This study examined whether an interdisciplinary English-science curriculum could improve primary school students' English proficiency and scientific inquiry skills while identifying practical challenges associated with implementation. A mixed-methods action research design was adopted across three urban primary schools in Xi'an. The quantitative strand used a quasi-experimental pre-test-post-test design involving 300 students: 150 students in experimental classes and 150 students in control classes. Experimental classes received interdisciplinary teaching that connected English language use with scientific concepts, inquiry tasks, experimental design, and data analysis, whereas control classes continued with traditional English and science instruction. Paired-sample t-tests were used to evaluate within-group changes. The experimental groups showed substantial gains in English scores across the three schools, increasing from 72.3 to 85.2, 71.9 to 84.5, and 73.4 to 83.8, respectively (t = 12.67-14.12, p = .001). Scientific inquiry scores also increased from 73.5 to 87.1, 72.0 to 86.2, and 73.2 to 85.4 (t = 13.34-15.20, p = .001). Improvements in control classes were much smaller. Qualitative analysis of teacher interviews, classroom observations, and student reflection logs identified three implementation themes: the importance of cross-subject teacher collaboration, constraints in teaching resources and planning time, and strong student engagement with authentic real-world tasks. Students generally reported greater interest and perceived relevance, although some experienced difficulty balancing English language demands with scientific content. The findings suggest that carefully designed interdisciplinary curriculum can simultaneously strengthen language application and scientific inquiry, but sustainable implementation requires structured collaboration, appropriate scaffolding, and institutional resource support.
Çoban, Z., & Selvi, B. (2023). An interdisciplinary approach to secondary school English curriculum.
Cui, Y. (2023). Optimizing decision trees for English teaching quality evaluation (ETQE) using artificial bee colony (ABC) optimization. Heliyon, 9(8), e19274.
DelliCarpini, M. (2009). Dialogues across disciplines: Preparing English-as-a-second-language teachers for interdisciplinary collaboration, 11(2).
Demir, K., & Güraks?n, G. E. (2022). Determining middle school students' perceptions of the concept of artificial intelligence: A metaphor analysis. Participatory Educational Research, 9(2), 297-312.
Dolapç?o?lu, S., & Bolat, Y. (2020). An action research study on developing an interdisciplinary curriculum in inclusive education. Education and Science, 45(204), 345-369.
Ji, S., & Tsai, S.-B. (2021). A study on the quality evaluation of English teaching based on the fuzzy comprehensive evaluation of bat algorithm and big data analysis. Mathematical Problems in Engineering, 2021, 1-12.
Kanmaz, A. (2022). A study on interdisciplinary teaching practices: Primary and secondary education curricula. African Educational Research Journal, 10(2), 200-210.
Keller, C. (2023). Collaborating outside of the silo: An action research study of interdisciplinary collaboration of teachers at a small suburban middle school in the Northeast.
Leahey, L. K. (1999). An interdisciplinary approach to integrated curriculum.
Liao, Q. (2023). English teaching project quality evaluation based on deep decision-making and rule association analysis. Journal of Combinatorial Mathematics and Combinatorial Computing, 118, 119-127.
Liu, K., Dong, T., & Chen, S. (2024). Fuzzy instructional assessment model and algorithm based on back propagation neural network. Computer-Aided Design & Applications, 21(S10), 181-195.
McPhail, G. (2017). Curriculum integration in the senior secondary school: A case study in a national assessment context. Journal of Curriculum Studies, 50(1), 56-76.
Mohammad, S., Alshebel, M., Al Oraini, B., Vasudevan, A., Mohammad, S., Jiang, H., & Al Sarayreh, A. (2024). Research on multimodal college English teaching model based on genetic algorithm. Data & Metadata, 3, 421.
Munkebye, E., Scheie, E., Misund, S., Gabrielsen, A., Øyehaug, A., Jordet, A., & Nergård, T. (2021). Interdisciplinary primary school curriculum units for sustainable development.
Song, X., Mak, J., & Chen, H. (2025). Teachers' and learners' perceptions about implementation of AI tools in elementary mathematics classes. SAGE Open, 15(2).
U?tu, H., Saito, T., & Menti? Ta?, A. (2021). Integration of art into STEM education at primary schools: An action research study with primary school teachers. Systemic Practice and Action Research, 35(2), 253-274.
Wang, H.-H., Charoenmuang, M., Knobloch, N. A., & Tormoehlen, R. L. (2020). Defining interdisciplinary collaboration based on high school teachers' beliefs and practices of STEM integration using a complex designed system. International Journal of STEM Education, 7(1).
Zhang, H., & Wang, J. (2023). A smart knowledge discovery system for teaching quality evaluation via genetic algorithm-based BP neural network. IEEE Access, 11, 53615-53623.
Zulkarnain, N., & Md, M. (2023). Primary teachers' perspectives on using artificial intelligence technology in English as a second language teaching and learning: A systematic review. International Journal of Academic Research in Progressive Education and Development, 12(2), 861-875.
Wang, Z., & Jamaludin, K. A. (2026). Interdisciplinary English-Science Curriculum and the Development of English Proficiency and Scientific Inquiry Skills among Primary School Students: A Mixed-Methods Action Research Study. International Journal of Academic Research in Business and Social Sciences, 16(7), 781-793.
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