Authors : Raymund D. Rempillo; Danilo E. Despi

Volume/Issue : Volume 11 - 2026, Issue 3 - March

Google Scholar : https://tinyurl.com/mcrxjr4x

Scribd : https://tinyurl.com/2ekeyjtz

DOI : https://doi.org/10.38124/ijisrt/26mar1187

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : This study explored how artificial intelligence (AI) tools support teaching-related tasks (TRT) among teachers at Sorsogon National High School, including both Junior and Senior High School departments. Specifically, it examined teachers’ experiences in utilizing AI, the influence of these experiences on their performance of teaching-related tasks, their assessment of AI’s impact on instructional outputs, challenges encountered during use, and the implementation of schoolbased AI utilization guidelines aligned with DepEd policies. A qualitative research design was employed using in-depth interviews and focus group discussions (FGD) with twenty-five (25) teacher-participants. Data were analyzed through thematic analysis and organized according to the five Statements of the Problem (SOP). Findings revealed that teachers’ initial encounters with AI tools—primarily ChatGPT, Canva AI, and Microsoft Copilot—were informal and self-initiated, often driven by workload demands rather than institutional directives. AI was commonly utilized as a drafting and support tool in lesson planning and Daily Lesson Log preparation (DepEd Order No. 42, s. 2016), instructional material development, assessment drafting aligned with DepEd Order No. 8, s. 2015, and language editing. These experiences influence teachers’ organization of tasks, time management practices, instructional strategy selection, differentiated instruction, assessment alignment, and teaching confidence. Participants perceived improvements in the organization, clarity, and completeness of outputs, alongside reduced cognitive load and preparation stress when AIassisted drafts were carefully reviewed and contextualized. Despite these benefits, challenges were identified, including concerns regarding accuracy and reliability, the need for verification and extended editing, limitations in internet connectivity and device access, varying levels of prompting skills, and ethical considerations related to authenticity and responsible use. Teachers emphasized that AI should remain a supportive tool guided by professional judgment rather than a replacement for teacher expertise. The study highlights the importance of implementing structured, policy-aligned AI utilization practices supported through Learning Action Cell (LAC) initiatives and institutional support mechanisms. The findings suggest that AI integration can enhance teachingrelated tasks when grounded in ethical practice, teacher agency, and curriculum alignment within the Philippine secondary education context.

Keywords : Artificial Intelligence, Teaching-Related Tasks, Instructional Materials Develop, Daily Lesson Log, Assessment Preparation.

References :

1. Abrahamson, E. D. (2024). A student-focused critical analysis of Turnitin software: Understanding its role as a learning tool. Current Research Journal of Pedagogics, 5(10), 1–7.
2. Abdullah, M. R., & Arifin, I. (2024). School Administrative Staff: Duties and Responsibilities in Modern Education. Proceedings Series of Educational Studies, (4), 329-337.
3. Ahmad, S. F., Alam, M. M., Rahmat, M. K., Mubarik, M. S., & Hyder, S. I. (2022). Academic and administrative role of artificial intelligence in education. Sustainability, 14(3), 1101.
