Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
ChatGPT Overreliance, Writing Skill Development, and Academic Integrity: Evidence from Senior High School Learners
0
Zitationen
7
Autoren
2026
Jahr
Abstract
This study aimed to determine the extent of practice of teaching strategies in science among public secondary school science teachers in District V-B, San Carlos City Division, during the School Year 2025–2026. Specifically, it assessed the extent to which selected teaching strategies—namely lecture method, laboratory experiments, demonstration method, inquiry-based learning, and cooperative learning—were practiced as perceived by teachers and school heads. The study also examined whether a significant difference existed between the perceptions of teachers and school heads regarding the extent of practice of these teaching strategies. Furthermore, it identified the degree of seriousness of the problems encountered by teachers in the implementation of teaching strategies in science. Based on the findings, an action plan was developed to strengthen and enhance the practice of effective science teaching strategies in public secondary schools. The findings revealed that the teaching strategies in science were practiced to a high to very high extent, as perceived by both teachers and school heads, with school heads generally rating the extent of practice higher than teachers. A significant difference was found between the perceptions of teachers and school heads regarding the extent of practice of teaching strategies in science. The problems encountered by teachers in implementing these strategies were rated as serious, with time constraints, insufficient budget, and lack of adequate laboratory equipment identified as the most pressing concerns. In response to these findings, an action plan was proposed to address the identified challenges and to further improve the extent and quality of teaching strategies in science instruction.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.339 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.211 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.614 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.478 Zit.