Exploring Teachers Perceptions in Learning in the Age of Artificial Intelligence
Abstract
Abstract Artificial Intelligence (AI) has becoming clearer in secondary education, influencing both teaching practices and student’s learning behaviors. This study is intended to explore teacher’s perceptions of learning in the age of Artificial Intelligence at Angono National High School. Particularly, it studied teachers’ ideas about AI, the commonly used AI tools, and their perceptions of Artificial Intelligence in terms of; accomplishing assignments, making reviewers, and explaining topics. The study used a qualitative case study research design. Three teachers handling Science, Mathematics, and English subjects participated in the study. The participants were selected through purposive sampling, as they regularly observe students’ use of Artificial Intelligence in school-related activities. Data were also gathered through interview questions and analyzed using thematic analysis to identify if there are patterns and themes in the teachers’ responses. The results of this study shows that teachers generally view AI as a useful educational tool when used properly. The commonly used AI identified by the teachers are Chat GPT and Gemini AI. Their responses noted that AI helps student complete assignments faster and effectively. However, they also said that they were concerned that students are becoming too dependent on AI, which might affect their ability to comprehend the lessons. They emphasize that Artificial Intelligence can support teaching and learning if it is used responsibly and under teachers’ supervision It emphasizes the need for clearer guidelines along side with better prompts to promote meaningful learning and responsible AI use in school. Teachers’ supervision helps students use Ai effectively and safely.
Fields of Study & Subjects
Artificial Intelligence in Education
Artificial Intelligence in Healthcare and Education
Educational Technology and Pedagogy
Publication details
- Journal / source
- Research Square
- Publication date
- 3 March 2026
- Language
- EN
- Document type
- Preprint