4. Aljemely, Y. (2024). Challenges and best practices in training teachers to utilize artificial intelligence: A systematic review. Frontiers in Education, 9, 1470853. https://doi.org/10.3389/feduc.2024.1470853
5. AI-Assisted Education Study. (2025). AI-assisted education: An investigation into its extent of use, teachers’ efficiency, and students’ performance (SY 2023–2024). https://journals.indexcopernicus.com/api/file/viewByFileId/2345600
6. Aldukhail, S. (2025). Mapping the landscape of generative language models in dental education: A comparison between ChatGPT and Google Bard. European Journal of Dental Education, 29(1), 136–148. https://doi.org/10.1111/eje.13056
7. Ali, D., Fatemi, Y., Boskabadi, E., Nikfar, M., Ugwuoke, J., & Ali, H. (2024). ChatGPT in teaching and learning: A systematic review. Education Sciences, 14(6), 643. https://doi.org/10.3390/educsci14060643
8. Ali, R., Tang, O. Y., Connolly, I. D., et al. (2023). Performance of ChatGPT, GPT-4, and Google Bard on a neurosurgery oral boards preparation question bank. Neurosurgery, 93(5), 1090–1098. https://doi.org/10.1227/neu.0000000000002551
9. Almalki, A., Althunibat, S., & Alrefaei, L. (2021). Artificial intelligence applications in education: A systematic review. International Journal of Emerging Technologies in Learning, 16(2), 4–18. https://doi.org/10.3991/ijet.v16i02.18091
10. Al Mashagbeh, M., Dardas, L., Alzaben, H., & Alkhayat, A. (2024). Comparative analysis of artificial intelligence-driven assistance in diverse educational queries: ChatGPT vs. Google Bard. Frontiers in Education, 9, 1429324. https://doi.org/10.3389/feduc.2024.1429324
11. Anggraeny, F. T., Wahanani, H. E., Akbar, A., Ilham, M., Raharjo, P., & Rizkyando, S. (2021). Peningkatan ketrampilan kreativitas desain grafis digital siswa SMU menggunakan aplikasi Canva pada ponsel pintar. JATTEC, 2(2).
12. Anggrini, R. P., Rahma, P., & Nurhatmi, J. (2025). Integration of artificial intelligent in Canva platform as innovative media for physics learning. Jurnal Edu Research, 6(1), 1554–1559.
13. Astaño, J. L. (2025). The effectiveness of Canva as an instructional tool in improving students’ academic performance: A meta-analysis. Journal of Digital Learning and Distance Education, 3(10), 1327–1345. https://doi.org/10.56778/jdlde.v3i10.468
14. Aydin, Ö. (2023). Google Bard generated literature review: Metaverse. Journal of AI, 7(1), 1–14.
15. Azaria, A. (2022). ChatGPT usage and limitations. ResearchGate. https://www.researchgate.net/publication/366618623_ChatGPT_Usage_and_Limitations
16. Balalle, H., & Pannilage, S. (2025). Reassessing academic integrity in the age of AI: A systematic literature review on AI and academic integrity. Social Sciences & Humanities Open, 11, 101299. https://doi.org/10.1016/j.ssaho.2025.101299
17. Bandura, A. (1997). Self-efficacy: The exercise of control. W.H. Freeman.
18. Chanpradit, T., Samran, P., Saengpinit, S., & Subkasin, P. (2024). English paraphrasing strategies and levels of proficiency of an AI-generated QuillBot and Paraphrasing Tool: Case study of scientific research abstracts. Journal of English Teaching, 10(2), 110–126. https://doi.org/10.33541/jet.v10i2.5619
19. Choiriyah, S., Ramadhan, S., Nugroho, A., & Muharom, F. (2025). Artificial intelligence-driven learning assessment in faculties of education: An exploratory study. Munaddhomah: Jurnal Manajemen Pendidikan Islam, 6(3), 482-495.
20. Citradevi, C. P. (2023). Canva sebagai media pembelajaran pada mata pelajaran ipa: seberapa efektif? sebuah studi literatur. Ideguru: Jurnal Karya Ilmiah Guru, 8(2), 270-275.
21. Celik, I., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: A systematic review of research. TechTrends, 66(4), 616–630. https://doi.org/10.1007/s11528-022-00715-y
22. Cope, B., Kalantzis, M., & Searsmith, D. (2021). Artificial intelligence for education: Knowledge and its assessment in AI-enabled learning ecologies. Educational Philosophy and Theory, 53(12), 1229–1245. https://doi.org/10.1080/00131857.2020.1728732
23. Corcuera, L. C. (2024). Uncovering QuillBot: Filipino senior high school students’ experiences and factors influencing its use in enhancing language writing skills. International Journal of Scholars in Education, 7(2), 67–81. https://doi.org/10.52134/ueader.1497368
24. Creswell, J. W., & Plano Clark, V. L. (2021). Designing and Conducting Mixed Methods Research (3rd ed.). SAGE Publications.
