This document discusses analyzing student behavior when watching interactive online courses. It presents the LIVE DataEvaluator, a Python application that generates visualizations of student interaction data from the iMoox online learning platform. The visualizations include tables of participant numbers, progress and certificates; viewership statistics; dropout rates; timestamps of student interactions; response times to questions; and changes in calculated attention levels. Diagrams then analyze retention, effectiveness, interactivity and attention over time. The goal is to better understand student engagement and learning experiences to improve online education.

1. SCIENCE
PASSION
TECHNOLOGY
Analysis of students’ behavior watching iMoox
courses with interactive elements
Daniel Dohr
9. November 2023
1

2. Motivation & Goals
• Importance of technology-enhanced learning
§ Interaction data
• Provide the means to improve education
§ Learning experience
2

3. Research Question
How can students’ behavior in interactive learning
videos be visualized and analyzed?
3

4. Background
• Attention & Interaction
• MOOCs
§ Education
• The LIVE Platform
§ Host Lectures
§ Gather Information
4

5. LIVE DataEvaluator
• Python Application
• Generates various Visualizations
• Command Line Interface
5

6. Evaluation – Tables
iMoox Course Data
§ Participants
§ Knowledge base
§ Progress & Improvement
§ Certificates
6
LIVE Data
§ Actual Viewership
§ Watch AVG

7. 7

8. Evaluation – Tables
iMoox Course Data
§ Participants
§ Knowledge base
§ Progress & Improvement
§ Certificates
8
LIVE Data
§ Actual Viewership
§ Watch AVG

9. Dropout Ratio
• Viewership status
• Skips
9

10. Interactions
• Timestamps
• Video Interactions
• Interest
10

11. Answer Delay
• Student answer times
• Violin and Box plots
• Kernel Density
11

12. Attention Change
• Calculated by LIVE
• Marked Interactions
12

13. Diagram Analysis
Retention and Effectiveness
• Dropout Diagram
• Answer Delay Diagram
13
Interactivity and Attention
• Interaction Diagram
• Attention Change Diagram

14. Conclusion
• Importance of good visualisations
• Improvements
• Future Work
14

15. Thank you for your attention!
15