Guiding the Digital Teacher: Mentors’ Perspectives on the Use of Artificial Intelligence in Interns’ Instructional Delivery

This phenomenological study examines mentors' perspectives on preservice teachers' (interns') use of artificial intelligence (AI) tools in instructional delivery during practicum in public schools under the DepEd Division of Bukidnon, Philippines. The study details mentors' views on AI in lesson planning, activities, and assessments. It also identifies challenges from AI reliance, including gaps in content depth, learner adaptation, and classroom dynamics. The study reviews strategies, feedback, and interventions to strengthen interns' pedagogical skills alongside AI. A qualitative design captured the lived experiences of 20 purposefully selected mentor teachers. Data were collected through a semi-structured questionnaire via Google Forms. Thematic analysis included transcription, coding, categorization, and theme development. Mentors observed that AI-enhanced lessons were more efficient and engaging, thanks to professional materials such as visuals, quizzes, and presentations. However, they found it hard to judge interns' real abilities because polished outputs often hid weaknesses in critical thinking, personal explanation, and live delivery. Key strategies were oral explanations, contextual adaptation, manual elements, creativity, and post-lesson reflection methods meant to balance technology with human skills. Mentors advised using AI as a preparation aid, not a classroom replacement, and emphasized qualities like empathy, improvisation, and learner connection that are irreplaceable. The study recommends that teacher education institutions and DepEd collaborate on ethical AI training. It also suggests revising practicum evaluations to focus on delivery over aesthetics, requiring AI disclosure and personalization, and creating peer forums to support human-centered teaching amid digital advances.

AI, supervision, practicum, instruction

1. Alreiahi, N. J., & Alrwaished, N. (2025). Integrating AI tools into preservice mathematics teacher education: A qualitative study of lesson planning practices. Contemporary Educational Technology, 17(4), ep617. https://doi.org/10.30935/cedtech/17549 [Google Scholar] [Crossref]

2. Antonio, R. (2025). Fostering preservice science teachers’ AI-Tpack competence and reflections through an AI-focused pedagogical learning course. Journal of Technology and Science Education, 15(3), 784. https://doi.org/10.3926/jotse.3693 [Google Scholar] [Crossref]

3. Bautista, A., Estrada, C., Jaravata, A. M., Mangaser, L. M., Narag, F., Soquila, R., & Asuncion, R. J. (2024). Preservice teachers’ readiness towards integrating AI-based tools in education: A TPACK approach. Educational Process: International Journal, 13(3), 40-68. https://doi.org/10.22521/edupij.2024.133.3 [Google Scholar] [Crossref]

4. Bower, M., Torrington, J., Lai, J. W. M., Petocz, P., & Alfano, M. (2024). How should we change teaching and assessment in response to increasingly powerful generative Artificial Intelligence? Outcomes of the ChatGPT teacher survey. Education and Information Technologies. https://doi.org/10.1007/s10639-023-12405-0 [Google Scholar] [Crossref]

5. Co, S. J. (2025). Artificial intelligence in Philippine education: A narrative review of applications, perceptions, and challenges. Zenodo (CERN European Organization for Nuclear Research). https://doi.org/10.5281/zenodo.15902950 [Google Scholar] [Crossref]

6. Cordevilla, P., Banot, L., & Velez, M. (2024). Generative AI: Perspectives of teaching interns. Science International-Lahore, 36(6), 665–675. https://www.researchgate.net/publication/387139654_GENERATIVE_AI_PERSPECTIVES_OF_TEACHING_INTERNS [Google Scholar] [Crossref]

7. Courtney, S. A., Austin, C. K., & Zolfaghari, M. (2023). International perspectives on teacher induction: A systematic review. Teaching and Teacher Education, 125, 104047. https://doi.org/10.1016/j.tate.2023.104047 [Google Scholar] [Crossref]

8. David, R. M. T., & Maroma, A. P. (2025). Exploring the Integration of ChatGPT in Pre-Service Teacher Education: Benefits, Challenges and Pedagogical Implications. International Journal of Multidisciplinary: Applied Business and Education Research, 6(3), 1333-1342. https://doi.org/10.11594/ijmaber.06.03.24 [Google Scholar] [Crossref]

9. Department of Education. (2026). Foundational guidelines on artificial intelligence in basic education (DO_s2026_003r 1). DepEd: Manila. https://www.deped.gov.ph/wp-content/uploads/DO_s2026_003r-1.pdf [Google Scholar] [Crossref]

10. Doğan, N. E. (2026). Pre-Service Teachers’ Attitudes towards the Use of AI Tools in Microteaching and Practicum Processes. SDU International Journal of Educational Studies, EFOK 2025 Special Issue. https://doi.org/10.33710/sduijes.1774195 [Google Scholar] [Crossref]

