Student Health And Attendance Data

This dataset provides insights into the health, attendance, and overall well-being of college students. It combines biometric data (stress levels, sleep patterns, anxiety, and mood scores) with class attendance information to assess the relationship between student health and academic performance. The dataset is designed for studying and analyzing factors that influence student engagement and risk levels in an educational setting.

Key Features:
Student ID: A unique identifier for each student.
Date: The date of the class for which attendance and health data were recorded.
Class Time: The time range for the class session attended by the student.
Attendance Status: The student's attendance status for the day (e.g., 'Present,' 'Absent,' 'Late').
Stress Level (GSR): A measurement of the student's stress level, derived from Galvanic Skin Response (GSR), a physiological indicator of stress.
Sleep Hours: The number of hours the student slept on the night before the class, reflecting the quality of rest.
Anxiety Level: A subjective measure of the student's anxiety, rated on a predefined scale.
Mood Score: A score representing the student's mood, indicating their emotional state during the class session.
Risk Level: A categorization of the student’s health and engagement risk (e.g., 'Low,' 'Medium,' 'High'), based on the combination of attendance and biometric indicators.