MACSc Project Presentation - Investigating Different Map Views for Different Landmark-based Navigation Instructions

Who: Ankita Patel

Title: Investigating Different Map Views for Different Landmark-based Navigation Instructions

Examining Committee:

Bonnie MacKay - Faculty of Computer Science (Supervisor)
Derek Reilly - Faculty of Computer Science (Reader)


People use various mobile applications on a daily basis to save time such as, bank applications, and transit apps. They also use mobile apps to help them in their day to day activities, such as map applications to help navigate familiar and unfamiliar areas. This research project explores a mobile navigation app called “Block Party” that helps people navigate and find locations while walking in a neighbourhood.

“Block Party” is an android mobile application that has three different map views: Map view, List view and Immersive view. This research explores the different features of Block Party for navigation tasks. We were also interested in learning which map view people find most helpful to learn and recall landmarks in their neighbourhood.

We conducted a field evaluation, where participants used the app on three different routes while using one of the three map views. All the participants followed the same routes but used different map views on the routes. After performing the study tasks (i.e. they asked to find different waypoints using different map views for each routes), participants filled in a questionnaire to test their neighbour familiarity related to each map views (e.g. to determine if they could identify different landmarks they would have come across while navigating the routes). Lastly, participants took part in a semi - structured interview which gave us overall idea about how they found each map views. We found that participants had a higher recall for locations when using the immersive view compared to the other map views. Participants indicated that they preferred the list view as it was more convenient to navigate than other two map views (Map view and Immersive view). 



Room 211, Goldberg Computer Science Building