Toward the incorporation of temporal interaction analysis techniques in modeling and understanding sociotechnical systems

Abstract

The increased complexity of modern sociotechnical systems (STS) necessitates the need for a manageable representation of their attributes, to augment our understanding and enable the development of ways through which we can increase their effectiveness, efficiency, and safety. Although many of the methodologies developed in the Human Factors domain map and investigate system properties and network structures, the inclusion of the temporal dimension in the analysis of STS remains limited. In this paper we present how modeling and visualization of STS can be augmented with the incorporation of temporal interaction analysis techniques that enable a micro-level, fine-grained analysis of data. We provide an overview of temporal analysis techniques by breaking down their main function, requirements, types of research questions they can address, and the visualization properties they offer, attempting to enhance their use in system analysis. This overview can assist researchers in selecting an analysis technique, enabling the incorporation of temporality in STS analysis, and helping towards the design of improved and safer systems and interventions.

Sequential Behavioral Analysis: A Novel Approach to Help Understand Clinical Decision-Making Patterns in Extended Reality Simulated Scenarios

“…Use of sequential analysis has been suggested as a means to study learners' sequences of behaviors and transitions between them. 8,9 In essence, sequential analysis helps detect whether the occurrence of one event is linked to the subsequent occurrence of another event in real time. 10,11 Despite the fact that sequential studies provide correlational data only, the identification of close temporal relationships between 2 events can be used to identify educational targets for improvement and potentially be linked to learning outcomes.…”

“…Sequential analysis is a technique that helps identify sequential patterns present in a large amount of data. Use of sequential analysis has been suggested as a means to study learners' sequences of behaviors and transitions between them 8,9 . In essence, sequential analysis helps detect whether the occurrence of one event is linked to the subsequent occurrence of another event in real time 10,11 .…”