Enhancing students’ understanding of numerical sequences through real-life contexts and python programming

This study examines the impact of contextualized instruction supported by Python programming on students’ understanding of numerical sequences in upper secondary education. The research was conducted using a quasi-experimental pretest-posttest design with 48 informatics-profile students at IAAP “Andrea Durrsaku” in Kamenica, including an experimental group (n = 25) and a control group (n = 23), without random assignment. A mixed-methods approach was employed to combine quantitative results with qualitative insights into students’ engagement and learning processes. The experimental group engaged in real-world, Python-supported contextual tasks, while the control group followed traditional instruction.  AI-assisted tools were introduced only during the post-test phase for the experimental group as supportive resources for code generation. Data were collected using pre-tests and post-tests, open-ended student questionnaires, and structured observation sheets. The data were analyzed using SPSS, and the results were subsequently described and interpreted. The results revealed a statistically significant effect of the instructional intervention on students’ post-test performance after controlling for pre-test differences. The experimental group significantly outperformed the control group and demonstrated a large effect size (F(1, 45) = 32.370, p < .001, Partial Eta Squared = .418). Students also demonstrated improved abilities in pattern recognition, constructing general terms, and interpreting results, along with increased engagement and participation in learning activities. Overall, the findings suggest that integrating contextualized learning with programming-based support can enhance students’ conceptual understanding of numerical sequences.