Mobile-Assisted Case-Based Learning to Promote Creative Cognitive Flexibility and Deep Understanding in Physics - Tutut Nurita; Lia Yuliati; Arif Hidayat; An Nuril Maulida Fauziah; Muhamad Arif Mahdiannur; Ahmad Fauzi Hendratmoko (CV FOUNDAE, 2026)
Developing creative thinking in physics requires instructional approaches that encourage students to apply multiple problem-solving strategies and representations in authentic contexts. However, evidence on how mobile-assisted case-based learning promotes creative cognitive flexibility remains limited. This study investigated the contribution of mobile-assisted case-based learning to students’ creative cognitive flexibility as an indicator of deep conceptual understanding of ideal gas concepts. An explanatory sequential mixed-methods design was employed involving 70 undergraduate students who participated in a mobile-supported case-based learning intervention delivered through smartphones and a learning management system. Quantitative data were collected using pretest–posttest assessments of cognitive flexibility, while qualitative evidence was derived from students’ written responses to examine shifts in reasoning strategies and representational use. The findings indicate meaningful improvements in students’ creative cognitive flexibility following the intervention, accompanied by predominantly positive learning interest. Qualitative analyses further revealed that students became more capable of employing multiple solution pathways, integrating mathematical, graphical, and conceptual representations, and critically reflecting on the assumptions underlying ideal gas models. These findings suggest that mobile-assisted case-based learning provides an effective learning environment for fostering adaptive reasoning, strengthening deep conceptual understanding, and promoting creative thinking in undergraduate physics education. The study contributes empirical evidence supporting the integration of mobile technologies with authentic case-based pedagogy to advance higher-order thinking in digital science learning.