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Bangladesh School-Level Student Age Data
Education & Learning Analytics
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About
Detailed insights into the age distribution of students across five secondary school classes (Class 6 to Class 10) in Bangladesh are provided. This information offers a structured representation of student populations by specific age groups, showing how students are distributed across different grades. It is a valuable resource for understanding trends related to student age, class progression, and potential dropout rates within Bangladesh's secondary education system. The data was collected in the year 2016.
Columns
- YEAR: The year the data was collected.
- DISTRICT: The district where the school is located.
- UPAZILA/THANA: The sub-district or police precinct within the district.
- EIIN: The Educational Institute Identification Number, a unique code for each school.
- INSTITUTE NAME: The name of the educational institution.
- CLASS_SIX_AGE_UNDER11: Number of Class 6 students under the age of 11.
- CLASS_SIX_AGE11: Number of Class 6 students aged 11.
- CLASS_SIX_AGE12: Number of Class 6 students aged 12.
- CLASS_SIX_AGE13: Number of Class 6 students aged 13.
- CLASS_SIX_AGE14: Number of Class 6 students aged 14.
- CLASS_SIX_AGE15: Number of Class 6 students aged 15.
- CLASS_SIX_AGE_UPER15: Number of Class 6 students over the age of 15.
- CLASS_SEVEN_AGE_UNDER11: Number of Class 7 students under the age of 11.
- CLASS_SEVEN_AGE11: Number of Class 7 students aged 11.
- CLASS_SEVEN_AGE12: Number of Class 7 students aged 12.
- CLASS_SEVEN_AGE13: Number of Class 7 students aged 13.
- CLASS_SEVEN_AGE14: Number of Class 7 students aged 14.
- CLASS_SEVEN_AGE15: Number of Class 7 students aged 15.
- CLASS_SEVEN_AGE_UPER15: Number of Class 7 students over the age of 15.
- CLASS_EIGHT_AGE_UNDER11: Number of Class 8 students under the age of 11.
- CLASS_EIGHT_AGE11: Number of Class 8 students aged 11.
- CLASS_EIGHT_AGE12: Number of Class 8 students aged 12.
- CLASS_EIGHT_AGE13: Number of Class 8 students aged 13.
- CLASS_EIGHT_AGE14: Number of Class 8 students aged 14.
- CLASS_EIGHT_AGE15: Number of Class 8 students aged 15.
- CLASS_EIGHT_AGE_UPER15: Number of Class 8 students over the age of 15.
- CLASS_NINE_AGE_UNDER11: Number of Class 9 students under the age of 11.
- CLASS_NINE_AGE11: Number of Class 9 students aged 11.
- CLASS_NINE_AGE12: Number of Class 9 students aged 12.
- CLASS_NINE_AGE13: Number of Class 9 students aged 13.
- CLASS_NINE_AGE14: Number of Class 9 students aged 14.
- CLASS_NINE_AGE15: Number of Class 9 students aged 15.
- CLASS_NINE_AGE_UPER15: Number of Class 9 students over the age of 15.
- CLASS_TEN_AGE_UNDER11: Number of Class 10 students under the age of 11.
- CLASS_TEN_AGE11: Number of Class 10 students aged 11.
- CLASS_TEN_AGE12: Number of Class 10 students aged 12.
- CLASS_TEN_AGE13: Number of Class 10 students aged 13.
- CLASS_TEN_AGE14: Number of Class 10 students aged 14.
- CLASS_TEN_AGE15: Number of Class 10 students aged 15.
- CLASS_TEN_AGE_UPER15: Number of Class 10 students over the age of 15.
Distribution
The data is provided in a single CSV file named
data_resource_2018_02_05_Student_By_Age.csv with a size of 2.21 MB. It contains 18,195 rows and 40 columns. It should be noted that many columns, particularly those for less common age groups in certain classes, have a high percentage of missing values.Usage
This information is ideal for analysing student enrolment patterns and demographic trends in Bangladesh's secondary schools. It can be used to study age-related factors in education, class progression, and dropout rates. Data scientists can employ this data to build predictive models for student retention and educational outcomes based on age distribution.
Coverage
The data covers secondary schools across 64 districts and 538 upazilas/thanas in Bangladesh for the year 2016. It focuses on the student population in Classes 6 through 10.
License
Attribution 4.0 International (CC BY 4.0)
Who Can Use It
- Educational Researchers: To study trends in student enrolment, age distribution, and dropout rates.
- Policymakers and Government Agencies: To identify regions or classes with high dropout rates and inform decisions to improve the education system.
- NGOs and Development Organisations: To design targeted interventions aimed at reducing dropout rates and enhancing student retention.
- Data Analysts: To perform demographic studies and calculate age-based enrolment trends for educational forecasting and budgeting.
- Machine Learning Practitioners: To build predictive models related to student retention and educational outcomes.
Dataset Name Suggestions
- Age Distribution of Secondary School Students in Bangladesh
- Bangladeshi Student Demographics: Class and Age Data
- Secondary Education Enrolment by Age in Bangladesh (2016)
- Bangladesh School-Level Student Age Data
- Classwise Age Distribution in Bangladeshi Schools
Attributes
Original Data Source:Bangladesh School-Level Student Age Data
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