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University Student Retention and Demographics Peru
Education & Learning Analytics
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About
Student enrolment records from a Peruvian university for the academic year 2023 form the core of this collection. The data captures a wide array of academic, financial, and demographic indicators useful for analysing higher education trends in Peru. Key metrics include tuition payment status for both 2022 and 2023, study modality preferences (on-site, online, remote), and student retention categories such as new enrolments, re-entries, and reinstatements.
The dataset is particularly valuable for educational institutions and analysts looking to understand factors influencing student retention, the popularity of specific academic programmes like Law (Derecho) and Architecture, and the financial behaviour of the student body. Users should note that the data contains inconsistencies, particularly within the gender column (mixed formats such as 1, 2, M, F, U) and missing values in institutional background fields, necessitating data cleaning and transformation prior to in-depth analysis.
Columns
- ENROLLMENT: Categorises the student status (e.g., Re-enrolled, New, Reinstated).
- TUITION PAYMENT MARCH 2022: Binary indicator (0/1) of whether tuition was paid in March 2022.
- TUITION PAYMENT MARCH 2023: Binary indicator (0/1) of whether tuition was paid in March 2023.
- GENDER: Student gender identity, currently requiring standardisation (values include M, F, U, 1, 2).
- PROGRAM/MAJOR: The specific academic discipline the student is studying.
- SHIFT/SCHEDULE: The time block for classes (Morning, Afternoon, Night, Mixed).
- STUDY MODE: The modality of attendance (On-site, Online, Remote, To be determined).
- AGE RANGE OF ENROLLED STUDENT: Categorical age brackets (e.g., 21-23, 24-29).
- DEPARTMENT: Geographic department of residence or study (e.g., Lima, Arequipa).
- PROVINCE: Geographic province of residence or study.
- DISTRICT: Specific district of residence or study.
- TYPE OF EDUCATIONAL INSTITUTION: Origin institution type (e.g., School, Institute).
- INSTITUTION STATUS: Funding status of the origin institution (Public or Private).
- BENEFIT DISCOUNTS: Flags if the student receives financial aid or discounts.
- NUMBER OF ENROLLED COURSES: Total count of active courses per student.
- AT-RISK COURSE: Indicator of courses where the student is at risk of failure.
- CLASSIFICATION: Academic level classification (e.g., Undergraduate).
- CAMPUS: Physical campus location (e.g., UTP Lima Centro, UTP Arequipa).
- FACULTY: The academic faculty to which the student belongs (e.g., Engineering).
- DISABILITY: Boolean indicator of disability status.
- EDUCATIONAL INSTITUTION: Name of the previous educational institution attended.
Distribution
The dataset is provided in CSV format (peru_student_enrollment_data_2023.csv) with a file size of approximately 6.88 MB. It contains 37,600 valid records across 21 columns. The data structure is predominantly categorical and numerical, with significant concentrations in specific values; for instance, 92% of records represent re-enrolled students, and 54% of students are associated with the Lima department.
Usage
- Student Retention Analysis: Identify risk factors for dropout by correlating tuition payments and course load with enrolment status.
- Academic Planning: Assess demand for specific majors and study shifts (e.g., Night vs. Mixed) to optimise scheduling.
- Financial Forecasting: Analyse year-over-year tuition payment trends (March 2022 vs. March 2023).
- Data Cleaning Projects: An ideal resource for data science students to practise standardising inconsistent categorical data (gender, location).
- Demographic Studies: Explore the age and geographic distribution of university students in Peru.
Coverage
- Geographic: Focuses on Peru, with a heavy concentration in Lima (54%) and Arequipa (16%), covering various provinces and districts.
- Time Range: The primary focus is the academic year 2023, with historical payment reference data for March 2022.
- Demographic: University students aged primarily between 21 and 29, covering both genders and various socioeconomic backgrounds (indicated by school origin and benefit status).
License
CC BY-NC-SA 4.0
Who Can Use It
- University Administrators: For resource allocation and strategic planning.
- Educational Researchers: To study higher education trends in Latin America.
- Data Analysts: For building predictive models regarding student success and financial stability.
- Policy Makers: To understand regional disparities in access to private higher education.
Dataset Name Suggestions
- Peru Higher Education Enrolment 2023
- University Student Retention and Demographics Peru
- Peruvian Academic Enrolment & Financial Metrics
- UTP Student Enrolment Analysis 2023
Attributes
Original Data Source: University Student Retention and Demographics Peru
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