Table 2 Summary of features.
From: Student dropout prediction through machine learning optimization: insights from moodle log data
Feature | Description |
|---|---|
max_consecutive_days_with_access | Maximum consecutive days the student accessed the course. |
max_consecutive_days_without_access | Maximum consecutive days the student did not access the course. |
first_log_days_diff | Amount of days passed between the start of the course and the student’s first log. |
max_consecutive_days_with_access_week | Maximum consecutive days in a week with course access. |
max_consecutive_days_without_access_week | Maximum consecutive days in a week without course access. |
logs | Total logs entries. |
week_logs | Amount of logs in a week. |
daily_avg | Average daily logs. |
weekly_avg | Average weekly logs. |
days_with_logs | Total days with log entries (indicating course activity). |
days_with_logs_avg | Average number of days with log entries (a measure of student engagement). |
days_with_logs_week | Total days with log entries (indicating course activity) in a week. |
days_with_logs_avg_week | Average number of days with log entries (a measure of student engagement) in a week. |
activity | Logs categorized as general activity. |
content | Logs categorized as content-related interactions. |
other | Logs that don’t fit into predefined categories. |
report | Logs related to report activities. |
system | Logs that reflect interaction with the system or platform. |
activity_week | Activity logs specific to each week. |
content_week | Content-related logs specific to each week. |
other_week | Logs categorized as ‘other’ for each week. |
report_week | Logs related to report activities for each week. |
system_week | System interaction logs specific to each week. |
course progress* | Indicates the course progress (week / total weeks) |
total_weeks* | Indicates the total of weeks |
