Building Scientific Reasoning Using a Data Literacy Module in Higher Education - Shofiyah, Noly; Wulandari, Fitria Eka; Aulina, Choirun Nisak; Prihatiningtyas, Suci; Nisa’, Khoirun; Nuzula, Janatul Firdausi (International Journal of Research and Community Empowerment, 2025)
Scientific reasoning is a fundamental skill that must be developed in higher education, particularly in science-related disciplines. However, existing learning resources often lack an explicit focus on data interpretation and evidence-based analysis, both essential for scientific reasoning. This study aimed to develop and evaluate the validity, practicality, and effectiveness of a data literacy-based e-module designed to enhance undergraduate students’ scientific reasoning skills. Employing a design and development approach based on the ADDIE model, the research included analysis, design, development, implementation, and evaluation stages. The e-module was developed by aligning curriculum needs, scientific reasoning indicators, and core data literacy principles. Content and construct validity were assessed through expert reviews, yielding high validity scores (above 3.7) and strong reliability (α = 0.83-0.94). Small-scale trials with undergraduate science education students demonstrated high levels of learning activity (72%-94%) and consistent student engagement throughout the learning phases. Students' scientific reasoning improved significantly, with N-Gain scores ranging from 0.49 to 0.74, categorized as moderate to high, particularly in indicators such as proportional thinking. Statistical tests indicated no significant differences between class groups, suggesting consistent effectiveness across cohorts. Student feedback was overwhelmingly positive, with agreement levels reaching 100% on most evaluation indicators. This research contributes to the advancement of pedagogical design by integrating data literacy into the scientific reasoning process, offering a replicable learning resources that can be adapted across science disciplines to better prepare students for data-driven scientific inquiry in the digital era.