Higher Education Students Performance Evaluation
Donated on 8/14/2023
The data was collected from the Faculty of Engineering and Faculty of Educational Sciences students in 2019. The purpose is to predict students' end-of-term performances using ML techniques.
Dataset Characteristics
Multivariate
Subject Area
Social Science
Associated Tasks
Classification
Feature Type
Integer
# Instances
145
# Features
31
Dataset Information
For what purpose was the dataset created?
The purpose is to predict students' end-of-term performances using ML techniques.
Additional Information
1-10 of the data are the personal questions, 11-16. questions include family questions, and the remaining questions include education habits.
Has Missing Values?
No
Introductory Paper
By N. Yilmaz, B. Şekeroğlu. 2019
Published in Advances in Intelligent Systems and Computing, vol 1095
Variables Table
| Variable Name | Role | Type | Demographic | Description | Units | Missing Values |
|---|---|---|---|---|---|---|
| Student Age | Feature | Categorical | Age | 1: 18-21, 2: 22-25, 3: above 26 | no | |
| Sex | Feature | Binary | Sex | 1: female, 2: male | no | |
| Graduated high-school type | Feature | Categorical | Education Level | 1: private, 2: state, 3: other | no | |
| Scholarship type | Feature | Categorical | 1: None, 2: 25%, 3: 50%, 4: 75%, 5: Full | no | ||
| Additional work | Feature | Binary | 1: Yes, 2: No | no | ||
| Regular artistic or sports activity | Feature | Binary | 1: Yes, 2: No | no | ||
| Do you have a partner | Feature | Binary | Marital Status | 1: Yes, 2: No | no | |
| Total salary if available | Feature | Categorical | Income | 1: USD 135-200, 2: USD 201-270, 3: USD 271-340, 4: USD 341-410, 5: above 410 | no | |
| Transportation to the university | Feature | Categorical | 1: Bus, 2: Private car/taxi, 3: bicycle, 4: Other | no | ||
| Accomodation type in Cyprus | Feature | Categorical | 1: rental, 2: dormitory, 3: with family, 4: Other | no |
0 to 10 of 33
Additional Variable Information
Class Labels
Student ID 1- Student Age (1: 18-21, 2: 22-25, 3: above 26) 2- Sex (1: female, 2: male) 3- Graduated high-school type: (1: private, 2: state, 3: other) 4- Scholarship type: (1: None, 2: 25%, 3: 50%, 4: 75%, 5: Full) 5- Additional work: (1: Yes, 2: No) 6- Regular artistic or sports activity: (1: Yes, 2: No) 7- Do you have a partner: (1: Yes, 2: No) 8- Total salary if available (1: USD 135-200, 2: USD 201-270, 3: USD 271-340, 4: USD 341-410, 5: above 410) 9- Transportation to the university: (1: Bus, 2: Private car/taxi, 3: bicycle, 4: Other) 10- Accommodation type in Cyprus: (1: rental, 2: dormitory, 3: with family, 4: Other) 11- Mothers’ education: (1: primary school, 2: secondary school, 3: high school, 4: university, 5: MSc., 6: Ph.D.) 12- Fathers’ education: (1: primary school, 2: secondary school, 3: high school, 4: university, 5: MSc., 6: Ph.D.) 13- Number of sisters/brothers (if available): (1: 1, 2:, 2, 3: 3, 4: 4, 5: 5 or above) 14- Parental status: (1: married, 2: divorced, 3: died - one of them or both) 15- Mothers’ occupation: (1: retired, 2: housewife, 3: government officer, 4: private sector employee, 5: self-employment, 6: other) 16- Fathers’ occupation: (1: retired, 2: government officer, 3: private sector employee, 4: self-employment, 5: other) 17- Weekly study hours: (1: None, 2: <5 hours, 3: 6-10 hours, 4: 11-20 hours, 5: more than 20 hours) 18- Reading frequency (non-scientific books/journals): (1: None, 2: Sometimes, 3: Often) 19- Reading frequency (scientific books/journals): (1: None, 2: Sometimes, 3: Often) 20- Attendance to the seminars/conferences related to the department: (1: Yes, 2: No) 21- Impact of your projects/activities on your success: (1: positive, 2: negative, 3: neutral) 22- Attendance to classes (1: always, 2: sometimes, 3: never) 23- Preparation to midterm exams 1: (1: alone, 2: with friends, 3: not applicable) 24- Preparation to midterm exams 2: (1: closest date to the exam, 2: regularly during the semester, 3: never) 25- Taking notes in classes: (1: never, 2: sometimes, 3: always) 26- Listening in classes: (1: never, 2: sometimes, 3: always) 27- Discussion improves my interest and success in the course: (1: never, 2: sometimes, 3: always) 28- Flip-classroom: (1: not useful, 2: useful, 3: not applicable) 29- Cumulative grade point average in the last semester (/4.00): (1: <2.00, 2: 2.00-2.49, 3: 2.50-2.99, 4: 3.00-3.49, 5: above 3.49) 30- Expected Cumulative grade point average in the graduation (/4.00): (1: <2.00, 2: 2.00-2.49, 3: 2.50-2.99, 4: 3.00-3.49, 5: above 3.49) 31- Course ID 32- OUTPUT Grade (0: Fail, 1: DD, 2: DC, 3: CC, 4: CB, 5: BB, 6: BA, 7: AA)
Reviews
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset higher_education_students_performance_evaluation = fetch_ucirepo(id=856) # data (as pandas dataframes) X = higher_education_students_performance_evaluation.data.features y = higher_education_students_performance_evaluation.data.targets # metadata print(higher_education_students_performance_evaluation.metadata) # variable information print(higher_education_students_performance_evaluation.variables)
Yilmaz,Nevriye and Şekeroğlu,Boran. (2023). Higher Education Students Performance Evaluation. UCI Machine Learning Repository. https://doi.org/10.24432/C51G82.
@misc{misc_higher_education_students_performance_evaluation_856,
author = {Yilmaz,Nevriye and Şekeroğlu,Boran},
title = {{Higher Education Students Performance Evaluation}},
year = {2023},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.24432/C51G82}
}Keywords
Creators
Nevriye Yilmaz
nevriye.yilmaz@neu.edu.tr
Boran Şekeroğlu
boran.sekeroglu@neu.edu.tr
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.