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Analyzing engagement in a web-based intervention platform through visualizing log-data.

Cecily Morrison¹, Gavin Doherty

¹Engineering Design Centre, University of Cambridge, Cambridge, United Kingdom. cpm38@cam.ac.uk.

Journal of Medical Internet Research

|November 19, 2014

Summary

Visualizing user log data offers new insights into engagement with web-based interventions, aiding development and evaluation. This approach enhances understanding of user patterns and intervention effectiveness.

Keywords:

Web-based interventions data visualisation engagement log-data analysis

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Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective

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Published on: July 1, 2015

Area of Science:

Digital Health
Human-Computer Interaction
Data Science

Background:

Engagement is crucial for web-based interventions.
Rigor in designing these interventions is needed.
Log data can illuminate engagement patterns but requires organization.

Purpose of the Study:

Explore using log-data visualizations to understand engagement.
Enhance comprehension of user interaction with digital interventions.

Main Methods:

Applied exploratory sequential data analysis to log data.
Generated visualizations (Navigation Graph, Stripe Graph, etc.).
Examined visualizations for individual and cohort engagement using SilverCloud Platform data.

Main Results:

Presented four novel visualizations for user engagement.
Navigation Graph shows individual usage; others show cohort usage.
Examples illustrated salient features for two datasets.

Conclusions:

Data visualization of log data offers alternative insights into engagement.
Visualizations support intervention development and evaluation.
Enables analysis of usage patterns, usability, and real-time feedback.