Learning Styles of Students Amidst Pandemic Vis-À-Vis Academic Performance in Science 10: A Basis For Proposed Intervention Plan
Bibliographic record
Abstract
This research looked upon the learning styles of selected Grade 10 students amidst pandemic vis-à-vis academic performance in science to have a basis for proposed intervention plan to better deliver science instructions for the best teaching and learning experiences where correlations of academic performance and learning styles of the respondents were analyzed. The result shows that majority of the respondents are auditory learners. There are very few kinesthetic learners. Most of the respondents got a Satisfactory level on their academic performance during the first quarter. While there was a noticeable increase in their academic performance during the second quarter where majority of the respondents got Very Satisfactory level. Learning style of the respondents significantly affect their academic performance. This implies that learning style correlates highly to the academic performance. This means that the learning style of the students is connected to their academic performance. Being aware of this, teachers can develop lessons and activities that suits well their learners learning styles. In this way, they are helping their students in developing their skills and increasing their academic performance.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".