Gamified flipped learning in a programming language course

The aim of this research is to investigate the impact of teaching the Python programming language within the 9th-grade elective Computer Science curriculum using the Gamified Flipped Learning Model (GFLM) on students' academic achievement. A mixed-methods research design, which incorporates both quantitative and qualitative data collection methods, was used in this study. The sample of the research consists of 175 9th-grade students studying at a project school. Of these participants, 89 were assigned to the experimental group and 86 to the control group using cluster sampling, with clustering done at the class section level. During the implementation process, the experimental group students used the Gamified Flipped Learning Model (GFLM) environment, while the control group students only used the Flipped Learning Model (FLM) environment. The study data were collected over a 12-week period within one term. Data collection tools included a Pre-Achievement Test, two Academic Achievement Tests (AAT), and a structured student opinion form. Additionally, Online End of Module Evaluation Tests (OEMET) were administered to both groups every week. Academic Achievement Tests (AAT) were used to determine learning success. The collected quantitative data were analyzed using independent samples t-test and Pearson correlation test in the SPSS program. The findings showed that students who experienced the GFLM had higher achievement test scores. It was found that the scores obtained from the OEMET by the students who experienced with GFLM had a significant impact on the second AAT 2. Furthermore, students in the experimental group who experienced with GFLM expressed positive opinions regarding the use of gamification elements. These findings highlight that gamification elements and OEMET are effective in increasing student success. It is recommended that these findings be considered for more effective planning of the use of GFLM in programming instruction.