Learning process modeling phases from modeling interactions and eye tracking data
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摘要
The creation of a process model is a process consisting of five distinct phases, i.e., problem understanding, method finding, modeling, reconciliation, and validation. To enable a fine-grained analysis of process model creation based on phases or the development of phase-specific modeling support, an automatic approach to detect phases is needed. While approaches exist to automatically detect modeling and reconciliation phases based on user interactions, the detection of phases without user interactions (i.e., problem understanding, method finding, and validation) is still a problem. Exploiting a combination of user interactions and eye tracking data, this paper presents a two-step approach that is able to automatically detect the sequence of phases a modeler is engaged in during model creation. The evaluation of our approach shows promising results both in terms of quality as well as computation time demonstrating its feasibility.
论文关键词:Process of process modeling,Eye tracking,Interaction tracking,Automatic phase detection,Classification,Sequence labeling
论文评审过程:Received 17 July 2017, Revised 25 February 2019, Accepted 7 April 2019, Available online 10 April 2019, Version of Record 7 June 2019.
论文官网地址:https://doi.org/10.1016/j.datak.2019.04.001