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Factors in Student Grades Dataset
Education & Learning Analytics
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About
This dataset provides a detailed view of factors influencing academic performance in high school students. It is designed for educational research, predictive modelling, and statistical analysis, offering insights into student demographics, study habits, parental involvement, and extracurricular activities. The dataset includes a target variable, GradeClass, which categorises students' grades, making it suitable for data science and machine learning projects.
Columns
- StudentID: A unique numerical identifier for each student, ranging from 1001 to 3392.
- Age: The age of students, spanning from 15 to 18 years.
- Gender: Coded as 0 for Male and 1 for Female.
- Ethnicity: Student ethnicity, coded as 0 for Caucasian, 1 for African American, 2 for Asian, and 3 for Other.
- ParentalEducation: Parents' education level, coded from 0 (None) to 4 (Higher).
- StudyTimeWeekly: Weekly study time in hours, ranging from 0 to 20.
- Absences: Number of absences during the school year, from 0 to 30.
- Tutoring: Tutoring status, where 0 indicates No and 1 indicates Yes.
- ParentalSupport: Level of parental support, coded from 0 (None) to 4 (Very High).
- Extracurricular: Participation in extracurricular activities, 0 for No and 1 for Yes.
- Sports: Participation in sports, 0 for No and 1 for Yes.
- Music: Participation in music activities, 0 for No and 1 for Yes.
- Volunteering: Participation in volunteering, 0 for No and 1 for Yes.
- GPA: Grade Point Average on a scale of 2.0 to 4.0, influenced by various factors.
- GradeClass: Classification of students' grades based on GPA: 'A' (GPA >= 3.5), 'B' (3.0 <= GPA < 3.5), 'C' (2.5 <= GPA < 3.0), 'D' (2.0 <= GPA < 2.5), 'F' (GPA < 2.0).
Distribution
This dataset contains information on 2,392 high school students, structured into 15 columns. It is typically available in a CSV file format. All columns have valid data with no missing values. This dataset is synthetic and was generated for educational purposes.
Usage
This dataset is ideal for:
- Educational Research: Analysing factors that contribute to student academic success.
- Predictive Modelling: Developing models to forecast student performance or grade classifications.
- Statistical Analysis: Exploring correlations between student attributes and academic outcomes.
- Data Science and Machine Learning Projects: Providing a robust foundation for various analytical tasks.
Coverage
The dataset focuses on high school students, aged 15 to 18 years. It includes demographic details such as gender and ethnicity, and provides insights into study habits, parental involvement, and participation in extracurricular activities. The specific geographic or time range of the data is not specified.
License
Attribution 4.0 International (CC BY 4.0)
Who Can Use It
- Academic Researchers: To study educational outcomes and factors influencing student achievement.
- Data Scientists and Machine Learning Engineers: For building and testing predictive models related to student performance.
- Educators and Policy Makers: To gain insights into student success and inform educational strategies.
Dataset Name Suggestions
- Academic Success Factors for High School Students
- Student Performance Analytics Dataset
- High School Academic Achievement Data
- Factors in Student Grades Dataset
Attributes
Original Data Source: Factors in Student Grades Dataset
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