480 student records categorized by 16 demographic, academic, and behavioral features collected from a Learning Management System. The data tracks specific interactions such as 'raisedhands', 'VisITedResources', and 'AnnouncementsView' to predict academic performance across three classes: Low, Medium, and High.
Use Cases
- Predict student performance levels ('Class') using behavioral features like 'raisedhands' and 'VisITedResources'
- Analyze the correlation between parental involvement ('ParentschoolSatisfaction') and student academic success
- Identify the impact of student attendance on final grades using the 'StudentAbsenceDays' column
- Cluster students into engagement profiles based on 'Discussion' frequency and 'AnnouncementsView' counts
Strengths
- 480 rows of student data covering 16 distinct attributes including nationality and stage ID
- Includes four behavioral features: 'raisedhands', 'VisITedResources', 'AnnouncementsView', and 'Discussion'
- Categorical target variable 'Class' representing performance levels Low (0-69), Medium (70-89), and High (90-100)
- Captures parental engagement through 'ParentAnsweringSurvey' and 'ParentschoolSatisfaction' columns