Student migration trends in Kazakhstan: A dataset by settlement and region (2020-2024)

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief Pub Date : 2025-09-16 DOI:10.1016/j.dib.2025.112059

Anel Tarakbay, Alexander Pilipenko, Assel Duisengali

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引用次数: 0

Abstract

This data article presents a dataset on Kazakhstan's student migration within the country using the National Education Database (NEDB) for the years 2020-2024. The dataset includes transfers among schools for the country as a whole and year-by-year observations for the settlement type (urban or rural) and the region. To date, no publicly accessible datasets have been released at a comparable level of detail for educational mobility in Kazakhstan.

The data were derived from the NEDB, a centralized administrative system where educational organizations report student-level data in real time, which ensures the relevance of the data. The entered data are confirmed by electronic digital signatures of the heads of organizations, which ensuring their relevance. It contains detailed information about each student of the educational organization and their longitudinal education information. While raw data in NEDB presented are just administrative records, the student migration data were derived from these records. Using the mentioned longitudinal data, general migration trends by year (2020-2024), overall migration between regions, migration in high mobility areas, migration between rural and urban areas, migration trends by grade level of secondary school students were calculated. General migration trend data by year and overall migration data between regions can further be aggregated into bigger administrative units if needed.

This dataset was compiled as part of a broader research program on the education system of Kazakhstan that aims to forecast student enrollment, teacher requirements, and school infrastructure requirements. The gathered data also support school capacity planning, the evaluation of infrastructure burden, and determination of future demand for teachers and related educational resources.

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哈萨克斯坦学生移民趋势：基于居住地和地区的数据集（2020-2024年）

本文使用国家教育数据库（NEDB）提供了2020-2024年哈萨克斯坦国内学生移民的数据集。该数据集包括整个国家的学校之间的转移，以及对定居类型（城市或农村）和地区的逐年观察。到目前为止，还没有公开的数据集，详细程度与哈萨克斯坦教育流动性的数据集相当。这些数据来自NEDB，这是一个集中的管理系统，教育机构在该系统中实时报告学生水平的数据，从而确保了数据的相关性。输入的数据由各组织负责人的电子数字签名确认，确保其相关性。它包含了教育机构中每个学生的详细信息和他们的纵向教育信息。虽然NEDB中的原始数据只是管理记录，但学生迁移数据是从这些记录中导出的。利用上述纵向数据，计算了各年（2020-2024年）总体人口迁移趋势、区域间总体人口迁移趋势、高流动性地区人口迁移趋势、城乡人口迁移趋势、中学生各年级人口迁移趋势。按年划分的一般移民趋势数据和区域间的总体移民数据，如有需要，可以进一步汇总成更大的行政单位。该数据集是哈萨克斯坦教育系统更广泛研究计划的一部分，旨在预测学生入学率、教师需求和学校基础设施需求。收集到的数据还支持学校能力规划、基础设施负担评估以及确定未来对教师和相关教育资源的需求。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.