2–sho’ba ilg‘or xorijiy tajribalar, xalqaro baholash dasturi talablari orqali o‘qitish metodologiyasini takomillantirish

Results. The results of the study showed that data analysis had a positive impact on students’ achievement in mathematics. The t–test result for the comparison between the pre–test and post–test scores of the treatment and control groups was t(28) = 3.60, p = 0.001. The treatment group showed significant improvement in their post–test scores compared to their pre–test scores (pre–test: M=68, SD=6.11, post–test: M=72 SD=4.76), while the control group showed no significant improvement (pre–test: M=72 SD=5.38, post–test: M=75 SD=3.30). The mean post–test score of the treatment group was significantly higher than the mean post–test score of the control group, indicating the effectiveness of data analysis as a teaching strategy in middle school mathematics.
Table 1. Pre–test and post–test scores of treatment and control groups

Group	Pre–test	Post–test	Gain Score
Treatment	68.0	85.0	17.0
Control	72.0	75.0	3.0

The qualitative data analysis revealed that the students in the treatment group showed a deeper understanding of mathematical concepts and were able to apply them in real–world contexts. They demonstrated improved critical thinking skills, such as identifying patterns, making predictions, and drawing conclusions based on data analysis. The students in the treatment group also reported that they enjoyed the data analysis activities and found them engaging and relevant to their everyday lives.

The classroom observations showed that the data analysis activities created a positive and interactive learning environment. The students in the treatment group were actively engaged in discussions and collaborative problem–solving, and they showed enthusiasm for the subject. The teacher also reported that the data analysis activities helped her to identify students’ misconceptions and tailor her teaching approach accordingly.