Testing hypothesis on qualitative data: the use of hyperRESEARCH computer-assisted software
Social Science Computer Review
Extracting usability information from user interface events
ACM Computing Surveys (CSUR)
MacVisSTA: a system for multimodal analysis
Proceedings of the 6th international conference on Multimodal interfaces
Exploratory sequential data analysis: foundations
Human-Computer Interaction
Developing process models as summaries of HCI action sequences
Human-Computer Interaction
A Trace-Based System for Technology-Enhanced Learning Systems Personalisation
ICALT '09 Proceedings of the 2009 Ninth IEEE International Conference on Advanced Learning Technologies
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We present a new method and tool for activity modelling through qualitative sequential data analysis. In particular, we address the question of constructing a symbolic abstract representation of an activity from an activity trace. We use knowledge engineering techniques to help the analyst build an ontology of the activity, that is, a set of symbols and hierarchical semantics that supports the construction of activity models. The ontology construction is pragmatic, evolutionist and driven by the analyst in accordance with their modelling goals and their research questions. Our tool helps the analyst define transformation rules to process the raw trace into abstract traces based on the ontology. The analyst visualizes the abstract traces and iteratively tests the ontology, the transformation rules and the visualization format to confirm the models of activity. With this tool and this method, we found innovative ways to represent a car-driving activity at different levels of abstraction from activity traces collected from an instrumented vehicle. As examples, we report two new strategies of lane changing on motorways that we have found and modelled with this approach. © 2012 Wiley Periodicals, Inc.