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    Teaching and learning Mathematics using a translanguaging approach: Implications for productive STEM instruction
    (2025-01-01)
    Montana, Joveth Jay D.
    ;
    Lehao, Fernan B.
    ;
    Palayon, Raymund T.
    ;
    Braga, Albert A.
    In multilingual classrooms in the Philippines, particularly in content-based subjects, language often serves as both a tool and a barrier to learning. This study explored the communicative functions of translanguaging used by teachers and students in Senior High School, Mindanao State UniversityGeneral Santos Campus (MSU-GSC). Data were gathered through interviews with two mathematics teachers and a focus group discussion with students. The analysis revealed that teachers employed Cebuano and Filipino alongside English to explain complex concepts, translate mathematical terms, and promote classroom interaction. For students, translanguaging facilitated clearer expression of ideas, encouraged them to ask questions confidently, and fostered collaboration. The study concludes that translanguaging is an effective pedagogical approach in teaching mathematics in multilingual classrooms, enhancing comprehension while fostering inclusivity. Moreover, it reinforces meaningful teaching and learning of STEM subjects by creating an interactive learning space where students feel empowered to engage, participate, and express their ideas confidently.
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    Semantic Tagging of AI-Generated Science Texts to Identify Topics for Teaching STEM in K-12 Contexts
    (2025-01-01)
    Palayon, Raymund T.
    ;
    Amamio, Regie P.
    ;
    Chongchit, Yenying
    ;
    Chanthap, Naruethai
    As STEM education continues to play a crucial role in preparing students for future challenges, finding effective ways to improve its content and instructional delivery, especially in K-12 settings, requires ongoing attention and innovation. This study employed semantic tagging on AI-generated science texts to identify key semantic tags that can serve as topics for STEM instruction. Two datasets were analyzed using the English USAS semantic tagger and AntConc tool. The findings highlight topic-specific areas associated with animal and vegetable production (e.g., domestic animals, health and disease, farming and horticulture), increasing the students' perspectives on agricultural practices, technological applications, system designs, and mathematical knowledge. The semantic tags identified can inform and enrich STEM curriculum design, offering educators a data-driven approach to selecting relevant and appropriate content for K-12 instruction. Overall, this study provides steps to examine other STEM-related texts for the development of curriculum design from a linguistic approach.