How quickly do we learn conceptual models?

In organizations, conceptual models are used for understanding domain concepts. Learning the domain from models is crucial for the analysis and design of information systems that are intended to support the domain. Past research has proposed theories to structure conceptual models in order to improve learning. It has, however, never been investigated how quickly domain knowledge is acquired when using theory-guided conceptual models. Based on theoretical arguments, we hypothesize that theory-guided conceptual models expedite the initial stages of learning. Using the REA ontology pattern as an example of theoretical guidance, we show in a laboratory experiment how an eye-tracking procedure can be used to investigate the effect of using theory-guided models on the speed of learning. Whereas our experiment shows positive effects on both outcome and speed of learning in the initial stages of learning, the real contribution of our paper is methodological, i.e. an eye-tracking procedure to observe the process of learning from conceptual models

The Use of Eye-tracking in Information Systems Research: A Literature Review of the Last Decade

Eye-trackers provide continuous information on individuals’ gaze behavior. Due to the increasing popularity of eye- tracking in the information systems (IS) field, we reviewed how past research has used eye-tracking to inform future research. Accordingly, we conducted a literature review to describe the use of eye-tracking in IS research based on a sample of 113 empirical papers published since 2008 in IS journals and conference proceedings. Specifically, we examined the methodologies and experimental settings used in eye-tracking IS research and how eye-tracking can be used to inform the IS field. We found that IS research that used eye-tracking varies in its methodological and theoretical complexity. Research on pattern analysis shows promise since such research develops a broader range of analysis methodologies. The potential of eye-tracking remains unfulfilled in the IS field since past research has mostly focused on attention-related constructs and used fixation count metrics on desktop computers. We call for researchers to utilize eye-tracking more broadly in IS research by extending the type of metrics they use, the analyses they perform, and the constructs they investigate