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Synthetic Online Course Engagement Dataset
Education & Learning Analytics
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£79.99
About
This synthetic online course engagement dataset has been created as an educational resource for data science, machine learning, and education analytics applications. The data focuses on learners’ engagement with online courses, including time spent, quizzes taken, and completion rates. It is designed to help users analyze patterns of online learning behaviour, assess factors influencing course completion, and build predictive models for learner success.
Dataset Features:
- CourseCategory: Category of the course taken by the learner (e.g., "Programming," "Arts," "Health").
- TimeSpentOnCourse: Total time spent on the course (in hours).
- NumberOfVideosWatched: Total number of videos watched by the learner during the course.
- NumberOfQuizzesTaken: Number of quizzes attempted by the learner.
- QuizScores: Average score achieved on quizzes (out of 100).
- CompletionRate: Percentage of the course content completed by the learner.
- CourseCompletion: Whether the learner successfully completed the course (1 for completed, 0 for not completed).
Sample:
Usage:
This dataset is useful for a variety of applications, including:
Education Analytics: To explore how engagement metrics such as time spent and quizzes taken influence course completion.
Learner Behavior Analysis: To identify trends and patterns in learner engagement across different course categories.
Predictive Modeling: To develop models that predict course completion based on learner behaviour and performance.
Instructional Design: To optimize course content and structure by analyzing the relationship between engagement metrics and learner success.
Coverage:
This dataset is synthetic and anonymized, ensuring that it is safe to use for experimentation and learning without compromising any real learner data.
License:
CCO (Public Domain)
Who can use it:
- Data science enthusiasts: For learning and practising data manipulation, education analytics, and predictive modelling.
- Educators and researchers: For academic studies or teaching purposes in online education and learning engagement.
- E-learning professionals: For analyzing learner behaviour and improving course content, structure, and engagement strategies.
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