11. Fudalan, A. (2025). Can AI replace teachers? The value of Artificial intelligence in Philippine education. Philippine Journal of Educational Research and Development, 1(2), 45–62. https://ejournals.ph/article.php?id=30510 [Google Scholar] [Crossref]

12. Gravette, R. (2026, February 24). AI in the classroom: Supporting teachers without replacing humanity. Next Generation Learning Challenges. https://www.nextgenlearning.org/articles/ai-in-the-classroom-supporting-teachers-without-replacing-humanity [Google Scholar] [Crossref]

13. Hallström, J., Mannila, L., Nordlöf, C., Heintz, F., Sperling, K., & Stenliden, L. (2026). AI literacy for K–12 education: an international Delphi study. Interactive Learning Environments, 1–18. https://doi.org/10.1080/10494820.2026.2649553 [Google Scholar] [Crossref]

14. Lacuna, J. R. (2025). Exploring the readiness of pre-service teachers for AI integration in Philippine education. International Journal of Research and Innovation in Social Science. https://dx.doi.org/10.47772/IJRISS.2025.90300392 [Google Scholar] [Crossref]

15. Liu, Z., Hu, Y., & Zhang, Q. (2025). Harnessing Artificial intelligence for preservice teacher Development A scoping review of applications, benefits, and challenges [Dataset]. In Mendeley Data. https://doi.org/10.17632/8vvhgb5hgs.1 [Google Scholar] [Crossref]

16. Nguyen, N. (2024, July 1). AI and authentic assessment. FeedbackFruits. https://feedbackfruits.com/blog/ai-and-authentic-assessment [Google Scholar] [Crossref]

17. Pitso, A. R. M. (2026). Sustainable Mentorship Practices: Designing Frameworks That Blend AI Efficiencies with Human Intuition. Open Books and Proceedings. https://doi.org/10.38140/obp4-2026-10 [Google Scholar] [Crossref]

18. Rodrigo, M. M. T. & Talandron-Felipe, M. M. P. (2024). Using artificial intelligence to support basic education teachers in Under-resourced Contexts. University of the Philippines Center for Integrative and Development Studies. https://cids.up.edu.ph/wp-content/uploads/2024/12/Rodrigo_UPCIDS_Using-Artificial-Intelligence-to-Support-Basic-Education-Teachers-in-Under-resourced-Contexts.pdf [Google Scholar] [Crossref]

19. Rokkones, R. K., & Giannakos, M. (2025). Toward hybrid teaching intelligence: investigating the potential of teacher–AI collaboration using large language models. Behaviour and Information Technology, 1–19. https://doi.org/10.1080/0144929x.2025.2564368 [Google Scholar] [Crossref]

20. Seufert, S., Hartmann, P., & Spirgi, L. (2025). Fostering Intelligent-TPACK through AI-assistance: A multi-method study in pre-service teacher education. Computers and Education Open, 9, 100314. https://doi.org/10.1016/j.caeo.2025.100314 [Google Scholar] [Crossref]

21. Tan, X., Cheng, G., & Ling, M. H. (2024). Artificial intelligence in teaching and teacher professional development: A systematic review. Computers and Education Artificial Intelligence, 8, 100355. https://doi.org/10.1016/j.caeai.2024.100355 [Google Scholar] [Crossref]

22. UNESCO. (2026). Artificial intelligence in education. UNESCO. https://www.unesco.org/en/digital-education/artificial-intelligence [Google Scholar] [Crossref]

23. United States Artificial Intelligence Institute. (2025, October 6). Part 1: AI in Education, Classroom Integration, and Impact in 2026. https://www.usaii.org/ai-insights/ai-in-education-classroom-integration-and-impact-in-2026. https://www.usaii.org/ai-insights/ai-in-education-classroom-integration-and-impact-in-2026 [Google Scholar] [Crossref]

24. Zawacki Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – Where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 1–27. https://doi.org/10.1186/s41239-019-0171-0 [Google Scholar] [Crossref]

• The Role of Artificial Intelligence in Revolutionizing Library Services in Nairobi: Ethical Implications and Future Trends in User Interaction
• ESPYREAL: A Mobile Based Multi-Currency Identifier for Visually Impaired Individuals Using Convolutional Neural Network
• Comparative Analysis of AI-Driven IoT-Based Smart Agriculture Platforms with Blockchain-Enabled Marketplaces
• AI-Based Dish Recommender System for Reducing Fruit Waste through Spoilage Detection and Ripeness Assessment
• SEA-TALK: An AI-Powered Voice Translator and Southeast Asian Dialects Recognition