Bibliographic record
Abstract
Advancement and evolution of different kinds of gadgets, mobile phones, laptops and computers are highly appreciated by most of the students today. These become effective tools to enhance their motivation and active engagement inside the classroom. However, these also change the continuity of lesson because students confine themselves in using gadgets and playing mobile games at home. Decline in students’ performance becomes visible. In educational system where technology cannot be withdrawn, an intensive effort of a teacher to integrate it constructively can revamp technology as an effective tool for learning. With this explosive space of change and development, the researcher decided to check out the effectiveness of video as a tool for learning in a form of video-aided selfreflection in teaching Biology. The study used quasi-experimental research design. The participants of this study were 100 Grade 8 students from two different sections handled by the researcher in the School Year 2018-2019. A researcher- made pre-test was steered out to the controlled group and experimental group at the beginning of the fourth quarter. Controlled group used traditional means of self-reflection while the experimental group used video-aided self-reflection. At the end of the quarter the same test was administered to both controlled and experimental group. Mean, standard deviation and t-test were used as statistical tools to navigate the results of the study. Findings revealed that both groups showed differences in their score implying that they had different level of performance in Biology after the utilization of video-aided self-reflection. This revealed that the use of video-aided selfreflection was an effective pedagogical tool in teaching Biology.
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 | 0.003 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".