TEACHERS’ QUALITY IN KAZAKHSTANI RURAL SCHOOLS

This article is based on a large study that explored quality issues in Kazakhstani rural schools from the perspective of key stakeholders, including school leaders, teachers, students, parents, and education managers. As the understandings and approaches to education quality vary from one context to another, there is no universally agreed definition of quality education. We employed the UNESCO Quality Framework to guide this study—the framework that suggests to seeing the quality in four main domains of education: 1. Contexts / environments (physical, academic, psychological, and social atmosphere in schools); 2. Inputs (teachers, curriculum, leadership, and others); 3. Processes (teaching and learning, assessment, and other processes); 4. Outputs (students’ learning outcomes, teachers’ professional growth and others). Within the larger study, this article focuses on teachers’ quality only.
The investigation of previous literature and the study's theoretical framework demonstrate that the rural school education challenges greatly impact the conditions of rural teachers’ professional activity.
The study employed a mixed methods research design, including both quantitative and qualitative inquiries: survey and semi-structured interviews [1]. The quantitative survey included 125 respondents from 40 rural schools across Kazakhstan. For qualitative part, 90 interviews (41 individual and 49 focus group) were conducted with participants from rural schools in Almaty, Kyzylorda, South Kazakhstan, Mangystau, and East Kazakhstan regions. Interviewees included teachers, principals, vice principals, subject coordinators, students of Grades 7–11, regional and district education managers, and parents.
The study's main findings describe the core teachers' issues, challenges, perceptions, and suggestions about facilitation processes for the quality of the rural teacher profession. The findings are organized across the main topics, which have been retrieved from qualitative and quantitative data.

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