Using Eye-tracking to Detect Search and Inference During Process Model Comprehension
Type
conference paper
Date Issued
2024
Author(s)
Abstract
Understanding process models involves different cognitive processes. These processes typically manifest in users' visual behavior and thus can be captured using eye-tracking.
In this paper, we focus on the detection of two very essential behaviors: information search and inference. Using a set of eye-tracking features allowing to discern these two behaviors, we train several machine learning (ML) models to predict whether the user is involved in a search phase or an inference one. Following a cross-validation approach inspired by the leave-one-out method, our ML models attain 85% precision, 82% recall, and an F1 score of 80%. The outcome of this work enables the creation of novel adaptive systems, detecting whether the user is involved in a search or inference phase and accordingly providing adequate support. Moreover, it opens up new opportunities to better understand how different process model, tool, user and task-related factors affect users' search and inference behaviors.
In this paper, we focus on the detection of two very essential behaviors: information search and inference. Using a set of eye-tracking features allowing to discern these two behaviors, we train several machine learning (ML) models to predict whether the user is involved in a search phase or an inference one. Following a cross-validation approach inspired by the leave-one-out method, our ML models attain 85% precision, 82% recall, and an F1 score of 80%. The outcome of this work enables the creation of novel adaptive systems, detecting whether the user is involved in a search or inference phase and accordingly providing adequate support. Moreover, it opens up new opportunities to better understand how different process model, tool, user and task-related factors affect users' search and inference behaviors.
Keywords
Process model comprehension
eye-tracking
search behavior
inference behavior
machine learning
Book title
Cooperative Information Systems - CoopIS 2024
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Name
COOPIS2024___Supporting_Users_Engagement_with_Process_Models.pdf
Size
1.54 MB
Format
Adobe PDF
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