If the owner of a first generation mobile phone pulled his device out of his pocket, it was clear what he wanted to do: He wanted to conduct a phone call. Over the course of the evolution of mobile phones this has changed: If the owner of a mobile phone pulls out his device nowadays, we cannot know in advance if he wants to make a phone call, read news, check the weather forecast or play a game.
A Thought Experiment. With the increased variety of functionalities that mobile phones provide to their users, the uncertainty of anticipating which function a user would use next also increased. However, a theoretical optimum for the design of current smartphones would be a phone that instantly has the correct application open when the owner wants to use it — as old phones always had the “phone call application” immediately available. Whereas the dial pad was directly available for conducting a phone call on old mobile phones, nowadays a user first has to tell her phone that she wants to make a phone call by clicking on a telephone icon, before she can dial a number. An optimal smartphone would remove the additional effort that users need to make, which have resulted from the variety of applications that became available for mobile phones. Reasons for this optimal smartphone being impossible mainly come down to the uncertainty in modeling human behavior and people’s changing interests; sensor-based approaches bear an a-priori failure that leads to ambiguity.
So, given that we cannot design a perfect multifunctional phone, what can we do to come such an idea as close as possible? You can find more thoughts on this in my thesis.
Mobile phones have evolved from communication devices to multi-purpose computing devices. However, smartphones still use full-screen notifications for incoming calls, which interrupt whatever activity the user was already engaged in. We propose new designs that allow users to postpone calls and also to multiplex by way of a smaller partial-screen notification. We report on a small-scale controlled lab study as well as a large-scale study in-the-wild. Our contribution is an enhanced interaction design for handling incoming calls on smartphones.
The number of available mobile applications is steadily increasing. People have rapidly adopted application stores as means to customize their devices with various functionalities that go beyond communication. Understanding the principles of mobile application usage is crucial for supporting users within this new ecosystem. In this paper, we investigate how people organize applications they have installed on their devices. We asked more than 130 participants for their habits for icon arrangement and collected more than 1,400 screenshots of their devices’ menus to further ground our findings. Based on this data we can distinguish five different concepts for arranging icons on smartphone menus, e.g. based on application usage frequency and applications’ functional relatedness. Additionally, we investigated how these concepts emerge in relation to frequency of application installations, removals and icon rearrangements, as well as users’ experience levels. Finally we discuss implications for the design of smartphone launchers, and highlight differences to icon arrangement on stationary computers.
AppFunnel: A Framework for Usage-centric Evaluation of Recommender Systems that Suggest Mobile Applications Matthias Böhmer, Lyubomir Ganev, Antonio Krüger
In: Proceedings of IUI ’13. Santa Clara 2013, USA (to appear).
Mobile phones have evolved from communication to multi-purpose devices that assist people with applications in various contexts and tasks. The size of the mobile ecosystem is steadily growing and new applications become available every day. This increasing number of applications makes it difficult for end-users to find good applications. Recommender systems suggesting mobile applications are being built to help people to find valuable applications. Since the nature of mobile applications differs from classical items to be recommended (e.g. books, movies, other goods), not only can new approaches for recommendation be developed, but also new paradigms for evaluating performance of recommender systems are advisable. During the lifecycle of mobile applications, different events can be observed that provide insights into users’ engagement with particular applications. This gives rise to new approaches for evaluation of recommender systems. In this paper, we present AppFunnel: a framework that allows for usage-centric evaluation considering different stages of application engagement. We present a case study and discuss capabilities for evaluating recommender engines by applying metrics to the AppFunnel.
Falling Asleep with Angry Birds, Facebook and Kindle – A Large Scale Study on Mobile Application Usage Matthias Böhmer, Brent Hecht, Johannes Schöning, Antonio Krüger, Gernot Bauer
In: Proceedings of Mobile HCI ’11, Stockholm 2011, Sweden.
While applications for mobile devices have become extremely important in the last few years, little public information exists on mobile application usage behavior. We describe a large-scale deployment-based research study that logged detailed application usage information from over 4,100 users of Android-powered mobile devices. We present two types of results from analyzing this data: basic descriptive statistics and contextual descriptive statistics. In the case of the former, we find that the average session with an application lasts less than a minute, even though users spend almost an hour a day using their phones. Our contextual findings include those related to time of day and location. For instance, we show that news applications are most popular in the morning and games are at night, but communication applications dominate through most of the day. We also find that despite the variety of apps available, communication applications are almost always the first used upon a device’s waking from sleep. In addition, we discuss the notion of a virtual application sensor, which we used to collect the data.