Student Performance Patterns in Engineering at the University of Johannesburg: An Exploratory Data Analysis

Keyphrases

• Admission Point 16%
• Completion Rate 16%
• Correlation Analysis 16%
• Data Science 16%
• Dropout Rate 16%
• Educational Data Mining 16%
• Engineering Enrollment 16%
• Engineering Students 33%
• Exploratory Data Analysis 100%
• Female Students 33%
• Gender Disparities 16%
• Historical Data 16%
• Increased Demand 16%
• Performance Patterns 100%
• Performance Potential 16%
• Point Score 16%
• Potential Influencing Factors 16%
• Python 16%
• Real-time Data Analysis 16%
• Recent Advances 16%
• Science Data 16%
• Student Achievement 33%
• Student Dropout 16%
• Student Performance 100%
• Support Interventions 16%
• Understanding Students 16%
• University of Johannesburg 100%

Social Sciences

• Data Mining 14%
• Data Science 14%
• Dropout Rate 28%
• Engineering 100%
• Exploratory Data Analysis 100%
• Gender Disparity 14%
• Mathematics 14%
• Student Performance 100%
• Student Success 28%
• Women Students 28%

Chemical Engineering

• Correlation Analysis 100%