25. Dahri, N. A., Yahaya, N., Vighio, M. S., & Jumaat, N. F. (2025). Exploring the impact of ChatGPT on teaching performance: Findings from SOR theory, SEM and IPMA analysis approach. Education and Information Technologies, 30, 18241–18276. https://doi.org/10.1007/s10639-025-13539-z
26. Department of Trade and Industry. (n.d.). Artificial intelligence. https://innovate.dti.gov.ph/resources/roadmaps/artificial-intelligence/
27. Department of Education. (2022, May 10). DepEd highlights Digital Rise Program as key player in addressing challenges in education quality. GOVPH. https://www.deped.gov.ph/2022/05/10/deped-highlights-digital-rise-program-as-key-player-in-addressing-challenges-in-education-quality/
28. Department of Education. (2023). DepEd Order No. 016, s. 2023: Revised guidelines on the implementation of the Department of Education Computerization Program. https://www.deped.gov.ph/wp-content/uploads/DO_s2023_016.pdf
29. Department of Education. (2024). DepEd Order No. 002, s. 2024: Immediate removal of administrative tasks of public school teachers. https://www.deped.gov.ph/wp-content/uploads/DO_s2024_002.pdf
30. Dodigovic, M. (2013). The role of anti-plagiarism software in learning to paraphrase effectively. CALLEJ, 14(2), 23–37.
31. Dorgbefu, E. A. (2024). Investigating teacher and student perceptions of the impact of ChatGPT on higher education (Master’s thesis). Northern Illinois University. https://huskiecommons.lib.niu.edu/cgi/viewcontent.cgi?article=8882&context=allgraduate-thesesdissertation
32. Espartinez, A. S. (2024). Exploring student and teacher perceptions of ChatGPT use in Philippine higher education institutions. Discover Education. https://www.sciencedirect.com/science/article/pii/S2666920X24000675
33. Estrellado, C. J. P., & Miranda, J. C. (2023). Artificial intelligence in the Philippine educational context: Circumspection and future inquiries. International Journal of Scientific and Research Publications, 13(5), 16–22.
34. Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2024). A SWOT analysis of ChatGPT: Implications for educational practice and research. Innovations in Education and Teaching International, 61(4), 460–474.
35. Fernández, A. (2024). Integration of AI helping teachers in traditional teaching roles. European Public & Social Innovation Review, 9(1), 1–17. https://doi.org/10.31637/epsir-2024-664
36. Fernandez, A. M., & Marcelo, P. I. (2024). Impact of Motivation on Students’ Classroom Engagement. International Journal Of Advanced Multidisciplinary Studies (IJAMS), 4(5).
37. Fetters, M. D., & Molina-Azorin, J. F. (2022). Utilizing a mixed methods approach for strengthening research studies. Journal of Mixed Methods Research, 16(1), 3–10. https://doi.org/10.1177/15586898211019620
38. Fitria, T. N. (2022). Avoiding plagiarism of students’ scientific writing using the QuillBot paraphraser. Elsya: Journal of English Language Studies, 4(3), 252–262. https://doi.org/10.31849/elsya.v4i3.9917
39. Fitri, A. J., & Desyandri. (2023). Pengembangan bahan ajar IPAS menggunakan model problem-based learning berbasis aplikasi Canva di kelas IV sekolah dasar. https://dev-ojs.uin-suska.ac.id/index.php/elibtidaiy/article/view/36168
40. Funa, A. A., & Gabay, R. A. E. (2025). Policy guidelines and recommendations on AI use in teaching and learning: A meta-synthesis study. Social Sciences & Humanities Open, 11, 101221. https://doi.org/10.1016/j.ssaho.2024.101221
41. Gallup. (2025, June 24). Three in 10 teachers use AI weekly, saving six weeks a year. https://news.gallup.com/poll/691967/three-teachers-weekly-saving-six-weeks-year.aspx
42. Gan, Z., An, Z., & Liu, F. (2021). Teacher feedback practices, student feedback motivation, and feedback behavior: how are they associated with learning outcomes?. Frontiers in psychology, 12, 697045.
