents of Lanipao Elementary School. No sampling procedure was considered. Only 1 parent or guardian served as a respondent for every child or learner enrolled in school year 2021-2022. On the other hand, the grade 2 learners’ academic performance in the second quarter was considered. The study sought to answer the parents’ profile in terms of sex, age, parents’ educational attainment, languages/dialects used/spoken at home, and parent’s monthly income, the behavior of the learners in terms of learning behavior, management behavior, and emotional behavior, and the academic performance of the learners. The researcher utilized a researcher-made questionnaire in the data collection process. Contents of the 30-item questionnaire were under survey type. The gathered data were tabulated and analyzed using the following statistical tools, mean and percentage, Spearman rho, Chi-square, and Pearson-r Correlation Coefficient. The study entailed that the parents’ demographic profile was not associated with the learners’ academic performance. Thus, the null hypothesis of no significant relationship between the parents’ profile and learners’ academic performance was not rejected. Furthermore, the academic performance of the learners was unrelated to their learning behavior, management behavior, and emotional behavior. Thus, the null hypothesis of no significant relationship between the level of learners’ behavior and their academic performance was not rejected. An action plan was drawn 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".