The Relationship between Innovative Teaching Strategies and Student Engagement of Grades 6 Learners
Bibliographic record
Abstract
This study examined the effects of emerging teaching strategies on the academic performance, engagement, and perceptions of Grade 6 students at North Cabadbaran Central Elementary School, Cabadbaran City, Agusan del Norte, during the first quarter of the 2024–2025 academic year. Specifically, it explored four instructional approaches: collaborative learning, technology-enhanced learning, differentiated instruction, and gamification. Using a descriptive–correlational quantitative design, data were collected through student surveys that assessed engagement and perceptions of instructional methods. Results indicated a strong positive correlation (r = 0.82) between innovative teaching strategies and student engagement, with an average weighted mean of 4.68 for engagement and 3.99 for perceptions of strategy. Students expressed a clear preference for technology-enhanced learning, while collaborative learning strengthened teamwork and communication. The study recommends professional development programs for teachers, broader integration of technology, and the development of a unified instructional strategy guide. Overall, the findings confirm that modern pedagogical approaches have a significant impact on enhancing student engagement and academic outcomes.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".