Lab’s TypeTester App to Bring Big Data to Visual Design
The MIT AgeLab has conducted research on the significance of typeface legibility as it relates to driver behavior since 2010. With computer interfaces and in-vehicle menus now commonplace in cars, the ability of the driver to quickly read text inside the vehicle before returning her attention to the road has become an important consideration for designers and scientists alike.
The Lab’s typeface study began in the Miss Daisy driving simulator. Here, researchers discovered that different typefaces had an impact on the driver’s ability to respond to in-vehicle text. This finding opened the way to a host of more subtle questions: how might elements such as contrast, font size, thickness, and small stylistic differences , etc., affect typeface legibility? Since Because it was not feasible to use Miss Daisy exclusively for this line of research, AgeLab research scientist Jonathan Dobres, PhD, developed a computer-based method for conducting the studyresearch. This model greatly increased the efficiency of research into these types of questions, but was still limited to laboratory settings and relatively small batches of data.
Consequently, the Lab, primarily via the work of Karola Klarl, a Master’s candidate from the University of Augsburg, Germany, developed an application called TypeTester, a tool that will allow research subjects to participate in the AgeLab’s typeface study remotely using an Android smartphone. The idea of using smartphones as a data collection research tool has precedence in Apple’s HealthKit and ResearchKit, which together leverage all the sensors in the iPhone to monitor specific health issues of app users and deliver that data to research hospitals. By conducting the study in this manner, the Lab will be able to reach a very large number of participants, communicate with them via app notifications, and leverage some “big data” in pursuit of answering design questions. The study will be structured so that participants receive experimental prompts in the form of daily “challenges.” These features should lead to a far higher level of subject participation than laboratory-based work, at the expense of giving up the high level of experimental control afforded by the laboratory environment.
The goal of this research is not to discover any sort of “best typeface,” but to identify the trade-offs that come with balancing aesthetics with utility, giving providing designers data-driven guidelines to use in their typeface decisions.
The TypeTester app is finished, with beta testing complete, and will be made public on Google Play for those who own an Android phone in mid-December.
Further information about the project can be found here.
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