The Complexity of High School Students' Semiotic Graphics in Solving Statistical Problems - Ahmad Choirul Anam (Jurnal Multidisiplin Ibrahimy, 2025)
The ability to represent data graphically is a crucial skill in learning statistics, yet it involves complex semiotic processes that are often influenced by students’ cognitive styles. This study was conducted to explore the semiotic complexity of high school students’ statistical graphs about their cognitive styles: field dependent (FD) and field independent (FI). Using a descriptive qualitative approach, four 12th-grade students were selected based on the Group Embedded Figures Test (GEFT) and a standardized mathematics ability test to ensure cognitive style categorization and equal academic level. Data were collected through a Semiotic Graph Complexity Test (TKSG) and semi-structured interviews focusing on four semiotic components: problems, actions, concepts, and properties.The findings show that students with FI cognitive styles demonstrated a higher level of semiotic complexity, reaching the "joint graphs" level, characterized by coherent integration of data, appropriate graph selection, and accurate symbolic interpretation. In contrast, FD students exhibited lower levels of complexity, often limited to literal and superficial representations. These results confirm that cognitive styles significantly affect students’ abilities to transform statistical data into meaningful graphical representations. This study highlights the importance of differentiated instruction based on cognitive styles, suggesting explicit scaffolding for FD students and more explorative tasks for FI students to enhance graph comprehension and statistical literacy.