43. Garcia, P. D., Maghanoy, D. R. G., Ahmad, F. S. H., Manabat, A. D., & Arnoco, J. P. (2025). ChatGPT, Grammarly, and Quillbot: Perceptions of students and teachers towards the use of AI tools in writing. Journal of English Language Teaching and Applied Linguistics, 7(3), 161–172. https://doi.org/10.32996/jeltal.2025.7.3.161
44. Google. (2023a). An important next step on our AI journey. https://blog.google/technology/ai/bard-google-ai-searchupdates/
45. Google. (2023c). Bard updates. https://bard.google.com/updates
46. Göçen, A., & Aydemir, F. (2020). Artificial intelligence in education and schools. Research on Education and Media, 12(1), 13–21. https://doi.org/10.2478/rem-2020-0003
47. Grammens, M., Voet, M., Vanderlinde, R., Declercq, L., & De Wever, B. (2022). A systematic review of teacher roles and competences for teaching synchronously online through videoconferencing technology. Educational Research Review, 37, 100461.
48. Gruenhagen, J. H., Sinclair, P. M., Carroll, J. A., Baker, P. R., Wilson, A., & Demant, D. (2024). The rapid rise of generative AI and its implications for academic integrity: Students’ perceptions and use of chatbots. Computers and Education: Artificial Intelligence, 7, 100273. https://doi.org/10.1016/j.caeai.2023.100273
49. Guetterman, T. C., Fetters, M. D., & Creswell, J. W. (2023). Integrating quantitative and qualitative results in mixed methods research. Annals of Family Medicine, 21(2), 157–164. https://doi.org/10.1370/afm.2944
50. Guest, G., Namey, E., & Chen, M. (2020). A simple method to assess and report thematic saturation in qualitative research. PLoS ONE, 15(5), e0232076. https://doi.org/10.1371/journal.pone.0232076
51. Hao, K. (2023). ChatGPT goes to school: The impact of AI language models on teaching and learning. Educational Technology Research and Development, 71, 1123–1145. https://doi.org/10.1007/s11423-023-10140-0
52. Handriadi, H., Souza, F., & Lima, R. (2025). The Relationship Between the Use of Teaching Aids and Science Concept Understanding in Elementary School Students. International Journal of Educatio Elementaria and Psychologia, 2(2), 91-101.
53. Helbing, D. (2019). Societal, economic, ethical and legal challenges of the digital revolution: From big data to deep learning, artificial intelligence, and manipulative technologies. In D. Helbing (Ed.), Towards digital enlightenment (pp. 47–72). Springer. https://doi.org/10.1007/978-3-319-90869-4_6
54. Heckler, N. C., Rice, M., & Bryan, C. H. (2013). Turnitin systems. Journal of Research on Technology in Education, 45(3), 229–248.
55. Holmes, W., & Tuomi, I. (2022). State of the art and practice in AI in education. European Journal of Education, 57(4), 542–570. https://doi.org/10.1111/ejed.12533
56. Huang, H.-W., Li, Z., & Taylor, L. (2020). The effectiveness of using Grammarly to improve students’ writing skills. Proceedings of the 5th International Conference on Distance Education and Learning, 122–127.
57. Ilieva, G., Yankova, T., Ruseva, M., & Kabaivanov, S. (2025). A framework for generative AI-driven assessment in higher education. Information, 16(6), 472. https://doi.org/10.3390/info16060472
58. Isnaini, K. N., Sulistiyani, D. F., & Putri, Z. R. K. (2021). Design training using Canva application. Progressive Community Service Journal, 5(1), 291. https://doi.org/10.31764/jpmb.v5i1.6434
59. Jain, S., & Jain, R. (2019). Role of artificial intelligence in higher education—An empirical investigation. International Journal of Research and Analytical Reviews, 6(2), 144z–150z.
