<b>RESPONDING TO THE CHALLENGES OF TEACHING NOMENCLATURE OF COMPOUNDS THROUGH GENERATIVE ARTIFICIAL INTELLIGENCE INSTRUCTIONAL MATERIAL (GAIIM)</b>

Generative AI in education facilitates the creation of innovative materials, reshaping paradigms and promoting transformative shifts. This qualitative narrative study aimed to identify challenges encountered by senior high school chemistry teachers in Quezon Province in teaching the nomenclature of compounds and to develop and evaluate Generative Artificial Intelligence Instructional Material (GAIIM) to address the challenges. Nine chemistry teachers were purposively sampled and interviewed using a validated semi-structured questionnaire. For ethical considerations, informed consent was obtained, and alphanumeric codes were used. A 4-point Likert scale was utilized to assess the GAIIM's acceptability among 30 science teachers. Using Taguette, the qualitative data were analyzed, and it revealed that student diversity, lack of mastery, time constraints, and insufficient instructional materials are the challenges of teachers. In response, they adjust class schedules, provide diverse learning activities, and enhance discussions. The GAIIM was designed using Microsoft PowerPoint and Canva to address the identified problems and incorporate effective teaching-learning strategies relevant to the local context. Quantitative data analyzed using Jamovi indicated that the GAIIM is ideal, valid, and ready for classroom implementation. To enhance generalizability, it is recommended to increase the sample size, conduct experimental studies to assess GAIIM's effectiveness, and train teachers in creating GAIIM.