STEAM Learning Integrating Deep Learning and Ethnomathematics to Improve Numeracy Literacy and Pancasila Student Profile

Improving numeracy literacy and character education aligned with the Pancasila Student Profile (P5) remains a key challenge in Indonesian education, particularly in remote areas. Conventional mathematics instruction often lacks contextual and cultural relevance, limiting student engagement and holistic development. This study implemented a STEAM (Science, Technology, Engineering, Arts, Mathematics) learning model integrating Deep Learning principles and Ethnomathematics to enhance numeracy and character development. Using a mixed-methods sequential exploratory design, the research was conducted with 28 ninth-grade students at SMPN 1 Masalembu. Qualitative data from observations, interviews, and reflections informed the development of quantitative instruments measuring numeracy literacy and P5 competencies. Quantitative analysis showed significant gains in numeracy literacy, with pre-test scores increasing from M = 42.80 (SD = 7.61) to post-test scores of M = 82.47 (SD = 6.32), t(27) = −27.58, p 0.001, with a large effect size (Cohen’s d = 5.21). Qualitative findings indicated that students engaged meaningfully and joyfully with mathematical concepts through culturally relevant tasks involving Sumenep batik motifs. Improvements were also observed in critical thinking, creativity, cooperation, and cultural appreciation. The integration of STEAM, Deep Learning, and Ethnomathematics effectively enhanced students’ cognitive and character outcomes. This model offers a promising, culturally responsive approach for mathematics instruction in remote and diverse educational settings, supporting the objectives of the Merdeka Belajar curriculum.