Exploring the Data Learning Domain in Turkish Grade 1–8 Mathematics Textbooks An Analysis of the Data Investigation Cycle (PPDAC) and Levels of Cognitive Demand

This study examines tasks in the “data” strand of Turkish Grades 1–8 mathematics textbooks within the frameworks of the “data investigation cycle” (problem formulation, data collection, data analysis, conclusion) and “cognitive demand levels” (memorization, procedures without/with connections, doing mathematics). Eight textbooks approved by the Ministry of National Education were analyzed using a basic content-analytic approach. The findings show that the “data analysis” component is dominant across all grade levels, whereas the “problem formulation”, data collection” and “conclusion-drawing” components are largely limited. In terms of cognitive demand, tasks predominantly fall under “procedures with connections.” The intersectional analysis of data-investigation components × cognitive-demand tasks indicates that higher-order “doing mathematics” tasks are concentrated mainly within “problem formulation” and “data collection,” whereas the “data analysis” and “conclusion-drawing” components remain mostly at the “procedures with connections” level. No concentration at the “memorization” level was observed in any component. The results call for redesigning the data strand across all grade levels to ensure a balanced representation of the PPDAC (Problem, Plan, Data, Analysis, Conclusion) cycle; shifting from passive data reception to student-generated, real-data collection; increasing productive representation tasks and prediction-generalization-based inference; and strengthening higher-order reasoning at the “doing mathematics” level. In addition, it is recommended that this transformation be validated through classroom-based implementations and that comparative analyses across publishers and years test the continuity and generalizability of the observed patterns.