Flipped classroom learning model: It’s effect on the academic performance of science students in the distance learning
Bibliographic record
Abstract
This action research aims to assess the effect in the academic performance level of the SHS learners through the utilization of Flipped Classroom Learning Model in teaching earth and Life Science. Specifically, this inquiry aimed to: (1.) determine the competency-based performance levels of SHS learners in Earth and Life Science for the first quarter in the Learning Distance Modality; (2. ) find out the extent of acceptability of Flipped Classroom Learning Model interventions, innovation, and strategies to the improvement of learning outcomes in ELS in Distance Learning Delivery Modality and ;(3.) ascertain the effect of the implemented interventions, innovations, and strategies on the improvement of the learners’ academic performance in ELS. This study adopted the Descriptive-Evaluative method of research. It utilized descriptive survey questionnaire, and informal Interview. Purposive sampling design was used to determine the three hundred nineteen (319) students (males and females) from six Grade 11 classes of Don Servillano Platon Memorial National High School in Tinambac, Camarines Sur, Philippines. The data were analyzed and interpreted using mean, and frequency count. The data revealed that the competency-based performance levels of SHS learners in Earth and Life Science for the first quarter in the Distance Learning Delivery Modality was improved. The data for was generated from SF 9 and or SF10 of learners in for the first quarter. In line with the extent of acceptability of Flipped Classroom Learning Model interventions, innovations, and strategies to the improvement of learning outcomes in ELS in Distance Learning Delivery Modality gathered from the questionnaire in five-point Likert Scale have brought into varied rate. Most of the FCL interventions, innovations and strategies were highly accepted. However, the utilization of e- aklatan and e-assessment tool were accepted. These was accounted to the unstable internet signal in some remote areas.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".