As mobile web browsing becomes more commonplace, it is interesting to investigate the patterns of users’ focus. The authors propose, exploiting the findings in the research, an appropriate software architecture that takes into account the changing attention of users during the navigation of web pages. The basic idea is that a commercially available Internet of Things (IoT) can be used for exploratory research; that is, relatively cheap electroencephalogram (EEG) tools can be used for the scientific investigation of user behavior when users are reading and looking at websites.
This conference proceedings paper was published in a short paper format; that is, according to publication conventions, it reports the basic ideas and novelties without the requirement of scientific rigor or meticulous investigation. The content of the paper can be assessed primarily by the design science research paradigm, and secondarily on a systematic, empirical study that is evaluated by descriptive statistics information. However, the paper conforms only to the basic requirements of a research paper, in that it presents a design artifact in the form of an outline architecture description; the statistical sample can hardly be considered as significant (the Hungarian professor of mathematics Rényi stated that 20 samples may demonstrate significant statistical behavior).
The research question that is raised is how user attention and interest can be tracked to make websites more responsive and increase user inclusion. The authors propose an architecture for mobile web browsing that exploits an EEG kit (a wearable and portable kit) and the architecture building blocks of mobile operating systems: browsers, open-source Java tools, and so on. The idea may be interesting for a wider research community having not enough financial resources to perform serious research on the usage of the web and users’ behavior.
From the viewpoint of design science research, the authors provide only some elementary components in spite of the research requirements that are prescribed in the design science research paradigm; the paper contains only a description of the software architecture consisting of the relevant components. The architecture description lacks the presentation of the applied methods, evaluation of the design approach, and compliance between the design artifacts and the requirements.
For measuring attention and eye movement (blinks), the authors developed metrics and then carried out measurements. Employing this approach, the authors try to map the attention level of users to sections and block elements of Hypertext Markup Language (HTML) web pages using scroll position in the experiment. The authors assess neither the adequacy of the exposed solution for usability by customers nor the soundness of the approach for potential researchers following a similar path. The data collection concentrated on the use of web pages by some users. The presented statistical results and diagrams can hardly be considered significant because the user sample contains two people. However, it opens a way in which meticulous and statistically profound investigation could be carried out.
The result is a logical and partly physical-level software architecture that contains logical platforms (modules) with extension to the EEG toolset. The authors prove that the architecture and the software design are operational in a small laboratory environment. This may be interesting for researchers and practitioners working in IoT and human-machine interaction fields and may provide a chance for extended research on IoT and similar web-page-related fields.
