480 student records across three performance categories (Low, Medium, High) based on 16 behavioral and demographic features. The data tracks classroom engagement metrics such as hand-raising and resource visits alongside parental involvement indicators.
Use Cases
- Train a classification model to predict the 'Class' variable using behavioral features
- Examine the correlation between 'StudentAbsenceDays' and academic achievement
- Segment students based on engagement levels using 'VisitedResources' and 'Discussion' data
Strengths
- 480 individual student entries with 16 feature columns
- Behavioral tracking via 'raisedhands', 'VisitedResources', and 'AnnouncementsView'
- Target variable 'Class' with three distinct labels: L, M, and H
- Includes parental engagement metrics in 'ParentschoolSatisfaction' and 'ParentAnsweringSurvey' columns