60. Koltovskaia, S. (2020). Student engagement with automated written corrective feedback (AWCF) provided by Grammarly: A multiple case study. Assessing Writing, 44, 100450. https://doi.org/10.1016/j.asw.2020.100450
61. Kolade, O., Owoseni, A., & Egbetokun, A. (2024). Is AI changing learning and assessment as we know it? Evidence from a ChatGPT experiment and a conceptual framework. Heliyon, 10, e25953. https://doi.org/10.1016/j.heliyon.2024.e25953
62. Kurniati, E. Y., & Fithriani, R. (2022). Post-graduate students’ perceptions of Quillbot utilization in English academic writing class. Journal of English Language Teaching and Linguistics, 7(3), 437–451. https://doi.org/10.21462/jeltl.v7i3.852
63. King, M. R. (2023). Can Bard, Google’s experimental chatbot based on the LaMDA large language model, help to analyze the gender and racial diversity of authors in your cited scientific references? Cellular and Molecular Bioengineering, 16(2), 175–179.
64. Li, P. H., Mayer, D., & Malmberg, L. E. (2024). Student engagement and teacher emotions in student-teacher dyads: The role of teacher involvement. Learning and Instruction, 91, 101876.
65. Li, Y., & Ni, A. (2022). Using AI tools to support teacher workload and lesson planning: Case studies from secondary schools. Journal of Educational Computing Research, 60(8), 1790–1812. https://doi.org/10.1177/07356331221085439
66. Lim, Z. W., Pushpanathan, K., Yew, S. M. E., et al. (2023). Benchmarking large language models' performances for myopia care: A comparative analysis of ChatGPT-3.5, ChatGPT-4.0, and Google Bard. eBioMedicine, 95, 104770. https://doi.org/10.1016/j.ebiom.2023.104770
67. Lozano, A., & Fontao, C. (2023). Is the education system prepared for the irruption of artificial intelligence? A study on the perceptions of students of primary education degree. Education Sciences, 13(733), 1–15. https://doi.org/10.3390/educsci13070733
68. Maleki, A., et al. (2025). Students’ views toward ethical challenges in online formative assessment. Discover Education. https://link.springer.com/article/10.1007/s44217-025-00445-2
69. Mallillin, L. L. D., Mallillin, J. B., Ampongan, Y. D., Lipayon, I. C., Mejica, M. M., & Burabo, J. Z. (2023). Instructional design for effective classroom Pedagogy of teaching. Eureka: Journal of Educational Research, 1(2), 41-52.
70. Melchor, P. J. M., Lomibao, L. S., & Parcutilo, J. O. (2023). Exploring the potential of AI integration in mathematics education for Generation Alpha—Approaches, challenges, and readiness of Philippine tertiary classrooms: A literature review. Journal of Innovations in Teaching and Learning, 3(1), 39–44. https://doi.org/10.12691/jitl-3-1-8
71. Meng, S. (2023). Enhancing teaching and learning: Aligning instructional practices with education quality standards. Research and Advances in Education, 2(7), 17-31.
72. Meo, S. A., Al-Khlaiwi, T., AbuKhalaf, A. A., Meo, A. S., & Klonoff, D. C. (2023). The scientific knowledge of Bard and ChatGPT in endocrinology, diabetes, and diabetes technology: Multiple-choice questions examination-based performance. Journal of Diabetes Science and Technology. https://doi.org/10.1177/19322968231203987
73. Morris, R., Perry, T., & Wardle, L. (2021). Formative assessment and feedback for learning in higher education: A systematic review. Review of Education, 9(3), e3292.
