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

Tayanch so‘z va iboralar: matematika, strategiya, miqdoriy va sifat ma’lumotlari, tahlil usullari, o‘quvchilar, matematik tushuncha, pedagogik vosita.

Introduction. Mathematics education is an essential component of the school curriculum, and its significance is widely recognized across cultures and nations [5, 6]. In recent years, there has been a growing interest in innovative and effective teaching strategies that can improve students’ mathematical learning outcomes [1, 7]. Data analysis (Data–driven instruction) has emerged as a promising pedagogical tool that can enhance students’ understanding of mathematics and develop their critical thinking skills and that can help relate mathematics with daily lives of the students [2]. Data analysis involves collecting, organizing, and analysing data to draw meaningful conclusions and make informed decisions. It provides a practical and engaging way to teach mathematical concepts and skills, particularly in areas related to statistics and probability.
This paper presents a case study of data analysis in middle school mathematics, with a focus on a Turkish classroom with 30 students. The study aimed to explore the effectiveness of data analysis as a teaching strategy in middle school mathematics and its impact on students’ understanding of the subject. The study used a mixed–methods approach, combining quantitative and qualitative data collection and analysis techniques. The paper is organized as follows:
The methods section provides an overview of the study design, data collection, and analysis techniques; the results section presents the findings of the study; the discussion section discusses the implications of the findings for mathematics education in the Republic of Türkiye and provides recommendations for future research and practice.
Methods. This study used a mixed–methods approach to investigate the effectiveness of data analysis as a teaching strategy in middle school mathematics. The study was conducted in a Turkish classroom with 30 students, aged between 12 and 14 years. The study design involved two phases: a pre–test phase and an intervention phase.
In the pre–test phase, a mathematics test was administered to all 30 students to assess their baseline understanding of the subject. The test consisted of 30 multiple–choice questions covering various topics in middle school mathematics, which were numbers & algebra, measurement & geometry, and statistics & probability. The test was designed to measure students’ mathematical knowledge, skills, and problem–solving abilities.
In the intervention phase, the students were divided into two groups: a treatment group and a control group. The treatment group received data–driven instruction, while the control group received traditional instruction in mathematics. The intervention phase lasted for four weeks, during which the treatment group was introduced to data analysis techniques and applied them to solve mathematical problems. The control group received traditional instruction in mathematics, focusing on the same topics covered in the treatment group.
Data were collected using several techniques, including pre– and post–tests, student interviews, and classroom observations. The pre–test and post–test data were analysed using descriptive statistics and inferential statistics: t–tests and ANOVA. The interview and observation data were analysed using thematic analysis.