74. Mulyani, H., Istiaq, M. A., Shauki, E. R., Kurniati, F., & Arlinda, H. (2025). Transforming education: Exploring the influence of generative AI on teaching performance. Cogent Education, 12(1), Article 2448066. https://doi.org/10.1080/2331186X.2024.2448066
75. Nabhan, M., Rahayu, P. S., & Nor, H. (2021). Paraphrasing strategies in higher education. Proceedings International Conference on Education of Suryakancana. https://jurnal.unsur.ac.id/cp/article/view/1380
76. Nguyen, T. X. (2023). Using the online paraphrasing tool Quillbot to assist students in paraphrasing the source information: English-majored students’ perceptions. In Proceedings of the 5th Conference on Language Teaching and Learning (pp. 21–27). AIJR. https://doi.org/10.21467/proceedings.150.3
77. Nikolic, S., Daniel, S., Haque, R., Belkina, M., Hassan, G. M., Grundy, S., & Sandison, C. (2023). ChatGPT versus engineering education assessment: A multidisciplinary and multi-institutional benchmarking and analysis. European Journal of Engineering Education, 48(4), 559–614. https://doi.org/10.1080/03043797.2023.2234825
78. Oducado, R. M. F. (2019). Survey instrument validation rating scale. West Visayas State University, College of Nursing. Open Science Framework. https://osf.io/yzatc/download
79. Opara, E. C., Adalikwu, M. T., & Tolorunleke, C. A. (2023). ChatGPT for teaching, learning and research: Prospects and challenges. Global Academic Journal of Humanities and Social Sciences, 5(2), 33–40. https://doi.org/10.36348/gajhss.2023.v05i02.001
80. Philippine News Agency. (2021, June 24). Smart campus rises in Ilocos Norte. https://www.pna.gov.ph/articles/1144817
81. Philippine Information Agency. (2021, July 25). UNP adopts smart campus concept; receives P25M CHED grant. https://pia.gov.ph/news/2021/07/25/unp-adopts-smart-campus-concept-receives-p25m-ched-grant
82. Philippine Normal University. (2022). Teachers’ perceptions of AI-assisted instructional tools in Philippine secondary education. PNU Journal of Teacher Education, 12(1), 45–62.
83. Perdana, I., Manullang, S. O., & Masri, F. A. (2021). Effectiveness of online Grammarly application in improving academic writing: Review of experts experience. International Journal of Social Sciences, 4(1), 122–130. https://doi.org/10.31295/ijss.v4n1.1444
84. Pratschke, B. M. (2024). Generative AI and education: Digital pedagogies, teaching innovation and learning design. Springer Nature.
85. Prestoza, M. J. R., & Banatao, J. C. M. (2024). Exploring the efficacy of AI passion-driven pedagogy in enhancing student engagement and learning outcomes: A case study in Philippines. Asian Journal of Assessment in Teaching and Learning, 14(1), 45–54.
86. Rakhmanina, L., & Serasi, R. (2022). Utilizing Quillbot paraphraser to minimize plagiarism in students' scientific writing. Contemporary Issues in Education, Arts and Humanities, 26–33. http://novateurpublication.org/index.php/np/article/view/5
87. Rahaman, M. S., Ahsan, M., Anjum, N., Rahman, M. M., & Rahman, M. N. (2023). The AI race is on! Google’s Bard and OpenAI’s ChatGPT head to head: An opinion article. http://dx.doi.org/10.2139/ssrn.4351785
88. Rahayu, B. S., Hartinah, S., & Suriswo, S. (2024). Pengembangan modul ajar IPAS dengan model pembelajaran project based learning berbantu AI Canva pada siswa sekolah dasar. Journal of Education Research, 5(3). https://www.jer.or.id/index.php/jer/article/view/1502
89. Rahsepar, A. A., Tavakoli, N., Kim, G. H. J., Hassani, C., Abtin, F., & Bedayat, A. (2023). How AI responds to common lung cancer questions: ChatGPT vs Google Bard. Radiology, 307(5), e230922. https://doi.org/10.1148/radiol.230922
90. Romiszowski, A. J. (2024). Producing instructional systems: Lesson planning for individualized and group learning activities. Routledge.
91. Rudik, I. V., & Onyshchuk, I. Y. (2024). Artificial inteligence tools for developing educational resources: enhancing digital learning experience for teachers and learners.
92. Sallam, M. (2023). ChatGPT utility in healthcare education, research, and practice: Systematic review on the promising perspectives and valid concerns. Healthcare, 11(6), 887.
93. Sancar, R., Atal, D., & Deryakulu, D. (2021). A new framework for teachers’ professional development. Teaching and teacher education, 101, 103305.
94. Shi, L., Ding, A.-C., & Choi, I. (2024). Investigating teachers’ use of an AI-enabled system and their perceptions of AI integration in science classrooms: A case study. Education Sciences, 14(11), 1187. https://www.mdpi.com/2227-7102/14/11/1187
95. Stapleton, P. (2012). Gauging the effectiveness of anti-plagiarism software: An empirical study of second language graduate writers. Journal of English for Academic Purposes, 11(2), 125–133.
96. Su, J., & Yang, W. (2023). Unlocking the power of ChatGPT: A framework for applying generative AI in education. ECNU Review of Education, 6(3), 355–366. https://doi.org/10.1177/20965311231168423
97. Shi, L., Ding, A.-C., & Choi, I. (2024). Investigating teachers’ use of an AI-enabled system and their perceptions of AI integration in science classrooms: A case study. Education Sciences, 14(11), 1187. https://doi.org/10.3390/educsci14111187
98. Tan, X., Cheng, G., & Ling, M. H. (2025). 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
99. Tang, Y., & Ai, L. (2022). Exploring ChatGPT for differentiated instruction in secondary education. Computers & Education, 184, 104518. https://doi.org/10.1016/j.compedu.2022.104518
100. Tarraya, H. O. (2023). Teachers' Workload Policy: Its Impact on Philippine Public School Teachers (Public Policy Analysis and Review). Online Submission.
101. Tulo, N. B., & Lee, J. (2022). Continuing professional development of the teacher education faculty among philippine state universities and colleges. International Journal of Learning, Teaching and Educational Research, 21(6), 324-344.
102. U.S. Department of Education, Office of Educational Technology. (2023). Artificial intelligence and the future of teaching and learning: Insights and recommendations. https://www.ed.gov/sites/ed/files/documents/ai-report/ai-report.pdf
103. Umali, J. N. D. (2024). Artificial intelligence technology management of teachers and learner motivation in Calamba City private schools. International Journal of Multidisciplinary and Current Educational Research, 6(3), 82–88. https://www.ijmcer.com/wp-content/uploads/2024/06/IJMCER_MM0630821880.pd
104. Waisberg, E., Ong, J., Masalkhi, M., Zaman, N., Sarker, P., Lee, A. G., et al. (2023). Google’s AI chatbot “Bard”: A side-by-side comparison with ChatGPT and its utilization in ophthalmology. Eye, 38, 642–645. https://doi.org/10.1038/s41433-023-02760-0
105. Wong, Z. Y., & Liem, G. A. D. (2022). Student engagement: Current state of the construct, conceptual refinement, and future research directions. Educational Psychology Review, 34(1), 107-138.
106. Yuliani, Y., Kusrina, T., & Suriswo, S. (2025). Development of science learning modules with differentiated approach assisted by AI Canva human digestive system material to improve learning outcomes. Journal of English Language Education, 10(3). https://doi.org/10.31004/jele.v10i3.889
107. Zahara, S. L., Azkia, Z. U., & Chusni, M. M. (2023). Implementasi Teknologi Artificial Intelligence (AI) dalam Bidang Pendidikan. Jurnal Penelitian Sains Dan Pendidikan (JPSP), 3(1), 15-20.
108. 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), 1–39
109. Zheng, Q. (2021). Chinese university students’ perceptions of the use and effectiveness of Turnitin in EAP writing. International Journal of TESOL Studies, 3(2), 40–54. https://doi.org/10.46451/ijts.2021.06.04